Decentralized Energy Scheduling of LV Microgrid Under Stochastic Environment

The integration of multiple sources and loads in the grid, necessitates the need for an efficient energy management system. The energy management system can optimally coordinate different energy sources and loads subjected to different uncertainties to achieve demand-supply balance. In this paper, optimal scheduling of local energy sources is done with the utilization of the summed-up capacity of plug-in electric vehicle technology to minimize the operating cost of the microgrid. Due to intermittent and variability of RES sources and randomness in load, uncertainty is handled by the stochastic process with scenario generation and reduction method. The efficacy of the proposed approach is investigated on the residential feeder of CIGRE LV microgrid benchmark model. To test the feasibility of study, technical and economic constraints are considered while implementing a mathematical optimization model. Four cases of microgrid operation are considered for testing, namely islanded mode, grid-connected with the trade of energy in import power mode only, export power mode only and lastly both import-export power mode. The mathematical model is prepared and solved by YALMIP integrated into the MATLAB environment, and CPLEX solver is used to reduce computational time.