Capacity configuration optimization for stand-alone microgrid considering the uncertainties of wind and solar resource

Abstract

This paper focuses on capacity configuration optimization for the stand-alone Wind-PV-Diesel-Battery microgrid. A stochastic optimization model based on conditional value at risk (CVaR) is proposed to consider the operation risk of microgrid caused by the uncertainties of wind and solar resource. First, a large number of scenarios of wind and solar resources are generated using Latin Hypercube Sampling (LHS) method, and the scenarios reduction is subtracted by the use of K-medoids clustering algorithm. Second, based on the reliability of microgrid power supply, considering the economy and high utilization rate of renewable energy, a stochastic optimization model with minimum annual comprehensive cost is established combined with CVaR. Finally, binary particle swarm optimization algorithm is used to solve the above integer optimization model. The results of deterministic and stochastic optimization models are evaluated by risk index of power loss and load loss respectively. Simulation results show that the proposed model can well accommodate to many possible operation scenarios in the future.