Periodic Reporting for period 2 - Storage4Grid (Storage4Grid)
Periodo di rendicontazione: 2018-06-01 al 2020-02-29
Storage4Grid (S4G) started on Dec. 1st, 2016 and finished on Feb. 29th, 2020. The project aims at boosting the uptake of Energy Storage Systems (ESS) between the distribution grid level and the end-user level, by developing a novel, holistic methodology for modelling, planning, integrating, operating and evaluating distributed ESS (at end-user premises and at substations), Electrical Vehicles (EVs), innovative energy metering and energy routing technologies. The S4G holistic methodology comprises:
• A Decision Support Framework (DSF) for planning the deployment of distributed ESS
• Predictive control algorithms prioritizing and optimizing the use of storage capacity distributed at end-user premises, substation level and in EVs
• An innovative Unbundled Smart Meter (USM) and an Energy Router (ER) enabling the S4G storage control strategies in real-life settings.
S4G pursues a set of Technical Objectives (TO) linked with long-term Strategic Objectives (SO):
• TO1: pre-design the S4G interfaces, namely a set of interfaces and a joint Common Information Model (CIM) suitable for monitoring and control of heterogeneous storage systems
• TO2: develop a set of predictive control algorithms suitable to perform real-time optimization of distributed storage system in existing low and medium voltage grids
• TO3: establish an Unbundled Smart Meter (USM) extending existing AMI standards in open fashion to allow local “plug-in” integration of interfaces providing information about storage control, EV charging and local user interfaces to enable interaction with users
• TO4: establish a fully integrated Energy Router allowing an easier integration of DC home grid, renewables and EV’s in a Smart Grid ready approach
• TO5: develop a decision-support tool for analyzing, planning, forecasting and optimizing the use of distributed storage in the low and medium voltage grid
• TO6: To propose and apply an evaluation methodology that assesses the technical feasibility of the developed technologies & solutions and as well as evaluates the user acceptance while considering the multiple actors and stakeholders within a Smart Grid.
• SO1: engage with private and professional end users to secure acceptance of S4G solutions
• SO2: develop a business model framework involving relevant actors (individual prosumers, ESS technology providers, service providers, DSOs, ESCOs, etc.) supporting a number of business cases
• SO3: within the business ecosystem outlined in SO1, extend available insight on the potentials of storage technologies to help decision makers in defining investment strategies
• SO4: provide inputs to on-going standardization activities in the area of storage modelling, testing and control, so to foster an eco-system of vendors, service providers, private and professional storage users
• SO5: provide a set of cyber-security guidelines and policies for operating storage systems involving users data and preferences handling correctly privacy- and security-related aspects
The Storage4Grid project aimed at progressively achieving the objective’s previously enlisted, throughout its execution. At the beginning of the project, one or more quantitative indicators have been assigned to each of the project objectives, along with target values to be achieved by the end of the project. Activities within the project have been organized in three phases and, at the end of each phase, the indicators have been quantified and compared against the target values. By the end of the project all targets have been achieved and, in many cases over achieved.
• A Decision Support Framework (DSF) for planning the deployment of distributed ESS
• Predictive control algorithms prioritizing and optimizing the use of storage capacity distributed at end-user premises, substation level and in EVs
• An innovative Unbundled Smart Meter (USM) and an Energy Router (ER) enabling the S4G storage control strategies in real-life settings.
S4G pursues a set of Technical Objectives (TO) linked with long-term Strategic Objectives (SO):
• TO1: pre-design the S4G interfaces, namely a set of interfaces and a joint Common Information Model (CIM) suitable for monitoring and control of heterogeneous storage systems
• TO2: develop a set of predictive control algorithms suitable to perform real-time optimization of distributed storage system in existing low and medium voltage grids
• TO3: establish an Unbundled Smart Meter (USM) extending existing AMI standards in open fashion to allow local “plug-in” integration of interfaces providing information about storage control, EV charging and local user interfaces to enable interaction with users
• TO4: establish a fully integrated Energy Router allowing an easier integration of DC home grid, renewables and EV’s in a Smart Grid ready approach
• TO5: develop a decision-support tool for analyzing, planning, forecasting and optimizing the use of distributed storage in the low and medium voltage grid
• TO6: To propose and apply an evaluation methodology that assesses the technical feasibility of the developed technologies & solutions and as well as evaluates the user acceptance while considering the multiple actors and stakeholders within a Smart Grid.
• SO1: engage with private and professional end users to secure acceptance of S4G solutions
• SO2: develop a business model framework involving relevant actors (individual prosumers, ESS technology providers, service providers, DSOs, ESCOs, etc.) supporting a number of business cases
• SO3: within the business ecosystem outlined in SO1, extend available insight on the potentials of storage technologies to help decision makers in defining investment strategies
• SO4: provide inputs to on-going standardization activities in the area of storage modelling, testing and control, so to foster an eco-system of vendors, service providers, private and professional storage users
• SO5: provide a set of cyber-security guidelines and policies for operating storage systems involving users data and preferences handling correctly privacy- and security-related aspects
The Storage4Grid project aimed at progressively achieving the objective’s previously enlisted, throughout its execution. At the beginning of the project, one or more quantitative indicators have been assigned to each of the project objectives, along with target values to be achieved by the end of the project. Activities within the project have been organized in three phases and, at the end of each phase, the indicators have been quantified and compared against the target values. By the end of the project all targets have been achieved and, in many cases over achieved.
A) Initial Scenarios and Use Cases
3 scenarios were defined:
• The “Advanced Cooperative Storage Systems” scenario in Bucharest addresses lower-TRL solutions; namely, the energy router, the joint use of storage and DC buses, V2G services (Figure 1).
