EES & DER Collaboration: Procedural Guide for Energy Ecosystems

Ref. Ares(2017)5304792 - 30/10/2017
Research and Innovation Action
Storage capacity sharing over virtual neighbourhoods
of energy ecosystems
H2020 LCE-01-2016: 731285
WP3 – SHAR-Q compliance to standards and
definition of SHAR-Q processes and architectures
D3.3 - Procedural guides for collaboration of EES
and RES operators
Document Info
Contractual Delivery Date:
31/10/2017
Actual Delivery Date:
30/10/2017
Responsible Beneficiary:
ATOS
Contributing Beneficiaries:
BVR; UBI; ENERC; EEE; CEPV; ICCS; DEDDIE; EnG;
ATOSCZ
Dissemination Level:
Public
Version:
1.0
This project has received funding from the European Union’s Horizon 2020 Framework
Programme for Research and Innovation under grant agreement no 731285
Document ID: WP3 / D3.3
Document version: 1.0
Document Information
Document ID:
D3.3 Procedural guides for collaborations of EES and DER
operators
Version Date:
31/10/2017
Total Number of Pages:
60
Keywords:
Internet of Energy, Renewable Energy Resource, Processes,
Distributed Energy Storage, Interoperability, Integration,
Guidelines
Authors
Full Name
Beneficiary /
Organisation
e-mail
Role
Martin Wagner
Ugo Stecchi
Viktor Oravec
Stefan Vanya
ATOS
Overall Editor
Contributor
Contributors
Christoph Neudhart
Christian Kusmitsch
UBIMET Gmbh
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
Joao Oliveira
Mário Saleiiero
Natalie Samovich
Ines Fonseca
ENERC
[email protected]
[email protected]
[email protected]
[email protected]
Contributors
Andrea Moser
Joachim Hacker
Manfred Hotwagner
EEE
[email protected]
[email protected]
[email protected]
Contributors
Uxue Goitia
CEPV
[email protected]
Contributor
Evangelos Karfopoulos
Joannis Karakitsios
ICCS
[email protected]
[email protected]
Contributors
Maria Kouveletsou
Konstantinos Anastasakis
DEDDIE
[email protected]
konstantinos.anastasakis@gmai
l.com
[email protected]
Contributors
EnG
[email protected]
Contributor
ATOS CZ
[email protected]
[email protected]
Contributors
BAVENIR
Konstantinos Magkaniotis
Martin Zloklikovits
Adam Kapala
Ondrej Mamula
Contributors
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Reviewers
Full Name
Beneficiary /
Organisation
e-mail
Date
Claudia Battistelli
RWTH
27/10/2017
Konstantinos Magkaniotis
HEDNO
[email protected]
[email protected]
25/10/2017
Version history
Version
V0.1
Date
10/05/2017
Comments
First version of the ToC
V0.2
17/09/2017
First contributions from partners
V0.3
20/09/2017
Improvements to figures related to process chapter
V0.4
25/09/2017
Second cycle of contributions from partners
V0.5
30/09/2017
Third cycle of contributions from partners
V0.6
03/10/2017
Version for internal review
V0.7
09/10/2017
Improvements after internal review
V0.8
13/10/2017
Version for QA process
V0.9
26/10/2017
Final version after improvements from QA process
V1.0
30/10/2017
EC Submission
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Executive Summary
Distributed Energy Resources (DER) has the capability to drive through disturbances,
contribute to reliability services, and follow dispatch signals; capabilities that are used either
directly or through aggregators for a number of emerging services like demand response,
micro-grids, or virtual power plants. Therefore its increasing penetration will simplify
management of disturbances, provide reliability services, and follow dispatch signals;
capabilities that can be used either directly or through aggregators for many emerging
services like demand response, micro-grids, or virtual power plants; but also increase
complexity of the ICT solutions required to manage and integrate DER deployments.
The inherently variable output of almost all renewable energy sources, e.g. photovoltaic (PV)
or wind-turbine systems, can be mitigated using Electric Energy Storage systems (EES or
ESS), crucial to enable an effective integration of renewable energy into the local generation
of energy supply.
By linking renewable sources, storage systems and (home) energy management systems
h(EMSs) – currently happening in many European countries – new business models can be
developed for installations that depend on self-consumption of the electricity generated
locally (micro- or nanogrids), installations that could be aggregated in virtual power plants
(VPPs).
This deliverable “D3.3 - Procedural guides for collaboration of EES and RES operators” uses
a process approach to describe the most relevant activities performed by the main processes
involved in the generation, storage and consumption of energy.
The suit of processes covers all possible combination of DER, EES installations in low
voltage grid environment (based on use cases developed by the pilot sites – see DER & ESS
Use Cases chapter) to: firstly, detail interoperability requirements “behind the meter” and
regionally and, finally describe how SHAR-Q, as (h) EMS, will support the automation of the
processes.
This process approach is supported by the SHAR-Q pilot sites and will lead to the
normalization of load profiles based on generation, storage, or consumption opportunities.
Furthermore, it provides a more precise perception of the roles expected from affected
stakeholders, and the new business models that are expected to emerge from the
interoperability options in DER and ESS using (h) EMSs.
Consequently, the evolution and growth of an energy market is constrained by the existence
of competitive products and services, which meet the standards of the industry and take an
active role in the improvement of (h) EMS for home / building automation, all integrated into
attractive solutions from the end-user perspective.
As an initial conclusion, the selection of the models and manufacturers that will provide the
equipment for generation and storage and the selection of (h) EMSs are the most relevant
aspects stakeholders must take into account for the interoperability of DER and ESS
solutions.
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Table of Contents
1.
Introduction ..................................................................................................... 10
2.
DER & ESS Use Cases .................................................................................... 12
2.1
The Challenge of RES Variability .......................................................................13
2.2
The Use Cases for DER ......................................................................................13
2.2.1
DER use case by UBIMET (Austria) ..................................................................14
2.2.2
DER Use case for EEE (Austria) .......................................................................15
2.3
The Use Cases for EES.......................................................................................16
2.3.1
UBIMET´s use case (Austria) ............................................................................17
2.3.2
EEE’s use case (Austria)...................................................................................18
2.3.3
ENERCOUTIM´s use case (Portugal) ...............................................................19
2.3.4
EES systems behind the Meter .........................................................................20
2.3.5
EVs Storage Systems .......................................................................................22
2.3.6
Stand-alone Energy Systems (SAPS) ...............................................................23
2.3.7
Grid-connected microgrids ................................................................................23
2.3.8
Virtual Power Plants ..........................................................................................24
2.4
Advantages of DER-EES integration .................................................................25
2.4.1
3.
Advantages of RES-EV synergy........................................................................26
Guidelines for Integration Models.................................................................. 27
3.1
Processes ............................................................................................................27
3.2
High-Level DER Process ....................................................................................30
3.3
High-Level ESS Process .....................................................................................32
3.4
High-Level Consumption Process .....................................................................34
3.5
Integration behind the Meter ..............................................................................35
3.5.1
Integration of EVs (Greece) ...............................................................................36
3.5.2
Integration in Portugal .......................................................................................36
3.5.3
Integration in Austria .........................................................................................37
3.6
Integration at the Regional Level .......................................................................38
3.6.1
3.7
Regional integration in Austria...........................................................................39
Challenges for DER and ESS interoperability ...................................................42
3.7.1
Energy Infrastructure Integration Issues ............................................................42
3.7.2
Addressing the SHAR-Q integration barriers .....................................................43
3.8
Integrated DER and ESS use cases ...................................................................45
3.9
Alignment with SHAR-Q Platform ......................................................................45
3.9.1
SHAR-Q integration points ................................................................................46
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3.9.2
Business target information processing .............................................................47
3.9.3
Alignment of information flow with SHAR-Q logical components .......................50
3.9.4
Logically possible interactions among Energy Infrastructures and Services ......52
4.
Conclusions ..................................................................................................... 57
5.
References ....................................................................................................... 60
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Table of Figures
Figure 1. Internet of Energy ..................................................................................................11
Figure 2. Power producers in the use case-grid area of the Strem municipality ....................15
Figure 3. Map of a possible infrastructure in the pilot in Austria ............................................16
Figure 4. Grid area of the local DSO “Energy Güssing” ........................................................18
Figure 5. Schematic overview Martim Longo pilot.................................................................20
Figure 6. Schematics of SOLAR LAB and SDP Use cases ...................................................21
Figure 7. Components of a Process .....................................................................................28
Figure 8. Legend used for Process Figures ..........................................................................29
Figure 9. Processes related to Energy flow (from generation to consumption) .....................30
Figure 10. Sub-Processes for DER.......................................................................................32
Figure 11. Sub-Processes for EES .......................................................................................33
Figure 12. Sub-process of Energy Consumption ..................................................................35
Figure 13. Integration at the local level Austria .....................................................................37
Figure 14. Classical electricity grid .......................................................................................39
Figure 15. Grid of the local DSO – part Strem ......................................................................40
Figure 16. Integration at the regional level Austria ................................................................41
Figure 17. P2P/B2B/B2P using their power line to share energy (Local) ..............................45
Figure 18. P2P/B2B/B2P using DSO’s power lines to share energy (Local/regional) ............45
Figure 19. Example of “legacy” energy infrastructure ...........................................................46
Figure 20. Example of “connected” energy infrastructure .....................................................47
Figure 21. Generic information flow process, centralized approach ......................................48
Figure 22. Generic information flow process using gossip algorithm, decentralized approach
.............................................................................................................................................49
Figure 23. Mapping components on generic information flow process, centralized approach
.............................................................................................................................................50
Figure 24. Mapping components on generic information flow process, decentralised
approach ..............................................................................................................................51
Figure 25. Logically possible information interactions using Gossip algorithm for
communication among Smart Energy Facilities ....................................................................52
Figure 26. SHAR-Q platform component decomposition, information process flow and
platform alignment, centralized approach .............................................................................53
Figure 27. SHAR-Q platform component decomposition, information process flow and
