Dynamic and adaptive reconfiguration of electrical distribution system including renewables applying stochastic model predictive control

In this study, the structure of an electrical distribution network, which includes several electrical distribution feeders, is adaptively and dynamically reconfigured to minimise the daily operation cost of system that is under control of a local distribution company. Herein, for the first time, stochastic model predictive control (MPC) concept is applied in the problem to have dynamic and adaptability futures in the optimisation problem and to deal with the uncertainty and variability issues of renewable energy resources. The daily operation cost of distribution system comprises hourly energy loss cost of electrical feeders and switching cost of initially open and close switches installed on each feeder. The numerical study shows the existence of notable potential in reconfiguration of distribution system for energy loss and operation cost reduction. In addition, it is demonstrated that applying MPC in the optimal reconfiguration of distribution system results in better consequences in the presence of variable power of renewables. Moreover, it is proven that application of MPC in the problem increases the robustness and resiliency of optimisation procedure with respect to the prediction errors due to dynamic and adaptability characteristics of MPC.