• The “Cooperative EV Charging” scenario is a real life test site in Bolzano addressing methodologies for planning, evaluating and controlling storage units communicating and cooperating with EVs charging systems both in a commercial case and in a residential case (Figure 2).
• The “Storage Coordination” scenario is a real life test site located in Denmark addressing the use of storage as a buffer for fluctuations. It features 5 residential house in Fur, with storage units paired with PV installations, a lab and a grid area in the municipality of Skive with a large number of RES (Figure 3).
B) System architecture
Based on the 3 scenarios above, use cases and requirements the project developed a System Reference Architecture using the Smart Grid Reference Architecture (SGAM) Framework.
C) Exploitable Assets
The main exploitable assets generated by the project were identified as follows (details can be found in Table 1 and Table 2):
• Data Sets
• Modular components necessary to implement the full set of DSF functionalities: Data Ware House (DSF-DWH), Real-Time simulator (DSF-RT), Electric Vehicle Analytics (DSF-EVA), Simulation Engine (DSF-SE), Economic Engine (DSF-EE)
• Single-phase and tri-phase Energy Router (ER)
• The Grid-side ESS control system (GESSCon)
• Professional Realtime Optimization Framework for Energy Storage Systems (PROFESS)
• Professional Graphical User Interfaces (GUI)
• Professional Realtime Optimization Framework for Electric Vehicles (PROFEV)
• Residential Graphical User Interfaces (GUI)
• Unbundled Smart Meter (USM)
Table 3 provides more details about their IPR level, TRL and type of exploitation of each exploitable asset.
Finally, Table 4 indicates the possible beneficiaries (potential customers / end-users) interested in each exploitable asset. They can be grouped in the following four categories:
1. DSO and energy sector companies;
2. Manufacturers;
3. End-users (private / commercial);
4. Others (data companies and researchers / students).
D) Business Models
An overview of the storage market, TRL-level, stakeholders and policy framework in general, followed by a description of each test site and the associated business models were provided. Every business model takes as input the S4G Use Cases and is addressed in terms of stakeholder analysis, SWOT analysis from DSO perspective, risk analysis.
E) Test sites
In each test site the various S4G components were integrated following the S4G architectural view and adapted to the real-life situation in the field. Evaluation on activities were carried in each test site covering practical, technical and economic aspects, so to demonstrate potential benefit for stakeholders in terms of cost efficiency and added-value information.
3 scenarios were defined:
• The “Advanced Cooperative Storage Systems” scenario in Bucharest addresses lower-TRL solutions; namely, the energy router, the joint use of storage and DC buses, V2G services (Figure 1).
• The “Cooperative EV Charging” scenario is a real life test site in Bolzano addressing methodologies for planning, evaluating and controlling storage units communicating and cooperating with EVs charging systems both in a commercial case and in a residential case (Figure 2).
• The “Storage Coordination” scenario is a real life test site located in Denmark addressing the use of storage as a buffer for fluctuations. It features 5 residential house in Fur, with storage units paired with PV installations, a lab and a grid area in the municipality of Skive with a large number of RES (Figure 3).
B) System architecture
Based on the 3 scenarios above, use cases and requirements the project developed a System Reference Architecture using the Smart Grid Reference Architecture (SGAM) Framework.
C) Exploitable Assets
The main exploitable assets generated by the project were identified as follows (details can be found in Table 1 and Table 2):
• Data Sets
• Modular components necessary to implement the full set of DSF functionalities: Data Ware House (DSF-DWH), Real-Time simulator (DSF-RT), Electric Vehicle Analytics (DSF-EVA), Simulation Engine (DSF-SE), Economic Engine (DSF-EE)
• Single-phase and tri-phase Energy Router (ER)
• The Grid-side ESS control system (GESSCon)
• Professional Realtime Optimization Framework for Energy Storage Systems (PROFESS)
• Professional Graphical User Interfaces (GUI)
• Professional Realtime Optimization Framework for Electric Vehicles (PROFEV)
• Residential Graphical User Interfaces (GUI)
• Unbundled Smart Meter (USM)
Table 3 provides more details about their IPR level, TRL and type of exploitation of each exploitable asset.
Finally, Table 4 indicates the possible beneficiaries (potential customers / end-users) interested in each exploitable asset. They can be grouped in the following four categories:
1. DSO and energy sector companies;
2. Manufacturers;
3. End-users (private / commercial);
4. Others (data companies and researchers / students).
D) Business Models
An overview of the storage market, TRL-level, stakeholders and policy framework in general, followed by a description of each test site and the associated business models were provided. Every business model takes as input the S4G Use Cases and is addressed in terms of stakeholder analysis, SWOT analysis from DSO perspective, risk analysis.
E) Test sites
In each test site the various S4G components were integrated following the S4G architectural view and adapted to the real-life situation in the field. Evaluation on activities were carried in each test site covering practical, technical and economic aspects, so to demonstrate potential benefit for stakeholders in terms of cost efficiency and added-value information.
The areas targeted by S4G in progressing beyond the state-of-the-art and results expected until the end of the project are summarized in Table 5. The results presented in the previous section well depict how S4G succeeded in achieving them. In fact, S4G adopts an iterative approach that, on one hand, ensures that the final S4G outcomes achieve the goals set out in the project plan still meeting real-life needs and, on the other hand, issues a first full version of the results at early stages and subsequently improves and extends it as the project progresses.
The 9 Expected impacts (EI-1, …, EI-9) identified in the Grant Agreement (Table 6 and Table 7) are still relevant and do not need to be updated.
The 9 Expected impacts (EI-1, …, EI-9) identified in the Grant Agreement (Table 6 and Table 7) are still relevant and do not need to be updated.