Integrated modular energy systems and local flexibility trading for neural energy islands
The de-centralization of electricity generation requires equally de-centralized and affordable solutions to integrate more RES, increase the security of supply and decarbonize the EU energy future. The combination and unique integration of de-centralized storage with technologies for local energy system optimization, including demand response, electric vehicle charging optimization and synergies with other energy vectors at the 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, since 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. Optimization 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 CHP Plants to facilitate maximum RES integration, avoidance of curtailment and satisfaction of balancing/ ancillary grid needs. MERLON will enable the realization of novel business models, allowing local energy communities to introduce themselves in local flexibility markets, while paving the way for the realization of novel Microgrid-as-a-Service models, assigning to local DSOs the role of “Aggregator of Aggregators” 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 toward grid stability and alleviation of network constraints.