platform alignment, decentralized approach .........................................................................54
Figure 28. SHAR-Q Added Value Service influences Energy flows in the grid ......................55
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Table of Tables
Table 1. DR and Flexibility properties comparison ................................................................13
Table 2. Target Results Martim Longo ..................................................................................21
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List of Acronyms and Abbreviations
Term
Description
BRP
Balancing Responsible Party
DG
Distribution Grid
DR
Demand Response
DS
Distribution System
DSO
Distribution System Operator
ED
Energy Digitalisation
EES
Electrical Energy Storage
EMS
Energy Management Systems
ESCO
Energy Service Company
ESS
Energy Storage System
EV
Electrical Vehicle
hEMS
Home Energy Management Systems
HW
Hardware
ICT
Information and Communication Technologies
IoE
Internet of Energy
IoT
Internet of Things
IPP
Independent Power Producer
LCOS
Levelled Cost of Storage
PV
Photovoltaic
RES
Renewable Energy Sources
SAPS
Stand-alone Energy Systems
SPS
Small Power System
SW
Software
VPP
Virtual Power Plant
VU
Virtual Utility
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1.Introduction
Electric power systems worldwide are transforming to a resource mix that relies less on
coal and nuclear while integrating more natural gas, wind, solar, distributed generation,
and flexible loads. Specifically, Distributed Energy Resources (DER), the Energy
Digitalisation (ED) and the Internet of Things (IoT) are a rapidly growing part of this
transformation.
The potential impacts of DER have been extensively studied and understood at
distribution level but this is not the situation for Small Power System (SPS), particularly
for “behind-the-meter” models and their respective network elements.
As the penetration level of DER increases, the classical transmission model of
distribution system load (netted generation and load) is not valid anymore; the unique
characteristics of DER must be modelled separately to analyse and validate its impact
on continuously maintaining the balance between demand and generation of balancing
areas. Additionally, balancing activities will come to be more challenging in regions with
high levels of DER as these activities will require resources located on the SPS as well
as on the distribution system (DS), in situations where both systems do not interact
openly.
However the output of almost all renewable energy sources, e.g. photovoltaic (PV) or
wind-turbine systems, are inherently variable; energy output varies by season, time of
day, and over much shorter intervals due to intermittent clouds and shading. In each of
these time domains, output variability can be mitigated using Electric Energy Storage
Systems (EES or ESS), crucial to enable an effective integration of renewable energy
into the local generation of energy supply.
In order to meet worldwide goals for reduction of greenhouse-gas emissions, a
substantial portion of new generation capacity must come from renewable sources.
While the costs for renewable generation continue to fall, integrating and effectively
using these new resources, especially in regions with weak grid infrastructure, will
require energy storage.
In the same way, the IoT is becoming an increasingly growing topic concerning the
energy industry. It is a concept that refers to the interconnection of any device with any
other around it. The analyst firm Gartner1 says that by 2020 there will be over 26 billion
connected devices. Therefore, the IoT is a large connected network that includes
connections between people-people, people-things, and things-things.
1
Jacob Morgan – A Simple Explanation Of 'The Internet Of Things' (May 2013)
https://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-canunderstand/#121f505b1d09
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Figure 1. Internet of Energy2
The Internet of Energy changes everything about electricity.
The energy distribution grid can be understood as a pool of energy where people buy
and sell energy, all managed by the local energy company responsible for the energy
supply. The Internet of Energy (IoE), by enabling a shared economy in an open market,
will impact the cost of energy available in this pool to the point where energy would only
have a representative cost associated to the use of distribution networks [MOR14].
Open energy market means that energy companies to maintain the loyalty of their
customers will have to compete with other types of customers, the prosumers that sell
their excess of energy with superior conditions. Open markets and IoE means that
customers and stakeholders can choose how to manage their energy flows – e.g. buy
only energy produced by renewable sources, also means that they will have access to
cheaper energy and creates the fundaments for a shared economy. It likewise means
that energy companies must be able to change their business models based on market
requirements and with minimal inversions in infrastructure.
As a result, energy can be cheaper and originate from RES, integrated in the local
distribution grid with ESS, and sustained by automated algorithms managed with
software running on devices; and leading to new market rules that will require a
European energy policy to ensure everyone is playing the same game.
2
Anissa Dehamna, Alex Eller, William Tokash, Five Trends for Energy Storage in 2016 and Beyond (2016), White
Paper.
http://naatbatt.org/wp-content/uploads/2017/05/Insert-for-Anissas-blog.png
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2. DER & ESS Use Cases
Electric power systems worldwide are transforming to a resource mix that is less
dependent on coal and nuclear while integrating more natural gas, wind, solar, and
distributed generation. Specifically, Distributed Energy Resources (DER), the Energy
Digitalisation (ED) and the Internet of Things (IoT) are rapidly growing parts of this
transformation.
Electric Energy Storage (EES) is crucial to enable an effective integration of renewable
energy into the local generation of energy supply, its inherent variability of renewable
sources of energy. Therefore the combination of a PV or Wind farm with EES not only
avoids intermittency, it also provides balancing services. Technology is more and more
responsible for manage the variable generation of solar and wind energy.
Even ESSs remain expensive and with significant upfront investment, the installations of
ESSs are increasing dramatically around the world as system costs are rapidly
decreasing and as energy markets are being reformed to allow for the use of more
distributed resources. Every second installation of PV panel is bundled with EES in
Germany3.
Distributed and remote power systems have enormous potential to provide service
around the world, but are subject to a number of barriers including differences in the
physical structure of the grid, needs and desires of end users, and the regulatory and
market structure in a given country or region. Since the impacts of distributed energy
resources (DER) on the grid vary considerably by technology and region, it is necessary
to understand the factors that impact their interoperability [MAR15].
While the costs for renewable generation continue to fall, integrating and efficiently using
these new resources will require energy storage. Experience over the past several
decades has shown that the traditional, centralized grid cannot or will not cost-effectively
provide the constantly growing of energy needs in a reasonable amount of time.
Big market players, like E.ON and ENEL, are splitting their companies by cutting off their
departments holding fossil fuels generation in an effort to save their revenues which
decrease as the crude oil prices fall and cheap energy from DER installations rapidly
grows. France and Great Britain established capacity markets to ensure sustainability of
electricity reflecting rapid growth of DER generation. Similarly Poland plans to open the
capacity market at the end of 2017 in order to avoid premature closure of current coal
plants. On the other hand, Germany believes the capacity market could deform prices on
energy market even more; however, they are not going this way. Influence of DER on
energy market is indisputable. Sharing EES and flexibility mechanisms contributes to
ensuring security of supply and becoming integral part of the energy market, no matter
which capacity mechanism is present4.
3
The interview led by Jakub Kučera, an analyst of the RSJ Financial Group, and Michal Vít, a researcher in the
EUROPEUM independent think-tank.
http://oenergetice.cz/rozhovory/jorg-jasper-za-deset-let-budeme-flexibilite-premyslet-jinak/
4
Main reasons why European energy giants like CEZ, E.ON and Enel are losing their former power are
Decentralization, relocation of production to renewable sources and net production of CO2-free electricity.
http://oenergetice.cz/spolecnosti-svet/zachrani-se-e-on-zmenou-sve-strategie/
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The following sections of the chapter describe existing DER use cases based on the
pilot sites in the SHAR-Q project, enabling the analysis of the variability impact on
energy generated and potential of stability that provide EESs.
2.1 The Challenge of RES Variability
The output of almost all renewable energy sources, e.g. photovoltaic, wind turbines, etc.,
is inherently variable; output variability can introduce grid planning, operation and
stability issues that may require mitigation.
As more distributed energy resources are integrated into the grid, variability can be
offset by a range of technologies and programs, including battery storage on either side
of the customer meter, thermal storage, and Demand Response (DR). Combinations of
these options are often most effective to mitigate variability and raise the utility value of
distributed solar fleets.
Significant aid on power generation variability may be the consumers’ flexibility.
Flexibility covers short time consumption and production capacity provided by consumer
on demand. While DR was initially seen as voluntary reaction on market signals,
flexibility could be seen as a precisely measured reserved amount of power which can
be managed and controlled in both directions – production and consumption. Thus the
flexibility is a significant tool for both grid and market stabilization. Therefore flexibility
rather than DR “properties” fits perfectly to aggregation scenario and can be seen as
subset of aggregation.
Table 1. DR and Flexibility properties comparison
Flexibility
DR
Common duration time > 30 min
-
X
Fast reaction time
X
-
Grid stabilization
X
X
Cost per KWh optimization
X
X
Consumers’ asset controlled
X
-
Regulate consumption
X
X
Regulate production
X
-
Fits for energy services
X
X
Fits for aggregation services
X
-
2.2 The Use Cases for DER
It is relevant that energy market players understand DER functionality and develop a set
of guidelines to assist in modelling and assessments such that owners/operators of
generation and storage solutions can evaluate and model DER in the electric system.
Data requirements and information sharing across the transmission-distribution (T-D)
interface should also be further evaluated to allow for adequate assessment of future
DER deployments. Both off-line static data and real time data fulfil the role. Off-line static
data for instance for Mid-term Adequacy Forecast and on the opposite side the up to real
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time data for Economic Dispatch and Optimal Power Flow numerical optimization, both
are held on transmission level of grid operation.
DER will increasingly have state-of-the-art capabilities for active power control and
reliability services. However, there are differences in how DER is deployed within a grid
and the characteristics of the services and responses that they provide, so these
differences must be understood and modelled appropriately. Simultaneous efforts to
improve DER interconnection standards will assist in establishing criteria and
requirements for interconnection of DER to electric power systems.
Distributed Energy Resources encompass a broad set of solutions that include systems
and technologies designed to operate closer to customers on the electricity grid into
emerging markets, the reliability of local power supplies is a key consideration when
evaluating potential locations.
A wide deployment of renewable DER technologies could modify the demand profile of
power systems, while also affecting their management and operation. In this respect, a
large scale integration of RES could potentially require significant reinforcements of the
existing grid infrastructure. However, such investments can be avoided or postponed if
new operational strategies are applied. More specifically, demand-response services
can enable a larger integration of RES in the distribution network, without compromising
the network stability, while also avoiding or deferring grid reinforcements.
The following sub-sections are summaries of the use cases described in SHAR-Q’s
deliverable D2.4. They have been included to provide additional context to next chapters
and support conclusions.
2.2.1 DER use case by UBIMET (Austria)
For UBIMET as a provider of meteorological data and information the use case for
services imply close to real time meteorological data, hence gWeather solution provides
the basis data for demand and generation forecasts for both, local and regional level.
More precise weather forecasting reduces uncertainty in the generation and demand
prediction by at least adding a band of confidence to it. Price building and negotiations
between peers and stakeholders are supported by reasonable forecasts. These
forecasts, for UBI use cases under this topic, are regional and comprise meteorological
domains, and not necessarily single geographical locations.
Services operated in the use case are:


