Smart district energy optimization of flexible energy units for the integration of local energy storage

Several changes are involving electrical power systems, especially distribution networks. For this reason, the actors in charge of managing and operating reliably these grids are facing many technical issues regarding demand and supply balancing, Renewable Energy Sources and Electric Vehicles integration, peak load shaving, etc. In this context, many energy actions have been implemented for providing services to the power system managers by means of prosumers' demand and/or supply flexibility. This study reports the development of a centralized energy management solution for smart grids equipped with local storage devices, RES, consumers and other energy facilities in a district context. The district Energy Management System relies upon a multi-objective optimization implemented by means of a genetic algorithm, the Non-dominated Sorting Genetic Algorithm II. This optimization, based on both technical and economic criteria, aims at following a power profile sent by DSO exploiting the flexibility provided by every energy unit. The simulation models of the main components of the system are developed in order to simulate the district operations and are integrated in the Energy Management System. Moreover, the communication framework deployed between the different components of the system is reported and described.