Periodic Reporting for period 3 - FEVER (Flexible Energy Production, Demand and Storage-based Virtual Power Plants for Electricity Markets and Resilient DSO Operation)
Reporting period: 2022-08-01 to 2024-01-31
FEVER’s scope is defined by three axes and for each we have a clear set of objectives:
Dimension 1: Flexibility measures and flexibility-based electricity grid services
1. Implement flexibility measures that address the local needs for flexibility at the distribution grid, leveraging various flexibility assets
2. Implement a comprehensive flexibility aggregation, management and trading solution that incorporates intelligence around the optimal flexibility orchestration and is capable to offer flexibility services in different markets
3. Implement electricity grid services such as congestion management and overvoltage avoidance based on flexibility management techniques such as EVs’ (dis)-charging control
Dimension 2: Enhanced monitoring and automated control of the distribution grid
4. Implement an innovative toolbox that empowers the DSOs with advanced monitoring and automated control functions
5. Implement an advanced technology that leverages batteries’ inverters towards providing ancillary services
Dimension 3: Market mechanisms supporting and incentivizing flexibility services
6. Implement a hierarchical and scalable operational mechanism for day-ahead and continuous trading of flexibility services
7. Implement a toolbox for peer-to-peer flexibility trading based on decentralized ledger technologies.
FEVER also encompasses a set of cross-dimensional objectives:
8. Demonstrate and validate in realistic settings the mechanisms implemented in the project
9. Gain evidence of the replicability and scalability of the implemented solutions
Dimension 1: Flexibility measures and flexibility-based electricity grid services
1. Implement flexibility measures that address the local needs for flexibility at the distribution grid, leveraging various flexibility assets
2. Implement a comprehensive flexibility aggregation, management and trading solution that incorporates intelligence around the optimal flexibility orchestration and is capable to offer flexibility services in different markets
3. Implement electricity grid services such as congestion management and overvoltage avoidance based on flexibility management techniques such as EVs’ (dis)-charging control
Dimension 2: Enhanced monitoring and automated control of the distribution grid
4. Implement an innovative toolbox that empowers the DSOs with advanced monitoring and automated control functions
5. Implement an advanced technology that leverages batteries’ inverters towards providing ancillary services
Dimension 3: Market mechanisms supporting and incentivizing flexibility services
6. Implement a hierarchical and scalable operational mechanism for day-ahead and continuous trading of flexibility services
7. Implement a toolbox for peer-to-peer flexibility trading based on decentralized ledger technologies.
FEVER also encompasses a set of cross-dimensional objectives:
8. Demonstrate and validate in realistic settings the mechanisms implemented in the project
9. Gain evidence of the replicability and scalability of the implemented solutions
The project has developed and demonstrated as set of solutions that foster the adoption of flexibility in the electricity market, addressing the needs of different stakeholders:
-Three different markets (day-ahead, intra-day, real-time) incorporating flexibility services for mitigating issues of the distribution grid were developed and validated with real-life pilot data. The results showcased that they can mitigate operational issues with satisfactory scalability and accuracy, efficiently addressing issues of the distribution network.
-A wide portfolio of Energy Management Systems (EMSs) has been developed and demonstrated, capable to support a diverse set of loads (domestic, industrial, EVs) and storage assets (stationary batteries) under different contexts (e.g. energy communities, microgrids) as well as the utilization of virtual energy reservoirs.
-A solution for Distribution System Operators (i.e. DSO Toolbox) has been implemented and demonstrated, enabling the forecasting of various grid issues (congestions, voltage violations), offering proactive management of the grid, by leveraging flexible assets, ultimately acting as an alternative to traditional grid interventions and leading to higher RES penetration.
-Two novel business cases were demonstrated, enabled by two Energy Communities (in Wunsiedel and Hassfurt): Local energy balancing of community using DLT technologies & digital coins (FlexCoin); Regional balancing (Flexibridge), enabling trade of flexibility and energy among Energy Communities.
FEVER consortium was a founding member of the FlexCommunity, a community of more than 250 members aiming to promote the adoption of flexibility solutions in the energy system.
During this period, the consortium has paved its exploitation pathway, analyzing 15 Key Exploitable Results, conducted its scalability and replicability analysis, participated in 41 events, co-organised the FlexCommunity 2023 Conference, organized the project’s final event and produced 15 scientific publications.
-Three different markets (day-ahead, intra-day, real-time) incorporating flexibility services for mitigating issues of the distribution grid were developed and validated with real-life pilot data. The results showcased that they can mitigate operational issues with satisfactory scalability and accuracy, efficiently addressing issues of the distribution network.
-A wide portfolio of Energy Management Systems (EMSs) has been developed and demonstrated, capable to support a diverse set of loads (domestic, industrial, EVs) and storage assets (stationary batteries) under different contexts (e.g. energy communities, microgrids) as well as the utilization of virtual energy reservoirs.
-A solution for Distribution System Operators (i.e. DSO Toolbox) has been implemented and demonstrated, enabling the forecasting of various grid issues (congestions, voltage violations), offering proactive management of the grid, by leveraging flexible assets, ultimately acting as an alternative to traditional grid interventions and leading to higher RES penetration.
-Two novel business cases were demonstrated, enabled by two Energy Communities (in Wunsiedel and Hassfurt): Local energy balancing of community using DLT technologies & digital coins (FlexCoin); Regional balancing (Flexibridge), enabling trade of flexibility and energy among Energy Communities.
FEVER consortium was a founding member of the FlexCommunity, a community of more than 250 members aiming to promote the adoption of flexibility solutions in the energy system.
During this period, the consortium has paved its exploitation pathway, analyzing 15 Key Exploitable Results, conducted its scalability and replicability analysis, participated in 41 events, co-organised the FlexCommunity 2023 Conference, organized the project’s final event and produced 15 scientific publications.