Generation forecast for a region (e.g. grid coverage area for usage within SHARQ).
High temporal resolution Solar Record for regions with poor solar mapping and
unreliable forecasts for return-on-investment calculations (for investment and
operation of e.g. PV): this covers the need for a long-term view and a more
realistic solar record based on quasi-climatology (in this respect this means:
reanalysis of the past 30 years of irradiance).
In order to implement these services, SHAR-Q must provide power profiles for a region,
e.g. substation data or aggregated data from a low-voltage grid in highest possible
resolution, every 10min, for analysis and forecast. Data is gathered with API access to
SHAR-Q. The problem of intermittency and variability of renewable generation can thus
be handled for intraday and interday horizons.
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2.2.2 DER Use case for EEE (Austria)
The Austrian use case focuses on processes for shared economy over RES and EES,
targeting prosumers with decreased cost of kWh in the energy ecosystem.
The main actors within this energy ecosystem are mainly:





Consumers: Households, municipalities, companies with smart meters installed;
DER operator: In the case of the Austrian pilot, will be mainly photovoltaic plant
operators;
Electrical Energy Storage owners: Consumers that own battery storage units;
Prosumers: Consumers that own energy production units (photovoltaic plants,
etc.) and maybe also electrical energy storage units. The prosumers in the
Austrian pilot will mainly consist of buildings with different load profiles
(residential prosumers, work places, SMEs, etc.), energy production units and in
some cases storage units;
DSO: in the case of the Austrian pilot it is a local DSO that owns a small part of
the grid of the whole province. The pilot will be within the grid of this local DSO.
Figure 2 shows the number of the installed power in the public sector within the
considered are for the use case of Austria. The contribution of private households or
SMEs in the area to the power production is actually under evaluation and cannot be
estimated.
Figure 2. Power producers in the use case-grid area of the Strem municipality
The grid area of the use case of Austria in the Strem municipality shows a significantly
high share of PV-production and additional 1 MW photovoltaic plants have been realized
within the past few weeks and additional 1 MW are already in planning.
So the use case of Austria will mainly be composed of a set of prosumers with installed
PV-plants on the production side.
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Figure 3. Map of a possible infrastructure in the pilot in Austria
The core of the use case will be the retirement and care building of the municipality, as it
has a huge energy demand, a 170 kW PV-plant installed and in addition a 25 kWh
battery storage is planned to be integrated soon. On the DER side of the grid area of the
use case in Austria, it is foreseeable that there are additional energy power units, like the
biogas CHP plant, but the integration of such a plant is not part of the SHAR-Q approach
and consequently only PV-plants on DER side are part of the use case.
2.3 The Use Cases for EES
The ability to provide backup power is particularly important to the value proposition of
battery storage systems. While controllable water heaters and other forms of thermal
energy management can reduce electricity costs and can provide some services to grid
operators, they are able to provide energy for critical loads during an outage, fast
levelling of intermittent DER production, voltage and frequency decoupling, fast
frequency cycling attenuation or to firm the PV resource as a fixed amount of power, etc.
Energy storage is a crucial tool for enabling the effective integration of renewable energy
and unlocking the benefits of local generation and a clean, resilient energy supply. The
technology continues to prove its value to grid operators around the world who must
manage the variable generation of solar and wind energy. However, the development of
advanced energy storage systems (ESS) has been highly concentrated in select
markets, primarily in regions with highly developed economies.
There are several fundamental contributing factors that set the stage for energy storage
in different regions. Each country’s energy storage potential is based on the combination
of energy resources, historical physical infrastructure and electricity market structure,
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regulatory framework, population demographics, energy-demand patterns and trends,
and general grid architecture and condition. The efficiency and/or level of quality of
performance of these fundamental factors create demand for new products and
services, and energy storage has increasingly being sought to meet these emerging
requirements.
Despite rapidly falling costs, ESSs remain expensive and the significant upfront
investment required is difficult to overcome without government support and/or low-cost
financing. This type of advanced technology requires significant knowledge and
expertise to be developed and operated cost-effectively. Furthermore, the services
provided by ESS systems are often not properly valued or recognized within existing
energy market regulations. Even with these barriers, installations of stationary ESSs are
increasing dramatically around the world as system costs are rapidly decreasing and as
energy markets are being reformed to allow for the use of more distributed resources.
Experience over the past several decades has shown that the traditional, centralized grid
cannot or will not cost-effectively provide even basic electrical service to underserved
populations in a reasonable amount of time in a foreseeable future. Distributed and
remote power systems have enormous potential to provide service around the world, but
are subject to a number of barriers:
1. Physical grid infrastructure: The physical structure of any electricity system will
have an impact on the market for energy storage. There are significant
differences among power systems around the world in both physical architecture
and operations due to historical patterns of customer living conditions and power
usage as well as to specific grid configurations designed to accommodate these
circumstances.
2. Regulatory framework and market structure: The regulatory framework and
economic structure of an electricity market determines the level of competition
that exists at different levels of the electric power industry and is an important
consideration when examining the potential for energy storage deployments.
3. Population and Energy trends: Population demographics in countries around
the world also play a role in determining the structure of the power grid, and will
be an important factor in the development of energy storage markets. Countries
with more densely populated urban areas will require more concentrated
distribution circuits delivering higher voltage power, representative of the
European model.
4. Grid architecture and overall performance: The overall stability of the electrical
grid in a particular country or region is an important consideration in determining
the potential market for stationary ESSs. Additionally, operators of unstable grids
are likely to deploy utility-scale ESSs to minimize the likelihood of outages
affecting large numbers of customers.
Distributed Energy Resources encompass a broad set of solutions that include systems
and technologies designed to operate closer to customers on the electricity grid into
emerging markets, the reliability of local energy supplies is a key consideration when
evaluating potential locations.
2.3.1 UBIMET´s use case (Austria)
Similar to the RES use case, UBIMET’s EES use case comprises the creation and
implementation of generation forecasts for the respective generation site for solar
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Q registered user. The meteorological services for storage depend on the nature of
energy system of the user (e.g. PV plus storage plus heat pump requires a different set
of meteorological parameters than a PV that feeds into grid only). Forecast of
temperature in the above mentioned example time horizons might be relevant especially
when a heat pump is part of the system. In this case, when optimizing self-consumption,
demands on battery management vary with outside temperature as well.
Also, for optimal management of EES the tackling of intermittency is an issue. Fast
moving clouds, small clouds or fog is commonly not accounted for (or even accountable)
in prediction of irradiation. Real time generation forecast based on irradiation forecast
can provide a basis for battery management with different goals: self-consumption,
maximum safety of independence (quasi-insular operation), capacity sharing. The
service comprises maximum and average generation interday and intraday and
forecasts from minutes up to 10 days. Time resolution of irradiance around 10 min
should allow management algorithms to take into account even single clouds diminishing
PV performance, for the geographical pinpoint. This could drive the management based
on different goals.
2.3.2 EEE’s use case (Austria)
The use case of Austria contains a set of prosumers within a well delimited grid section
in the region, is owned by a local DSO and focuses on the establishment of processed
for shared economy over RES and EES.
The infrastructure of the grid area that will be researched within the Austrian pilot is
shown in the following figure:
Figure 4. Grid area of the local DSO “Energy Güssing”
As it is observable, it will be concentrated on the eastern part of the grid (marked in
green) of the local DSO, on the area of and around the municipality of Strem. This grid
section is the most critical one in the whole grid area of the DSO, because the number of
power production units grows rapidly. EES systems will therefore take over a very
important role in the use case of Austria to provide on the one hand a possibility to
release the grid in periods of overproduction and on the other hand to provide backup
power in periods of underproduction.
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The rest of the prosumers within the use case will be selected based on the existing
prerequisites (smart meters installed, installed battery storage systems etc.).
EES systems of the use case of Austria will be composed by a set of battery storage
systems installed at the prosumers place (retirement and care building, households,
public buildings, etc.).
Actual difficulty for the use case in Austria regarding EES systems is that there are
actually no battery storages installed. This means that incentives have to be created that
at the prosumers side, that already have PV-plants and smart meters installed, there will
additionally be implemented a storage system and that they are willing to be part of the
SHAR-Q collaboration network.
There are also some restrictions and uncertainties regarding the regulatory framework,
as there doesn’t exist a lot of experience in the region of implementing battery storages
especially in larger units and in public buildings.
In private households, there are some minor specifications for the integration on battery
systems in terms of security.
In public buildings there are some difficulties in the definition of the placement of the
storage system. Also the question of responsibilities and competences to decide the
correct placement and security requirements is unsolved yet. In general the regulation
for battery rooms I the Austrian standard “ÖVE_ÖNORM EN 50272 part 1 und part 2”
but the definitions for the latest battery storage developments aren’t yet incorporated
within this standard. Therefore the integration of battery storage systems and necessary
battery storage rooms is actually seen as a very complex issue and nobody gives
statements about the possibilities, limitations, etc.
This shows once again that there is actually no real experience with battery storage
systems in general and not a bit with larger scale battery storages. So the
implementation of battery storages in the Austrian pilot can become at some places a
challenging issue, due to inexperience of the respective authorities.
2.3.3 ENERCOUTIM´s use case (Portugal)
Shared renewable energy infrastructures designed to function as "plug and produce"
solution of the Solar Demonstration Platform will test the possibility to design and adapt
SHAR-Q peer to peer EES resource as the next step in renewable energy models
development for regional and interregional adaptation.
This use case will be contributing towards design and usage definition as well as
utilization of SHAR-Q platform for the electricity energy market that could be enhanced
through design and development of collaboration framework and value-added services.
Close collaboration with a wide network of stakeholders of the Demonstration Platform
and the Solar Lab infrastructures that ENERC is managing is contributing towards user
requirements definition and towards optimal system design to ensure better adaptability
towards the DER RES sector needs. Actors and infrastructures overview is presented
below in Figure 5. Schematic overview Martim Longo pilot.
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Figure 5. Schematic overview Martim Longo pilot
2.3.4 EES systems behind the Meter
Two types of storage facilities are being considered for deployment at SolarLab (SL) as
part of Solar Demonstration Platform. An important and evolving distributed generation
model based on self-consumption principles would be tested for storage integration.
Some discussions with equipment manufacturers are being conducted, and pending
outcomes of their involvement would be finalised at the pilot level.
Services for Platform Clients and DG will be deployed virtually and in simulation, by
integrating bigger storage system of approx. 100 kW at the Solar Demonstration
Platform. Such impacts as grid stabilisation (for DG) and predictive cash flow (for
platform clients) will be analysed. It is currently planned that a high power capacity and
high-speed response time storage system would be virtually placed between grid
injection point and transformer station of the CPV plants.
Solving grid issues at local level will be part of SHAR-Q demonstration. Once the service
has been deployed at the Solar Demonstration Platform, it will bring real-time reserve
activation to address real-time deviations to manage scheduled balance deviations
resulting from forecast errors (in load or generation) or incidents; and expect
demonstrate that local level solutions for grid issues are a more efficient and more
economical approach.
The following schematics (see Figure 6) outline the DEMO site set up as it is planned at
this stage of the project development and with the current assumption as to storage
technologies and other components. Final decisions as to the storage systems selection
and criteria should be taken during the next phases of project development.
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Figure 6. Schematics of SOLAR LAB and SDP Use cases
The system will have the solar modules which convert the solar radiation on a Direct
Current (DC) which goes to an inverter which will manage the charging of the battery
(DC) and also will convert DC to Alternating Current (AC) to be used in the EV charger
or in the load for self-consumption, or to supply to the main grid, in this stage there are
data logger to analyse and measure the production and consumption of different devices
(also temperature, humidity, solar radiation, etc.), and also a bi-directional smart meter to
measure the energy flow from the main grid or to the main grid.
It will also demonstrate storage providers’ solutions/ products ́ capability to deliver
services within local grid conditions (see Table 2).
Table 2. Target Results Martim Longo
Benefits area
Target results
DEMO
Demonstrate storage providers´ solutions/ products ́ capability to deliver services
within local grid conditions to benefit multi-stakeholder environment: infrastructure
managers; DER producers and grid operator.
DEMO
Demonstrate that energy storage of a medium size could have capacity of providing
DSOs with an effective option for reinforcing the network complementing cables/lines
and other investments in the electricity grid, allowing the DSO to save a significant
amount on network reinforcement cost.
FIN
Assessing the possibility of revenue streams beyond pilot phase of the project from
services Enercoutim will provide to DSOs/ Municipal systems/ other related projects
within DER RES value chain.
DEV
Design universal interface devices and protocols to enable DSO exchanges with DER.
INNO
Design a test environment of Energy storage and demand response as solutions to
balancing issues, as well as new options to address power quality, ancillary services
and network losses management.
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Benefits area
Target results
DEV
Test complementarity of the system to self-consumption model and assess an impact.
2.3.5 EVs Storage Systems
Lower emissions of greenhouse gases and other air pollutants require significant
changes in the public and private transportation aspect. Electric vehicles have been
identified as a keystone towards this direction, offering a great opportunity for greener
transportation. However, a fast growing of EVs integrated to the distribution system will
significantly modify the balancing challenges by triggering equipment overloads and
requiring potential reinforcement of the existing grid infrastructures.
Nevertheless, the demand elasticity offered by EVs during non-commuting periods can
assist in postponing or deferring premature grid investments. More specifically, the EV
battery capacity can be exploited as distributed storage device, while the EVs remain
parked (time periods representing more than 90% of the day). In this respect, the
elasticity offered by the EV demand can allow the increase of EV hosting capacity of
distribution networks, without any grid reinforcement.
The limited battery capacity of the EVs indicates their management as a fleet rather as
individual units in order to facilitate the provision of market oriented services. Such
services can be realized if the installed charging stations are employed with the ability to
adjust the power level of the charging process or if the charging stations enable the bidirectional power flow between the EV battery and the electricity grid. Bidirectional
power flow that allows the exploitation of V2G (vehicle-to-grid) capabilities of EVs
requires specially designed charging stations that allow power to be injected from the
station to the grid. Moreover, additional requirements should also be considered in the
EV side, in order for the EV battery to be able to provide power to the grid.
For use cases related to meteorological services on the local level the list of
requirements comprises: metadata of PV (roof top) installation: elevation, azimuth,
nominal system power, geographical position (lat/lon) and a history of generation (e.g.
three years of records generated power). For Storage forecast: Maximum and current
capacity should be provided over SHAR-Q API/adapter.
2.3.5.1 Greek Pilot Site
The pilot site in Meltemi, Greece, will focus on the synergy between the electric vehicles
and the renewable energy resources. The Meltemi campus, which is located near the
port of Rafina, comprises 170 cottages. Within the campus, there are various distributed
energy sources comprising a diesel generator, PVs and small residential wind turbine.
Charging stations will also be installed in the wider area of Rafina in order to observe the
synergy between EVs and RES. Therefore, Meltemi campus will enable the investigation
of the benefits of the SHAR-Q approach concerning the optimal sharing of EV/RES
capacities considering network operational constraints.
More specifically, the pilot site in Meltemi will:


