Stochastic, adaptive, and dynamic control of energy storage systems integrated with renewable energy sources for power loss minimization

In this study, the energy storage systems (ESS) integrated with renewable energy sources (RES), installed in a medium-voltage primary electrical distribution system, are controlled based on a proposed stochastic, adaptive, and dynamic approach to minimize the daily operation cost of system managed by the local distribution company (DISCO). A stochastic approach is applied in the operation problem to address the uncertainty of power of RESs. In addition, a model predictive control (MPC) technique is employed to deal with the variability of power of RESs. The daily operation cost of distribution system includes the hourly energy loss cost of electrical feeder, the hourly operation cost of ESSs, and the hourly switching cost of ESSs. The numerical study demonstrates a remarkable potential for reducing the operation cost of system by optimal control of ESSs and application of stochastic MPC. In addition, it is proven that applying MPC in the problem results in better outcomes. Moreover, it is shown that MPC increases the robustness of optimization procedure with respect to the prediction errors, due to dynamic and adaptability characteristics of MPC. (C) 2017 Elsevier Ltd. All rights reserved.