FEVER is a collaborative project that puts emphasis on implementing innovative solutions and services that leverage flexibility towards offering electricity grid services. Innovation in the project is being pursued in the following dimensions:
1. Optimized flexibility aggregation, management and trading
• Extraction and management of flexibilities from physical and virtual energy reservoirs. A wide range of user types and production processes and constraints are taken into account. The flexibility management algorithms have the ability to link several energy vectors.
• Multi-layered optimization of the flexible assets scheduling at the levels of each EMS territory and of the Flexibility Aggregator, implementing optimization features such as prioritized load activation and adaptation, dynamic backup load involvement in case of outages and simultaneous load adaptation and peak shaving operation.
• Optimization of the flexibility trading policy by matching flexibility offers and requests based on price optimization. An auction-based process selects the flexibility offers for activation, calculating the energy price and financial flows of the parties involved into the trading.
• Peer-to-peer flexibility trading on the basis of distributed ledger technologies and a set of innovative dAPPS (FlexTrading , FlexCoin, Community Management ) that support a total flexibility trading solution for Energy Communities.
2. Enablers of enhanced observability and controllability of the distribution grid
• Enhanced PV generation and load forecasting with emphasis on fine-grained spatiotemporal resolution. To achieve accurate short- and mid-term PV generation forecasting, machine learning models based on artificial neural networks was employed, whilst for load forecasting several methods were tested with random forest being considered as the state-of-the-art solution for the formulated problem.
• Enhanced distribution grid observability. For detecting abnormal variations from network variables (voltage and currents at the substations/grid nodes) multivariate statistical models are employed based on principal component analysis. For local observability, novel algorithms for accurate state estimation at the level of MV or LV feeder leveraging a variety of –often scarce- sensing data.
• Battery-based power quality monitoring and power quality enhancement services. Such services leverage power converters to enhance power quality through harmonics and unbalances forecasting and estimation of asset capacity reserve.
• Enhanced distribution grid control and automation including the identification of potential violations on the network operational constraints and proposition of mitigation actions based on grid reconfiguration and DERs’ flexibility.
3. Novel hierarchical and scalable mechanisms for day-ahead, close to real time and real-time markets for energy and ancillary services
• For the day-ahead horizon the proposed market mechanism includes flexibility as a tool and solves an optimization problem taking into account both the central market mechanisms and various technical constraints of the decentralized local distribution grid. In order to further enhance the secure operation of the distribution grid in case of unpredictable events, a continuous intraday trading mechanism is proposed, where the DSO and aggregators can trade grid energy and services to resolve emerging issues. Finally, for the real-time electricity balancing markets, FEVER proposes a real-time multi-layer iterative mechanism to provide ancillary services to the electricity balancing market.
The impact of the above solutions was measured and evaluated on the basis of piloting of 15 High Level Use Cases and their relevant Key Performance Indicators, utilizing 3 different real-life setups in Spain, Germany and Cyprus, as well as lab simulations.
1. Optimized flexibility aggregation, management and trading
• Extraction and management of flexibilities from physical and virtual energy reservoirs. A wide range of user types and production processes and constraints are taken into account. The flexibility management algorithms have the ability to link several energy vectors.
• Multi-layered optimization of the flexible assets scheduling at the levels of each EMS territory and of the Flexibility Aggregator, implementing optimization features such as prioritized load activation and adaptation, dynamic backup load involvement in case of outages and simultaneous load adaptation and peak shaving operation.
• Optimization of the flexibility trading policy by matching flexibility offers and requests based on price optimization. An auction-based process selects the flexibility offers for activation, calculating the energy price and financial flows of the parties involved into the trading.
• Peer-to-peer flexibility trading on the basis of distributed ledger technologies and a set of innovative dAPPS (FlexTrading , FlexCoin, Community Management ) that support a total flexibility trading solution for Energy Communities.
2. Enablers of enhanced observability and controllability of the distribution grid
• Enhanced PV generation and load forecasting with emphasis on fine-grained spatiotemporal resolution. To achieve accurate short- and mid-term PV generation forecasting, machine learning models based on artificial neural networks was employed, whilst for load forecasting several methods were tested with random forest being considered as the state-of-the-art solution for the formulated problem.
• Enhanced distribution grid observability. For detecting abnormal variations from network variables (voltage and currents at the substations/grid nodes) multivariate statistical models are employed based on principal component analysis. For local observability, novel algorithms for accurate state estimation at the level of MV or LV feeder leveraging a variety of –often scarce- sensing data.
• Battery-based power quality monitoring and power quality enhancement services. Such services leverage power converters to enhance power quality through harmonics and unbalances forecasting and estimation of asset capacity reserve.
• Enhanced distribution grid control and automation including the identification of potential violations on the network operational constraints and proposition of mitigation actions based on grid reconfiguration and DERs’ flexibility.
3. Novel hierarchical and scalable mechanisms for day-ahead, close to real time and real-time markets for energy and ancillary services
• For the day-ahead horizon the proposed market mechanism includes flexibility as a tool and solves an optimization problem taking into account both the central market mechanisms and various technical constraints of the decentralized local distribution grid. In order to further enhance the secure operation of the distribution grid in case of unpredictable events, a continuous intraday trading mechanism is proposed, where the DSO and aggregators can trade grid energy and services to resolve emerging issues. Finally, for the real-time electricity balancing markets, FEVER proposes a real-time multi-layer iterative mechanism to provide ancillary services to the electricity balancing market.
The impact of the above solutions was measured and evaluated on the basis of piloting of 15 High Level Use Cases and their relevant Key Performance Indicators, utilizing 3 different real-life setups in Spain, Germany and Cyprus, as well as lab simulations.