Boost the e-mobility concept, while also improving the quality of the urban
environment due to EVs and the de-carbonisation of energy and transport sector
Facilitate the development of new business models for e-mobility service
providers
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


Allow the management of the grid capacity in respect to the transformer station
capacity
Offer additional income to EV users, compensating the increased EV cost
Allow increased RES and EV hosting capacity of current grid infrastructures,
while avoiding premature grid reinforcement
2.3.6 Stand-alone Energy Systems (SAPS)
Stand-alone energy systems commonly describe energy solutions for off-grid structures
where prolong the distribution grid is cost-prohibitive. Typical SAPS include one or more
methods of electricity generation, energy storage, and regulation; consequently almost
all aspect of SAPS is equivalent to off-grid local power systems; still both can be
considered microgrids.
As described by P. Balachandra from the Indian Institute of Science: “Overall, the use
case for energy storage in SAPS is built primarily around the ability of storage to
maximize renewable generation use and minimize peak load, with secondary benefits
including ensuring the overall stability of the system. Ultimately, the operational objective
of the power system and the technology composition will determine which type of ESS is
used in a local/remote system, and to what degree. The technology composition of each
system is unique, because it is a response to a set of preferences and requirements set
by each individual end user” [BAL09]5.
2.3.7 Grid-connected microgrids
Meanwhile SAPS focuses on longer time of EES operation, grid-connected microgrid will
gain from fast-reacting EES with fast charging cycle, the short time of EES operation is
suitable to serve higher loads and to bridge the time needed to start backup resources or
adjust PHEV mode of operation. Therefore another use model that has emerged
following automation and digitalization is grid-connected microgrids [DUN17]6. A brief
definition for microgrid is:
“A microgrid is a group of interconnected loads and distributed energy resources within
clearly defined electrical boundaries that act as a single controllable entity with respect
to the grid. A microgrid can operate remotely, or connect and disconnect from the grid to
enable it to operate in both grid-connected and island-mode.”7
As stated in the recently released report by the Task Force Report of Solar Power
Europe8: “There is a considerable overlap between large (and especially commercial and
industrial) self-consumption and the use of grid-connected microgrids, with the major
5
P. Balachandra at Indian Institute of Science (October 2009)
https://www.researchgate.net/publication/222312157_Grid-connected_versus_standalone_energy_systems_for_decentralized_power-A_review_of_literature
6
Sonia Dunlop, Policy Adviser - Digitalisation and Solar, Solar Power Europe
http://www.solarpowereurope.org/reports/digitalisation-solar/
7
Beyond the buzzwords: Making the specific case for community resilience Microgrids
https://www.navigant.com/-/media/www/site/events/2016/pdfs/djones_beyond-the-buzzwords.pdf?la=en
8
SolarPower Task force – Digitalization and Solar (October 2017)
http://www.solarpowereurope.org/fileadmin/user_upload/documents/Publications/170928_Digitalisation_Solar_S
olarPower_Europe.pdf
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difference being that grid-connected microgrids are also engineered to be able to
provide back-up and continue operating during a grid power outage. This often involves
the use of battery storage or gas or diesel generators.” On regional bases the grid
management is more harmonised and has greater similarities in RES production
potential as well as loads mgt. potential.
The same report concludes, as consequence of the deployment of grid-connected
microgrids in two SHAR-Q demo sites regions, that the two major business opportunities
for solar based grid-connected microgrids that would enable and support peer to peer
models for storage sharing, are industrial sites and municipalities. These clusters are
“geographically discrete areas”, hence allowing better manageability and coordination.
2.3.8 Virtual Power Plants
Several tendencies are determining the market for energy storage, but perhaps none is
more dramatic than the advent of the virtual power plant. Virtual Power Plants (VPPs)
will serve as precursors to a fully functional energy cloud [DEH16]9.
Energy companies launched the phrase "Virtual Power Plants" (VPPs) to describe
networks of energy resources in a way that more people could understand and be
involved. The objective is to provide energy companies with additional generation
capacity for final customers (including from their prosumers) without actually requiring
them to construct new generating capacity on their own [CLA17]10.
After putting a lot of resistance to residential solar power losing the opportunity of
developing behind-the-meter assets with their customers, Utilities now are recognizing
that energy storage is not a threat; it’s an opportunity.
Virtual Power Plants (VPP) – or Virtual Utilities (VU) – are the most outstanding
examples of IoT applied to energy: the Internet of Energy11. This vision of the future for
the energy market use existing grid networks and infrastructures to modify the way
electricity supply and demand services are integrated.
A virtual utility can aggregate the generation from various distributed systems and act as
the intermediary between and with energy markets. A virtual utility can also act as an
integrator of non-traditional services provided to customers by third parties, e.g.
distributed energy resources outside its traditional service territory. In this model, the
utility does not own assets but merely provides integration services on behalf of the
supplier, provider or performer.
And the growth of VPPs will enable the energy cloud where which stakeholders can
purchase or sell energy from multiple sources among themselves; it will also provide the
fundamentals to construct a shared energy economy by empowering energy
transactions to flow in two directions.
9
Anissa Dehamna, Alex Eller, William Tokash, Five Trends for Energy Storage in 2016 and Beyond (2016), White
Paper
https://www.navigantresearch.com/research/five-trends-for-energy-storage-in-2016-and-beyond
10
Heather Clancy - Get ready for virtual power plants (January 2017)
https://www.greenbiz.com/article/get-ready-virtual-power-plants
11
Virtual Power Plant Revenues to Reach $7.4 Billion by 2015
https://www.navigantresearch.com/newsroom/virtual-power-plant-revenues-to-reach-7-4-billion-by-2015
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A successful virtual utility will be highly efficient at energy sourcing, managing or
interfacing with local distribution networks, real-time balancing of demand and supply,
and providing intelligent tools for managing customer engagement. Sustainability and
increased reliability (back-up power) may be offered as additional products, beyond the
traditional reliable and affordable grid power. To develop the additional capabilities, the
virtual utility will need to build partnerships with developers, system integrators, energy
service/energy savings companies (ESCOs), software/technology vendors and online
energy marketplaces.
Some relevant examples regarding the impact of VPPs are:

The portal www.SolarniNovinky.cz (or SolarNews) is an internet source of
specialized data focused on publication of news and technology developments in
photovoltaics & solar energy in the Czech and Slovak Republics. The portal
offers updated information on the developments in those fields12.
 Ancillary service for TSO – primary regulation13.
As Heather Clancy in her article (January 2017): “In a time of greater reliance on
distributed energy resources, VPPs represent one strategy helping to manage the
increasing prevalence of two-way power flows. This technology relies on software and
the smart grid, working remotely and automatically to combine a diversity of independent
resources into a network via sophisticated planning, scheduling, and bidding of DERbased services.” [CLA17]14
2.4 Advantages of DER-EES integration
Small energy storage systems in a home or business – EES – will provide the advantage
of enable the balancing of the grid on a localized level; they will store energy when there
is surplus of energy provided by a DER or its price is cheap; and will to supply energy
locally or allow the grid to obtain energy when demand is high. Hundreds or thousands
of DER could be interconnected to create a network of assets supporting the grid and
providing a price signal.
On the utility side, solar or wind projects are energy projects that also provide attached
energy storage to the grid to reduce the volatility going to the grid, reducing the need for
spinning reserves, and easily manage the effects of the “duck curve” (a rise in demand
in the late afternoon when the sun goes down and people get home from work). Once
long duration energy storage technology improves enough to store energy for night-time,
the requirements to change the way the energy market is managed will be fulfilled
[WAR16].
Variable forms of power generation present challenges to local electrical grids and.
ESSs represent the best option to levelling the variability of the output from renewable
sources by rapidly control variability. Also the excess of renewable energy production
12
Publication of news and technology developments in photovoltaics & solar energy in the Czech and Slovak
Republics.
http://www.solarninovinky.cz/?zpravy/2016032303/baterie-pomahaji-stabilizovat-frekvenci-v-siti
13
Ancillary service for TSO – primary regulation in Czech and Slovak Republics
http://oenergetice.cz/elektrina/akumulace-energie/steag-nainstaluje-90-mw-baterii-pro-regulaci-frekvence-v-siti/
14
Heather Clancy - Get ready for virtual power plants (January 2017)
https://www.greenbiz.com/article/get-ready-virtual-power-plants
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presents a key opportunity for long-duration, utility-scale ESSs to enable greater
utilization of these resources by aligning energy supply with demand.
Finally, there is another major driver needed to improve the resilience of the electrical
grid: recent natural disasters have highlighted the disadvantages of centralized grid vs.
decentralized architecture – the recovery time has led communities to opt for more local
generation and use of microgrids to ensure that they still have energy during a disaster.
2.4.1 Advantages of RES-EV synergy
A particular case for the efficient exploitation of the energy produced by RES concerns
the synergy among RES and EVs. More specifically, the elasticity offered by the EV
charging can be employed alongside the production of distributed energy sources to
provide flexibility services to the DSO. Moreover, the EV charging elasticity can
effectively be considered and managed alongside the variable RES production in order
to increase both the EV and RES hosting capacity, without additional grid investments.
Additionally, the flexible EV charging demand can be exploited in order to avoid
imbalance penalty costs incurred by the derivations between the forecast and the real
energy profile of RES. More specifically, imbalance services can be offered to Balancing
Responsible Party (BRP) who is in charge of guaranteeing the tracking of the scheduled
energy profile. The interest of BRPs in such services can be assured if compensating
the aforementioned imbalances through the offered services is cheaper than the
imbalance penalty.
Moreover, the management of the charging of an EV fleet can provide market oriented
services that will facilitate the optimal scheduling of the operation of RES, while also
taking into account the market prices. More specifically, such services will schedule the
RES and EV operation in respect to the market prices, while aiming to minimize the
energy cost. Within this concept, portfolio optimization services might be of particular
interest for facility managers or energy communities.
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3.Guidelines for Integration Models
Shared economics is deeply disrupting the traditional system of resource allocation, e.g.
alternative and collaborative funding is an unstoppable trend around the world; is
changing the relationships between people and business.
From the perspective of interaction and integration of DER and EES, the following
possible relationships between actors have been taken into account:



