Start Date: Jan 1, 2019
End Date: Dec 31, 2021
Budget: € 7.551.059
Integrated Modular Energy Systems and Local Flexibility Trading for Neural Energy Islands
The decentralisation of electricity generation requires equally decentralised and affordable solutions to integrate more RES, increase the security of supply and decarbonise the EU energy future. The combination and unique integration of decentralised storage with technologies for local energy system optimisation, including demand response (DR), electric vehicle (EV) charging optimisation and synergies with other energy vectors at local level, can offer a cost-efficient pathway (in comparison to high-CAPEX grid upgrade investments) for local energy systems optimization in presence of high volumes of volatile and intermittent RES. Huge amounts of currently non-utilized flexibility can be unleashed to ensure optimal congestion management and effective tackling of local instabilities and imbalances. MERLON introduces an Integrated Modular Local Energy Management Framework for the Holistic Operational Optimization of Local Energy Systems in presence of high shares of volatile distributed RES.
Optimisation in MERLON applies to multiple levels spanning optimal coordination of local generation, with demand and storage flexibility as well as flexibility offered by EVs and buildings in order to facilitate maximum RES integration, avoidance of curtailment and satisfaction of balancing/ ancillary grid needs. MERLON will enable the realisation of novel business models, allowing local energy communities to participate in local flexibility markets, while paving the way for the realisation of novel Microgrid-as-a-Service models for the provision of added-value services to the overlay distribution grid. It equips local stakeholders (DSOs, energy cooperatives, prosumers) with innovative and highly effective tools for the establishment of robust business practices to exploit their microgrids and dynamic VPPs as balancing and ancillary assets towards grid stability and alleviation of network constraints.