For distribution systems where wind sources are poor, low-wind-speed wind turbines (LWTG) plays an important role in improving the security, economy and reliability of the system. However, the stochastic volatility of LWTG output and loads poses a challenge to the technology of distribution network reconfiguration. Considering the uncertainty of LWTG output, photovoltaic output and changes of load in multiple continuous periods, a dynamic robust reconfiguration model is established. The optimization target is to minimize the three-phase current unbalance and network loss. The model solving process combines the Latin hypercube sampling-based Monte Carlo method, the Semi-invariant method and the compound differential evolution algorithm. The influence of LWTG on the reconfiguration results is explored based on the modified IEEE34-node simulation system, and the performance of the proposed dynamic robust reconfiguration method is then verified.
Distribution Network Reconfiguration Based on Differential Evolution Algorithm