P2P (peer to peer): Peer-to-peer (P2P) computing or networking is a distributed
application architecture that partitions tasks or workloads between peers. Peers
are equally privileged, equipotent participants in the application. By extension the
term is also used referring to “Person to Person”15.
P2B (peer to business): provides individuals with the opportunity exchange of
products, services or information with established businesses16.
B2B (business-to-business): B2B (business-to-business) is the exchange of
products, services or information between businesses, rather than between
businesses and consumers17.
It should be noted that the most important difference between these relationship models
is the distance that separates the entities, hence the channels of communication and
transmission to be used: DER requires the conduction of the generated energy to a
consumption or storage point, currently only possible using a power cable. In those
cases that the power cable is a (shared) propriety of the entities, additional actors will
not be involved; but if the distances that separate the generation and the
storage/consumption points are large, the introduction of a “distribution” stakeholder is
needed.
The following chapter proposes integration models based on the processes that enable
the integration for DER and ESS. Based on a high-level description of the generation,
storage and consumption processes, all use cases described in the previous chapter will
be aligned, enabling the description of a common and unique integration model that
applies to any DER & ESS deployment.
As said previously, the integration of DER and ESS requires the existence of a power
cable to transport energy from one point to another, in the processes described below
the cable is a common requirement.
3.1 Processes
A process is a collection of related, structured activities or tasks that produce a specific
service or product (serve a particular goal) for a particular customer or customers. There
are three main types of business processes:
15
P2P Definition
https://techterms.com/definition/p2p
16
P2B and P2P, Crowdfunding Vs crowdlending, what are the differences? (April 2017)
https://www.ecrowdinvest.com/blog/en/p2b-and-p2p/
17
B2B (business-to-business)
http://searchcio.techtarget.com/definition/B2B
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


Management processes that govern the operation of a system. Typical
management processes include corporate governance and strategic
management.
Operational processes that constitute the core business and create the primary
value stream. Typical operational processes are purchasing, manufacturing,
marketing, and sales.
Supporting processes, that support the core processes. Examples include
accounting, recruitment, and technical support.
Figure 7. Components of a Process
Processes can be designed and developed using the following components (see Figure
7):
1.
Process Input and Output: Are the major matters connected to the design of a
process; they give sense to a process by transforming certain Input to a
specified Output. In other words, Input is something the process needs to make
it work, while Output is specific result to be produced by this process.
An Input is specified, qualified, acquired and delivered into the process, is taken
into operation, according to the process’s workflow and gets gradually
converted into Output during progression of the process’s workflow. Input is
usually limited with certain categories:
 Raw materials (e.g. substances or objects);
 Resources (e.g. energy, water, etc.);
 Labour (e.g. personnel efforts);
 Information.
An Output can have any possible factors, form and features; it could be
anything creating any value, or everything that can be used for some purpose.
2.
Legal Framework is a structure of regulations, assumptions, principles and
(personal/business) rules that constrains a process.
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3.
Resources refer to all resources that a process will use to obtain the expected
output. Resources could include financial resources, inventory, human skills,
production resources, infrastructure or information technology (IT).
Processes can be decomposed using many additional detail levels to organize and
group related, structured activities or tasks to be performed by the process; the common
detail levels are: sub-processes, activities, sub-activities, tasks and sub-tasks. Its use
depends on the level of detail needed.
For intends of designing the figures that represent the processes, some notations
principles have been defined (see Figure 8):
Figure 8. Legend used for Process Figures





Start/End point of the process (or sequence of processes) are represented by
circles.
Arrows represent the flow from one process to another, consequently the output
from a process can be the input for another one.
Processes are represented as rectangles, inputs to the process are arrows
connected to the process at its left side and outputs are arrows starting at the
right side of the process.
Rhomb represents decision points (yes/no) that decide next steps.
Legal Framework are indicated at the top of the process; and resources at its
bottom.
A process will only start if the input is available; therefore a process can have more
than one input and more that 1 output (e.g. generation process has an energy and a
Besides the energy oriented issues defined in previous sections from 3.1 to 3.6 the
following technical challenges have to be addressed by the SHAR-Q Platform:
Based on the previously described design rules Figure 9 describes the sequence of
execution for the DER, ESS and (energy) Consumption processes (at high-level).
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Figure 9. Processes related to Energy flow (from generation to consumption)
The energy flow from generation to consumption is composed by 3 processes:
1.
2.
3.
Generation Process: The process starts with the availability of a renewable
source (wind, water, etc.) that will be used, using specific equipment
constrained by the legal framework, to generate energy. Its output is energy.
Storage Process: The process starts with the availability of energy needed to
stock energy on the storage system. Again, it uses specific equipment and
requires deployment space, both constrained by the legal framework to be
capable to provide stored energy as output.
Consumption Process: The process starts with the availability of the energy
needed to provide power to any device, appliance, equipment, etc. installed at a
specific location. Its output is that all energy requirements are being covered, in
next level of process decomposition (see Figure 12) it can also send an “energy
requirement” to Generation and Storage processes.
Following sections will provide additional details for each of these processes.
3.2 High-Level DER Process
As described by Figure 10, the decomposition of the Generation process is represented
by two sub-processes:
1.
Generate Energy: As its parent process, it starts with the availability of a
renewable source (wind, water, etc.) that will be used, using specific equipment
constrained by the legal framework, to generate energy. Its output is generated
energy.
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2.
Provide Energy Forecasting: shows additional activities related to the
generation, the capability to provide energy forecasting for a time-period.
Consequently, this sub-process can also start with an “energy request” sent
by the Storage or Consumption processes.
“Forecasting is the process of making predictions of the future based on past and
present data and most commonly by analysis of trends, consequently Provide Energy
Forecasting has a new requirement “forecasting data”, e.g. weather forecasting for solar
generation”18.
Forecasting is commonly perceived as a prediction for a distant future (hours, days, etc.)
but must also include immediate future represented by the time slot required by the
process to provide as answer to the requirement.
Based on the availability of energy forecasting, the process performs activities to provide
predictions per time period – expected generation under current climatic situation - and
identify which of following processes – energy usage – will take precedence over the
energy generated, available and forecasted – understood as energy available for a timeperiod in the future. Furthermore, the sub-process enables management of different
business models and use cases based on business rules. For example, a prosumer can
decide to sell energy to the Local Distribution Grid when the energy market conditions
provide him a price advantage.
Consequently, and depending on the rules that apply to the process - as part of the
business rules - the priority for following processes is defined as:
1.
2.
3.
Consumption process, which represents all appliances, equipment, etc.
currently requiring energy.
Storage process, which represent the storage solution available and their
storage capacity.
Local Distribution Grid, which represents the process to be performed to sell
and inject the – excess – of energy to the distribution grid.
Note! The Local Distribution Grid process can include activities like energy transactions
with a trader, DR process from DSOs, etc.; not described in the scope of this document.
Note! Many countries don’t allow inject surplus energy to the grid.
18
Forecasting
https://en.wikipedia.org/wiki/Forecasting
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Figure 10. Sub-Processes for DER
The decision point, named “Decision to distribute energy”, of the processes is related to
the priority defined for providing energy to Consumption, Storage or Local Distribution
Grid. The priority will be controlled by the “business rules” and automated by the control
software, based on the existing/forecasting of energy provided by previous sub-process.
At this decomposition level the resources required by the processes includes forecasting
information and the HW and SW resources has been separated. Both sub-processes
perform automatically based on their inputs; consequently no human interaction is
required.
The Control Software – in a basic installation represented by the inverter - starts to take
more relevance for the process diagram, it is responsible for managing the data flows
associated to the energy flows as well as taking the decisions regarding how to distribute
the available energy.
3.3 High-Level ESS Process
The Storage Process can use energy sources that come from local assets – located
behind the meter as rechargeable storage system; from other community member (P2P)
or from the Local Distribution Grid – represented by an energy trader and a DSO. In all
cases the transmission on energy from the source to the storage system requires an
energy cable that interconnects them and could involve a payment (fee) for the
transmission services.
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As shown by Figure 11, the ESS process is discomposed in two sub-processes:
1.
2.
Recharge the Storage System has the objective of recharging available
storage systems when storage capacity is available (input). The recharge rules defined by the final user, the manufacturer and/or the local legal framework constrains the sub-process, rules that includes the selection of the energy
source, with preference to renewable sources. Its main output is the load
capacity based on energy available per storage solution.
Note that this process is very similar to the recharge EV’s batteries; the only
difference is additional requirement for EV´s batteries to recharge in specific
charging spots.
Provide Stored Energy with the objective to cover energy requirements from
the Consumption, Recharge EV’s batteries and Local Distribution Grid
processes.
As mentioned in previous point, Recharge Storage System and Recharge EV´s
batteries only differ between them because of the need for additional equipment
(e.g. charging point).
Figure 11. Sub-Processes for EES
The Legal Framework has been detailed as “recharging” and “discharging” rules, both
including those legal aspects that are specific to them.
The Recharge Storage System sub-process can use at least 3 different sources of
energy to recharge the storage system: renewable sources represented by the energy
generated, stored energy represented by other storage systems capable to provide
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energy (e.g. an EV battery can be charged by a storage system); and the Local
Distribution Grid represented by the energy bought and paid by the energy bill.
Based on the energy stored, the Provide Stored Energy process can perform its
activities once started by an Energy request generated by the Consumption, Recharge
or Local Distribution Grid process, consequently, the sub-process has two inputs: the
energy request and the stored energy.
Even weather conditions have an impact on the capacity to store energy, it is not
relevant at this level of detail, but the type of resources has been separated. As for DER
processes, for EES both sub-processes perform automatically based on their inputs with
no human interaction.
The Control Software starts to take more relevance in the diagram, it is responsible for
managing the data flows associated to the energy flows as well as take the decisions
regarding how to distribute the available energy based on the energy requests received
from Consumption processes and the discharging rules.
3.4 High-Level Consumption Process
The Consumption Process can use energy sources that come from local asset, from
other community member (P2P) or from the Local Distribution Grid – represented by an
energy trader and a DSO. In all cases the transmission on energy from the source to the
storage system requires an energy cable that interconnects them and could involve a
payment (fee) for the transmission services.
This process covers the energy requirements from home/office appliances and from
other equipment or devices, either requiring or not interactions with a user, e.g.
television, home computer, smartphones or air conditioner, that can be programmed to
execute its actions/functions. For example, a light bulb can be turned on with a switch or
programmed to turn on at a specific time with a timer; and the process includes both.
As shown by Figure 12, the process is decomposed also in two sub-processes:
1.
Schedule use for energy equipment: the sub-process starts with an energy
forecast based on consumption patterns provided by the equipment, appliances
and any other device available locally. The forecast can be immediate, e.g.
turning on a television, or can be programmed to turn on at a certain hour, e.g.
washing machine.
Its outputs are two: a schedule plan provided to the next sub-process and an
energy request sent to other processes in those cases available energy is not
sufficient to cover the schedule plan.
The energy request will be sent to:
 Provide stored energy process (see Figure 11. Sub-Processes for EES)
if a storage system is available (locally or a community member);
 Generate energy process (see Figure 10. Sub-Processes for DER) if
generation system is available; or
 Local Distribution Grid (DSO + energy trader) using an energy contract.
This sub-process is controlled by the usage rules defined by the user and could
be automated using control software.
2.
Provide Energy to equipment: this sub-process is responsible for providing
energy to any device that uses energy to perform tasks and results, e.g. light
bulb provides light or a PC provides data processing capabilities.
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Its inputs are the schedule plan for usage of energy and a source of energy
controlled by the Energy Provider rules – rules for an energy contract could be
different to those defined by the user for the energy stored.
Taking into account that the Schedule use for energy equipment process controls
any new energy requirement – e.g. switch the heater on (now or in a time frame);
this sub-process finishes with all energy requirements covered.
Figure 12. Sub-process of Energy Consumption
3.5 Integration behind the Meter
“A Behind the Meter (BTM) system is a renewable energy generating facility (in this
case, a solar PV system) that produces power intended for on-site use in a home, office
building, or other commercial facility. The location of the solar PV system (DER) and
energy storage system (ESS) – like batteries of an EV – is literally “Behind the Meter”,
on the owner’s property, not on the side of the electric grid/utility19”
19
PV 101: What does “Behind The Meter” mean?
http://www.ppcsolar.com/behind-meter-mean/
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Integration behind the meter will be successful:
a. Locally:
 When the owner has a DER and ESS systems available and connected by a
power cable. This case includes ESS systems like the provided by his/her
EV.
 When a community of owners have DER and ESS systems available and
connected by power cables. Here community must be understood as
neighbourhoods, buildings or urbanizations with nearby locations.
b. Remotely:
 When DER and ESS systems are separated by large distances and require
the intervention of an energy distribution manager, usually a DSO, and its
distribution grid.
Following sub-sections describe SHAR-Q use cases and how they manage locally DERESS integration. For more details regarding regional integration see 3.6 Integration at
the Regional Level.
3.5.1 Integration of EVs (Greece)
Use cases that investigate the integration of the EVs and DER at the local level, concern
the provision of market oriented services. Those services will enable the optimal
scheduling of the DER and EES operation according to electricity market prices. More
specifically, portfolio optimization services will schedule the operation of the DER and
EVs in respect to the market prices trying to minimize the energy cost. Moreover,
additional services will exploit the flexible EV charging demand in order to minimize the
penalty cost of the deviations between the forecast DER production and the real one.
Provision of such services requires the installation of PVs and charging stations for EVs
in the examined local network. Particularly concerning the Greek pilot site Distributed
RES units are installed in the Meltemi campus, comprising small PV panels and small
residential wind turbine. No controllability will be considered for those DER units, while
monitoring data should be provided considering their production.
3.5.2 Integration in Portugal
It is expected that local ecosystem community will benefit from the distributed generation
and storage solutions that would be facilitated by SHAR-Q. The DSO, which manages a
substation placed 7Km from the site will also be able to benefit from the added value
services provided by the SHAR-Q platform. The implementation of SHAR-Q platform at
local level, such as municipal scale with regional roll out prospects is expected to also
make it possible to create average daily profiles for the Solar Lab facility. The Solar Lab
would also model self-consumption generation and services provision model.
The flow of data relating to energy generation, consumption and Electrical Energy
Storage between all actors when aligned to the added-value services is expected to
make the price of electricity to be optimised since consumers and prosumers will be
empowered to manage the electricity flow although the DSO will remain as the grid
operator.
Some mistrust in the new system is expected, so time for adaptation and investment on
education and transformation of the current infrastructures and systems will be required.
The scalability of the system is important and will be assessed within the pilot. Regional
rollout is considered.
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3.5.3 Integration in Austria
The Use Case of Austria will be a set of prosumers within the SHAR-Q network. The
energy production will be mainly based on PV-facilities; the storage will be mainly based
on battery storage systems. For the set of prosumers, four diverse types have been
defined (see Figure 13).
Figure 13. Integration at the local level Austria
Type A: Participants of “Type A” dispose of a PV-plant plus inverter. The generated
energy is partly consumed in the house; surplus is fed into grid at supply level voltage.
“Type A” participants represent the major number of cases. For self-production PVplants are the most common applications for buildings in Austria and in the Use Case
are of Austria, the number of installed PV-plants is rapidly growing.
Type B: Participants of “Type B” dispose of a battery storage unit and inverter. Energy is
purchased either from the grid or from another prosumer, stored and used for selfconsumption or gets resold. There is currently no case existing in the Use Case area of
Austria, but within SHAR-Q incentives for such services and such participants shall be
established.
Type C: Participants of “Type C” dispose of a PV-facility, inverter plus battery storage
unit. The generated energy is partly consumed in the house; surplus is either stored or
fed into grid. Stored energy can be used for optimized self-consumption or can be sold
to other participants. Participants of “Type C” represent a small number of cases.
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Type D: Participants of “Type D” are buildings like apartment buildings, public building,
etc. with different load profiles. “Type D” participants have implemented PV-plants,
inverters, and storage units. Peak loads are covered from surplus of other participants.
Apart from that, same functions as in type C.
3.6 Integration at the Regional Level
As far as the integration of RES and EVs at the regional level is concerned, the provision
of grid oriented services will be investigated. More specifically, those services will exploit
the flexibility offered by distributed energy resources and by EV charging, in order to
increase the RES and EV hosting capacity of distribution networks. Thus, investments
on grid reinforcement to support the additional charging demand of EVs or the extra
RES production can be deferred or avoided. Moreover, the DSO can request the
provision of flexibility services, like the control of active/reactive power of the DER
devices, in order to support voltage profile or avoid network congestion.
Concerning the installed PVs, power electronic interfaces of grid connected PVs could
allow active and reactive controllability, unlocking various business opportunities.
However, there is no regulated mechanism in Europe to facilitate the curtailment of the
excess PV production during low consumption periods. The PV production is considered
as negative load, and the energy produced by PV panels is injected to the electricity grid
without any curtailment capability. Among the EU countries only in Germany the system
operator can communicate curtailment set-points to PVs to ensure the reliable and
secure operation of the network.
In order to increase the RES penetration subsidy policies can be deployed. For instance,
pricing policies can be deployed until achieving a critical PV deployment level. Moreover,
net-metering is a significant incentive towards promoting the installation of PVs. More
specifically, a prosumer is provided the ability to virtually store his or her solar generation
surplus at a particular period of time, and exploit it in another high consumption period.
The virtually stored solar generation surplus is available for a maximum period of time
(usually one year) before being suspended. Therefore, prosumers are encouraged to
invest on PVs with an installed capacity that best fits their energy needs.
At the regional level SHAR-Q processes need to establish a service comprising
information about the regional power fed into the grid as a base for weather/generation
analytics: Bounding boxes for the definition of the serviced region and are here a
criterion: SHAR-Q end-users (private end users). These bounding boxes commonly are
rectangles that cover as much of an area as possible comprising significant points of
interests (POI): e.g. substations, commercial power plants, or private end users. This
POI can be represented in more than one bounding box which makes exact matching a
challenge.
The evolution of the previously referred community solar models (SHAR-Q D 2.4) will
also contribute to the development of a common energy strategy approach although
some scepticism in the new decentralised user managed and active prosumer enabled
system is expected. Some time for adaptation will be required but in the end this
evolution will prove to be an excellent reference to the region for new energy strategy.
This evolution will also fuel the shifts in the mobility sector towards decarbonisation and
larger penetration of self-consumption, RES generation legislation which will allow for a
decrease in the dependence from fossil fuels and better managed energy systems.
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3.6.1 Regional integration in Austria
The regional level for the Use Case of Austria is more or less the grid part and related
processes. First of all, a general overview of what a classical grid means, shall be given:
Classical grid:

