Optimal Bilevel Model for Stochastic Risk-Based Planning of Microgrids Under Uncertainty

Abstract

The sharp fluctuations of load consumption and renewable power generation make significant risks in microgrids (MG) planning problem. In order to handle the risk, this paper proposes an innovative risk-based bilevel model for optimal planning of MGs under uncertainty. Furthermore, two different risk neutral and risk averse strategies are defined for MGs operator to investigate the impact of risk strategies on the MG planning problem. The proposed problem has been formulated as stochastic bilevel model, where the optimal planning of distributed energy resource accomplishes in the upper level and optimum switch allocation problem for partitioning traditional distribution system into a number of MGs carries out in the lower level. The partitioning traditional distribution system into interconnected MGs is implemented considering economic, technical, reliability, and maximum supply security aspects. Cuckoo optimization algorithm and imperialist competitive algorithm are applied to minimize the objective functions of upper and lower levels, respectively. The simulation study is performed on the PG&E 69-bus distribution system and the consequent discussions demonstrate the adequacy and efficiency of the proposed methodology.