Hijjo, M.; Frey, G.: Stochastic Optimization Framework for Scheduling Isolated Microgrids. Proceedings of the 19th IEEE Mediterranean Electrotechnical Conference (MELECON2018), pp. X-X, Marrakesh, Morocco, May 2018. [ACCEPTED]
Microgrids have become extensively used as a promising resolution to mitigate the implications of power outages and lack of energy in different region of the world. Isolated Microgrids as one of the most applied topologies in the emergency power supplying systems, essentially incorporate battery energy storage system (BESS), acting as a stabilizing agent by balancing the unmet power for the system. Besides, they have the ability to minimize the cost of the system by using renewable energy sources (RES). This work proposes a stochastic optimization framework for coordinating the power flows in isolated microgrids incorporating diesel generators, solar array in addition to the BESS, based on the predicted RES generation and load demand. More precisely, a deterministic optimal schedule is firstly derived based on dynamic programming (DP) and the algorithm is then extended using the Genetic Algorithms (GA) to minimize the huge searching space and to find a reasonable schedule within a shorter time. The proposed stochastic method is expected to achieve a reasonable schedule within an appropriate time-budget in order to enable real-time operation of the microgrid. The simulation results show a significant reduction of the total operation cost when compared with the conventional priority based approach which does not employ the prediction.
Isolated Microgrids, Genetic Algorithms, Stochastic Optimization, Dynamic Programming.