dendritic organisation

unidirectional energy flow

stringent hierarchic organization
Figure 14 shows in which network level
which energy power unit types are
connected, as well as which consumer
types.
Figure 14. Classical electricity grid
As it is visible from Figure 14, the set of prosumers will be located in the low voltage
level of the grid of the local DSO. The next figure shows the net plan of the Strem use
case:
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Source: Energy Güssing
Figure 15. Grid of the local DSO – part Strem
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For the integration at regional level, it can be seen from Figure 16 that there are two
different types. The regional type I operate at a same strand on grid level. But as the
electricity grid operates in real on different strands, as well as different grid levels, «type
II» was defined as a process, operating on different strands at same grid level, bridged
by different grid levels.
Figure 16. Integration at the regional level Austria
To realize such a system different technical challenges, but also possibilities for DSOs at
regional level are present:
1. Enlarging the grid level strands or meshes in order to enable power exchange on
the same voltage level (more or less costly).
2. Restricting the power producing facilities´ output by the DSO to balance the
strands or meshes (least costly and simple but ineffective for the whole system –
loss of capacities).
3. Regulating transformers are needed to displace the surplus produced to the
higher voltage level (displaces also the problem to the next level – technically
feasible, economically questionable, legally maybe a hardship – because maybe
TSO needs to be involved).
Additionally also challenges for the P2P software programmers (and/or aggregators) will
appear:
1. Direct P2P trade of power at reasonable costs are only making sense within the
same strand or mesh.
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2. P2P trade across two or more non-connected strands or meshes is not possible
because no measurable flow is occurring (remember that the energy grid is
organized completely different and thus, not comparable to the internet).
3. P2P trade across different grid-voltage levels affects also the superordinate
levels of the whole system, which need to be taken into account.
4. The current legal framework regarding power economy is very restrictive
although varying from country to country. Thus, the P2P software has to
incorporate not only technical, but also regulatory boundaries.
There are also different organizational challenges to be solved when peer-to-peer
solutions shall be enabled. Those are mainly represented by legal issues, which have to
be solved:
 Active participants in the system (PV and/or grid bound storage owners) need to
have a license as electricity traders.
 Which fees have to be paid by the small scale electricity producers/prosumers for
grid access as well as for varying grid use? How is taxation executed when
blockchain are used?
 The matter of purchase commitment is currently bound to one supplier. Smart
contracts are currently not regulated in a legal framework. Thus, multiple
purchase commitments with varying amounts of energy are currently not
possible.
 Traders and suppliers, according to regulatory framework, have to be members
of a balance group. Who has to establish the required balance group and who
has to pay for the balancing energy in periods of strong volatility of production?
 How are different titles of ownership and participation treated? E.g. if one or
some participants are living in an apartment building of a housing association and
not all tenants are members?
So the theory of integration at local and regional level in Austria is accompanied by a lot
of challenges that have to be solved within the implementation process.
3.7 Challenges for DER and ESS interoperability
Requirements for interoperability between DER and ESS – and Consumption –
processes can be separated in two main aspects to be taken into account:


Energy requirements related to the equipment and infrastructure needed to
move energy between the generation and storage systems, and from both to
the devices, appliances, etc. that will consume available energy. Technical
requirements also include the interoperability with the distribution grid.
Technical requirements related to the software code or applications running
on computers needed to interoperate and control the equipment installed to
generate, store and use energy.
3.7.1 Energy Infrastructure Integration Issues
Distributed Energy Resources (DERs) such as energy storage systems (ESS) when
deployed at a large scale are capable of significantly influencing local energy systems.
DER can effectively support the electric grid with advanced control features to increase
hosting capacity by providing voltage support in local distribution grids, provide
supplementary energy services, and used for wide-area balancing.
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While the goal of the DER and ESS integration is common between the countries, there
are many differences in terminology and default values, situation that lead DER system
vendors to create versions of software compliant with regional requirements.
Consequently, the IEEE 1547 series of standards has defined the way stakeholders are
working together to enable growing amounts of DER/ESS can be interconnected with
the distribution grid. And the IEEE 2030 series of standards is supporting better
implementation of communications and information technologies that provide
interoperability solutions for enhanced integration of DER/ESS with the grid.
The evolving legal framework in Europe and the United States is driving PV inverters,
Energy Stability Systems, and other distributed energy resources (DERs/ESSs) to
provide advanced functions to support voltage and frequency in the local and regional
distribution grid.
Such functions will support technical solutions to the following requirements:





Stability of the distribution grid to avoid circumstances that could cause short
circuit impedances affecting the quality of the energy delivered.
The interoperability with the different types of stakeholders (the energy users,
consumers, prosumers, etc.) provides a better flexibility of the energy use.
Interoperability of the process resulting in forecasting to provide automated
system operation.
Clustering RES-DER stakeholders with storage capacity within local/regional
distribution grids ensure less interruption of service and increase stability at
the lowest network level.
Added-value creation provided to neighbourhood and grid operator based on
service integration for deployed DER/RES and connected to the distribution
grid.
3.7.2 Addressing the SHAR-Q integration barriers
Challenges are expected from the technical point of view since most devices coupled to
DER and ESS infrastructures (inverters, smart meters, etc.) have their own specific
communication protocols and APIs which, in some cases, may be blocked by the
manufacturers. Devices with well documented and open interfaces and APIs may be
easy to directly support in the (h)EMS but in other cases translating devices may be
required in order to allow their properties to be accessed. In some cases the
communication interfaces may be accessible and easy to integrate from the technical
point of view but blocked in a legal perspective (e.g. digitally reading of DSO's smart
meters is not allowed in several countries such as Portugal). In these cases, placement
of similar devices next to currently existing ones might be necessary.
3.7.2.1 Technical Integration Issues
Besides the energy oriented issues defined in previous sections the following technical
challenges must be taken in account:

Open standards and technology: The widely used set of data exchange
protocols supported by smart energy component must be implemented strictly
within those devices otherwise the data exchange will probably not work. In
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





SHAR-Q ecosystem we can work only with open standards and technology in
SHAR-Q interoperability gateway;
Legacy and non-connected energy components: legacy or non-connected
device management systems and appliances can bring more obstacles with
connectivity to SHAR-Q network. Therefore will be managed mainly via EMS. It is
easier to bring interoperability with energy infrastructure connecting one device
(EMS) using standard protocols at northbound interface instead of risking
proprietary based device management connected to EMS at southbound
interface;
Keep user behaviour data outside SHAR-Q open energy service platform:
store only meta-data necessary to exchange data related to connected smart
energy resources and smart grid assets. None user data must be stored in
SHAR-Q open energy service platform;
Exchange of the energy transaction within the coalition of prosumers: it is
necessary to collect information regarding energy produced and consumed by
each prosumer to enable optimization of the energy consumption and
reconciliation of the energy transactions. Moreover this information is also
needed for the energy consumption and production billing;
Exclusive access to smart energy components: to ensure that no
contradictive actions on Smart Energy Components. Exclusivity must be defined
on the level of the energy service provider providing the added-value services or
on the level of the connected smart energy facility;
Transparency and Accountability for exchanged information and set-points
within the peer-to-peer network: while all the connected energy infrastructures
do not have one owner, trust needs to be put on exchanged data. Peer needs to
be able verify origin of data received and be ensured that they were not altered
during transmission; Exchange of data in SHAR-Q should be secure in terms of
data integrity, confidentiality and availability. This approach is fully described in
D3.2 Security Framework;
Integration of the energy infrastructure into (h)EMS solution: The overall
challenge is to deploy (h)EMS solutions to ensure its reusability across the
facilities with same technologies and without change or intrusion of existing
energy infrastructure (change of the user interface of the EMS, etc.).
3.7.2.2 Non-technical Integration Issues
 User preferences: although there will exist added-value service which would
utilize proper set of smart energy components, a single user preference (comfort)
will define a business requirement desired from added-value service. User
preferences define final benefit of SHAR-Q added-value service. Usage of smart
energy appliances through SHAR-Q should be in line with users’ preferences.
That fact can influence one important SHAR-Q open energy service platform KPI
– free disposable power managed by the platform.
 Added-value service end-user centricity: added-value services are critical for
(h)EMS exploitation focusing on demand response, renewable energy
aggregators and energy distributions. Hence, End-user (households, building
owners, etc.) experience of the added-value services needs focus only on his
needs suppressing all the technical issues related to business process (can be
provided for the DSO, ESCOs, Service Providers, etc.).
Besides all the technical things, it is fundamental that all stakeholders understand the
mutual benefits of the DER/ESS/(h)EMS ecosystem and act accordingly by sharing the
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data flows of their equipment and allowing their control by dedicated value-added
services specifically designed in the scope of the SHAR-Q project.
3.8 Integrated DER and ESS use cases
For the distribution of energy between the DER and ESS a power line is needed,
consequently only 2 Use cases apply:
1. P2P/B2B/B2P using their own power line to share energy (local): the
stakeholders have a power line that enables bidirectional sharing of energy, e.g.
farms that share inversion of DER and ESS to share energy, an energy farm
deployed to serve a community/town (see Figure 17).
2. P2P/B2B/B2P using DSO’s power lines to share energy (local/regional): the
stakeholders require external power-lines provided by the DSO and an ESCO
(aggregator/trader) to access DSO’s services (see Figure 18).
Figure 17. P2P/B2B/B2P using their
power line to share energy (Local)
Figure 18. P2P/B2B/B2P using DSO’s
power lines to share energy
(Local/regional)
3.9 Alignment with SHAR-Q Platform
Energy flow processes modelled in previous chapters are accompanied by information
flow across the SHAR-Q Platform. In this chapter we develop generic process and subprocesses describing the information flow. Processes describing information flow across
the SHAR-Q Platform, which don’t influence the flow of electrical energy, are covered in
D2.6 – SHAR-Q Functional design document and D2.7 – Architecture of SHAR-Q
technology components, for example user and appliance registration, service
registration, search of A-V services and devices etc. Information flow which influences
the flow of energy is among energy infrastructure (EI), Added Value Services and
SHAR-Q components.
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3.9.1 SHAR-Q integration points
The critical points of integration, from ICT perspective the unhostile multiprotocol
environment, are the targeted areas of SHAR-Q project. SHAR-Q is going to overcome
these points of possible connectivity obstacles with SHAR-Q Open Gateway APIs based
on semantic interfaces, designed in D3.1.
Energy
Infrastructure 1
Legend
Process/Task
Energy flow
EMS Data flow
Device mgmt
A
B C
SHAR-Q Data flow
SHAR-Q SW component
The critical point of Interoperability toward SHAR-Q network
Cloud
Charge
controller
Inverter
Battery pack + BMS
AC Breaker
Box with EMS
SHAR-Q
GWAdapter+API
Energy
Infrast
ructure
Grid
Figure 19. Example of “legacy” energy infrastructure
Figure 19 shows an example of legacy infrastructure always autonomously drive smart
energy devices (PV, battery pack) and attached to SHAR-Q interoperable network via
SHAR-Q Open Gateway API stored in EMS or via EMS – Gateway Adapter integration.
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Legend
Energy
Infrastructure 2
Process/Task
Energy flow
EMS Data flow
Device mgmt
A
B C
SHAR-Q Data flow
SHAR-Q SW component
The critical point of Interoperability toward SHAR-Q network
3rdpartyEMSPortal
SHAR-Q
Open GW API
Cloud
HAN
gateway
AC Breaker
Box
SHAR-Q
GW Adapter+API
Energy
Infrast
ructure
Grid
Figure 20. Example of “connected” energy infrastructure
Figure 20 shows an energy infrastructure with autonomously driven smart energy
connected appliances (wash machine, cooling system etc.) that can be attached to
SHAR-Q interoperable network via SHAR-Q Gateway Adapter with Open Gateway API
or through third party cloud EMS using SHAR-Q Open Gateway API. The algorithm
which manages smart appliances to fulfil user needs and comfort can be either realized
inside HAN or on cloud. The critical point of integration showed on the picture express
the usual place where SHAR-Q ecosystem logic meets managed energy infrastructure
operators’ current energy efficiency and comfort setup.
Both figures covers all possible situations that may happened in real life and points on
fact that whenever the energy infrastructure is managed by “extraneous” energy
management algorithm, it will always be an energy infrastructure operators’ decision to
put the algorithm operation aside or to let SHAR-Q step into the algorithm and change it
according Added-value services business target.
3.9.2 Business target information processing
Following two figures depict two different approach of spreading the added-value
service business target to registered Energy Infrastructures.
Using the notation described for Data Flow Diagram of this document (see 3.1) provides
an overview of the processes supported by the SHAR-Q platform (see Figure 21).
Information exchange influencing power flow is taking place between Energy
Infrastructure (supply/demand source) and SHAR-Q Added Value Service only. Energy
infrastructure is provided with events and component’s properties from connected Smart
energy components. Added-value services provide commands to energy infrastructure
based on the result of the data processing. SHAR-Q Open energy service platform
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(Web-based collaboration manager) doesn’t step into information exchange in time of
event handling and commanding Infrastructure Owners’ devices and appliances. This is
a centralized approach. Business logic is executed as added-value service, which
handles communication with peers as described; see the following diagram where the
generic information flow process is graphically expressed.
Figure 21. Generic information flow process, centralized approach
The opposite of a centralised approach is decentralized approach which allows the peerto-peer communication between peers, handled by the gossip algorithm.
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Figure 22. Generic information flow process using gossip algorithm, decentralized
approach
Figure 22 graphically inscribes how the added-value services will push business targets
as gossip parameters to SHAR-Q gateway adapters at all Energy Infrastructures
registered in proper added-value service. The business logic is then partially executed
by gateway adapters themselves.
Information exchange influencing power flow is taking place between Energy
Infrastructure (supply/demand source) and SHAR-Q Added-value Service only. The
request of the added value services concerning the power flow towards the energy
infrastructures is realized by the negotiation among the energy infrastructures. Energy
infrastructure events and component’s properties from connected Smart energy
components are handled by gossip algorithm running on SHAR-Q gateway adapter.
Added-value services provides business target and receives results of proper actions.
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3.9.3 Alignment of information flow with SHAR-Q logical components
Figure 23. Mapping components on generic information flow process, centralized
approach
Figure 23 maps energy infrastructures’ end components, EMS, Smart Energy
Component management SW, generally units capable of communication, able of getting
information to and commands from SHAR-Q via SHAR-Q gateway adapter. Such units
lie at the end of the SHAR-Q Open energy service platform flow. SHAR-Q is capable to
manage either all Smart Energy Components through one unit like Energy Management
System or communicate with a single device like ESS via its Battery Management
System or generally Battery Management SW. At the other end of communication flow
lies a SW based Added-value Service, part of SHAR-Q, properly registered in the same
way as Smart Energy in SHAR-Q Open energy service platform (Web-based
collaboration manager). This is the way of smart energy components to be mapped using
centralized approach.
Figure 24 shows the diagram with information flow process that happens among the
same end units of the communication chain as described in previous paragraph. The
difference here is due to gossip negotiations that supports decentralized approach of
spreading information, ensuring the business target of Added-value service will be
fulfilled without direct information exchange of each Energy Infrastructure with the
specific Added-value Service Site.
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Figure 24. Mapping components on generic information flow process, decentralised approach
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3.9.4 Logically possible interactions among Energy Infrastructures and Services
Figure 25. Logically possible information interactions using Gossip algorithm for
communication among Smart Energy Facilities
Figure 25 contains the logical or hypothetical information exchange path. This example is
related to weather or RES production prediction. Added-value service 1 (AV1) provides
weather prediction; AV2 uses weather prediction to generate RES production prediction plan.
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The real information flow is the AV2 steps down to Smart Energy Facilities Layer and
becomes “the user” on the same level as Energy Infrastructure, requesting service from AV1.
Meanwhile from Logical information flow point of view – AV2 requests information from AV1.
Figure 26 illustrates information exchange between Energy Infrastructure and Added-value
service is supported by SHAR-Q Adapter and SHAR-Q Open Gateway API via SHAR-Q
interoperability network. Thus SHAR-Q Cloud components do not directly influence the flow
of the energy in the Energy Infrastructure. Energy flow is solely controlled by components of
Energy Infrastructure and local processing of information exchange form the Added-value
service through the SHAR-Q network (see Figure 26 and Figure 27).
Figure 26. SHAR-Q platform component decomposition, information process flow and
platform alignment, centralized approach
While Figure 26 illustrates the centralized approach, Figure 27 graphically expresses
composition with Gossip Negotiation Data, following the same principle of data exchange
independence on SHAR-Q cloud components.
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Figure 27. SHAR-Q platform component decomposition, information process flow and
platform alignment, decentralized approach
Figure 28 stands out the fact that SHAR-Q platform interaction with any smart energy
component by always processes and stores data related to the electrical power flow between
components and provides the commands necessary to operate and manage those
components, e.g. firmware updates. Therefore either type of added value service, grid or
market oriented, it will always influence power flow.
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Figure 28. SHAR-Q Added Value Service influences Energy flows in the grid
Figure 28 shows the relations of SHAR-Q information flows (data and commands) and how
the SHAR-Q logical SW and HW components interact with the grid technology provide
solutions to the following technical challenges:




Added-value service end-user centricity: added-value services are critical for
SHAR-Q Platform exploitation focusing on demand response, renewable energy
aggregators and energy distributions. Hence, End-user (households, building owners,
etc.) experience of the added-value services needs focus only on his needs
suppressing all the technical issues related to business process (can be provided for
the DSO, ESCOs, Service Providers, etc.);
Exchanging of the energy transaction within the coalition of prosumers: it is
necessary to collect information energy produced and consumed by each prosumer
on behalf of the added-value service to enable optimization of the energy
consumption and reconciliation of the energy transactions. Moreover this information
is critical for the energy consumption and production billing;
Exclusivity of the access to smart energy components by added-value
services: to ensure that no contradictive actions on Smart Energy Components will
be performed (charging and discharging commands in very short intervals by two
different added-value services) by any Added-value service or a set of Added-value
services an exclusivity of the access need to be ensured. Exclusivity need to be
defined on the level of the Service provider providing the added-value services or on
the level of the connected smart energy facility;
Accountability of the exchanged information and set-points within the peer-topeer network: while the connected infrastructures do not have one owner, trust
needs to be put on exchanged data. Peer needs to be able to verify origin of data
received and be ensured that they were not altered during transmission;
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
Integration of the energy infrastructure into SHAR-Q Platform: Smart energy
facilities are connected to SHAR-Q platform through SHAR-Q Adapters using locally
provided interfaces and supported protocols. The overall challenge is to implement
SHAR-Q Adapter in the way they are reusable across the facilities with same
technologies and without change or intrusion of existing energy infrastructure (change
of the user interface of the EMS, etc.).
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4. Conclusions
The road to transforming electricity networks over the next decade is becoming more explicit
and more detailed, grid stability based on renewable and distributed generation, lower cost
and storage solutions, micro-grids, electric and fuel cells vehicle for public and private
transportation, and higher presence of behind-the-meter devices.
The energy value-chain is evolving with new business models, and new roles for
stakeholders are under development leading, in the near future, to an energy value chain
that will require more interconnectivity and interoperability to form an integrated ecosystem of
unique IoT nodes that are highly interrelated without losing its individual characteristics and
objectives.
High penetration of distributed energy resources in urban areas (microgrids, nanogrids) will
require strong distribution system operators to reduce the need for transmission support and
the opportunity to manage all interfaces between local energy systems and traditional
distribution grids.
In the same way, because most of the renewable energy sources are variable; Electric
Energy Storage systems (EES or ESS) will be used to mitigate the mentioned variability,
crucial to enable an effective integration of renewable energy into the local generation of
energy supply.
There are two different aspects to be considered when providing guidelines for the
interoperability of distributed energy resources (DER) and energy storage systems (ESS);
both related to the distribution of energy and the data related this distribution from the
generation place, through the storage systems to the final consumer, more precisely their
energy-consuming devices. These aspects are:
Energy aspect
This aspect is the most relevant of both since the availability of energy starts with its
generation and its transportation and distribution.
From its beginning, this aspect has been evolving and improving until achieving a very
relevant efficiency in the world today. It has allowed the development of business models
and large investments to meet the population's growing energy needs.
To achieve this, highly specialised equipment and infrastructures have been developed,
standards and protocols have been defined and implemented, and there are available
transmission and distribution networks in almost any part of the world.
As a consequence of climate change and supported by technological developments,
humanity now has more and more efficient equipment for generation using renewable
sources and energy surplus storage systems, both capable of being connected to the
distribution network as additional sources and that ensure the stability, quality and continuity
of the electric service.
The development and improvement of specialized equipment (e.g. PV panels, inverters,
lithium batteries) has solved the challenges of these energy sources with automated
management and control systems included in such equipment, and as the only condition to
interoperate - transmit energy from one equipment to the other up to the grid - the need for
electrical cables that connect them.
These types of equipment have opened the door for installation and use by both energy
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behind-the-meter - but in distributed environments, e.g. generating farms, neighbourhoods,
buildings. And opened the door for Energy Management Systems (EMS) needed to manage
and control not only the energy sources – variable output of renewable sources, but more
important is to provide the fundamentals for new business models can be developed for
installations that depend on self-consumption of the electricity generated locally (micro- or
nanogrids).
Interoperability of DER, ESS and EMSs creates new challenges to be solved by the second
aspect:
Data Aspect
This aspect refers to obtaining, processing and consolidating data provided by generation,
storage or consumption equipment as well as by sensors and meters installed to manage
such equipment. Data that in turn is the basis for creating information and knowledge
regarding consumption profiles, current and future availability of energy, etc., as well as the
development of new value-added services for both a common energy market and a shared
energy economy.
The first step, obtaining data, is, therefore, the most important not only because of the need
for communication channels with the devices but also because of the need to understand the
data in an environment characterised by multiple standards and protocols. Furthermore,
controlling the devices is also necessary, e.g. software updates, or commands with
operations that must be sent to and performed by devices. Consequently, how to manage
the communication with these devices is a fundamental step for any EMS that will provide
the services required by the end user. In other words, the interoperability for the data aspect
between DER, ESS and the local distribution grid must be solved by the EMS. EMS is also
an important element in case of superiority – it manages behind-the-meter energy territory
and no value-added service can enter this territory directly. E.g. If an EMS runs a selfconsumption algorithm of a particular place, no value-added service shall be allowed to go
straight to a storage device of the mentioned territory and command it directly, outside the
EMS working algorithm.
A detailed analysis of the processes described in Chapter 3 of this document allows
exposing the following guides for the interoperability, final aim of this document:




Receiving or delivering energy from/to the local distribution network is constrained
to the conditions specified as standards and protocols by the network operator,
usually an energy service company. This company will also decide how to receive
and send the data related to the exchange of energy; consequently, it is
necessary to have an API that manages the exchange of information bidirectionally.
The ability to exchange energy (by HW) and data (by SW) with the operator
enables management of additional services such as grid balancing and Demand
Response programs based on service level agreements (SLA) or contracts.
Generation and/or storage capabilities are impacted by external – e.g. weather –
and internal – maintenance cycles for equipment – factors. Both must be
controlled by specific services provided by the EMS as a fundamental part of the
temporal definition of users’ profiles. Users are understood as any actor or
stakeholder involved in the energy-value-chain.
Due their operational complexity and to make the most of smart energy
components, they must be managed by an energy management system. The
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communication - and interoperability - with such devices is the sine qua non
condition that turns dumb elements into smart. Some examples are:
o ESSs are battery cells with battery management system.
o RES requires a smart inverter to balance the energy flow.
o RES in self-consumption scenario with ESS must be managed towards
business target,
o Building appliances are managed by EMS towards comfort and economic
benefits.
Users’ profiles are fundamental both to describe the availability of energy in a distribution
network and the network's ability to recover from a failure, e.g. outtake.


Levelized Cost of Storage (LCS): the worldwide cost of most battery storage
technologies is rapidly declining with variations depending on the type of
application and battery technology. However, their economic viability depends on
local market structure and incentives, among other factors – Legal framework.
EV´s batteries are understood as the category of ESS that provides energy to an
electrical motor but requires additional equipment to be recharged. As with usual
ESS’, this equipment will provide signals (data) to the EMS regarding availability
or requirements of energy to be processed by a software application. For this
class of batteries, other factors must be taken into account such as vehicle use
profile that includes factors such as availability time slot, physical location, types
of charging points available at its location, etc.
Once the above requirements have been met, these batteries can be used as mobile
sources of energy to balance and support specific requirements of the distribution network.
SHAR-Q as the platform responsible for managing the data flows, and the interactions of
available SW and HW components solves the main aspects required from an EMS:





End-user added-value service solves demand response, renewable energy
aggregators and energy distributions requirements.
Energy transaction within prosumers provides services to manage user profiles –
consumption and generation energy consumption and production billing;
Smart energy components management performed (charging and discharging
commands in very short intervals by two different added-value services) by
specific added-value service or a set of them.
Accountability and set-points within the peer-to-peer provide trust for exchanged
data.
Integration of the energy infrastructure implemented with adapters using locally
provided interfaces and supported protocols, reusable across the facilities with
same technologies and without change or intrusion of existing energy
infrastructure (change of the user interface of the EMS, etc.).
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5.References
[BAL09]
[CLA17]
[DEH16]
[DUN17]
[ELL17]
[FAR10]
[MAR15]
[MOR14]
[WAR16]
P. Balachandra, Grid-connected versus stand-alone energy systems for decentralized
power—A review of literature (2009), Article
https://www.researchgate.net/publication/222312157_Grid-connected_versus_standalone_energy_systems_for_decentralized_power-A_review_of_literature
Heather Clancy, GreenBiz 101: Get ready for virtual power plants (2017), Article
https://www.greenbiz.com/article/get-ready-virtual-power-plants
Anissa Dehamna, Alex Eller, William Tokash, Five Trends for Energy Storage in 2016
and Beyond (2016), White Paper
https://www.navigantresearch.com/research/five-trends-for-energy-storage-in-2016-andbeyond
Sonia Dunlop, Policy Adviser - Digitalisation and Solar, SolarPower Europe
http://www.solarpowereurope.org/reports/digitalisation-solar/
Alex Eller, Dexter Gauntlett, Energy Storage Trends and Opportunities in Emerging
Markets (2017). COMMISSIONED BY IFC AND ESMAP
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H. Farhangi, The path of the smart grid (2010), IEEE Power and Energy Magazine, vol.
8, no. 1, pp. 18-28, Jan./Feb. 2010
L. Martini et al., ELECTRA IRP approach to voltage and frequency control for future
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Jacob Morgan, A Simple Explanation Of 'The Internet Of Things' (2014), Forbes
https://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-thingsthat-anyone-can-understand/#121f505b1d09
Andrew Ward, Energy Editor, UK’s National Grid charges up battery storage plants
(2016), Financial Times
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