计及新能源接入低压配电网分布式储能双层协同优化OA

Aiming at the problem of voltage over-limit and network loss surge caused by the penetration rate of new energy exceeding 15%in low-voltage distribution network of Zhejiang Province,a double-layer collaborative optimization method of distributed energy storage is proposed to provide an integrated solution of"Planning-Operation".Based on the measured data of Quzhou area,a stochastic hybrid model considering the characteristics of wind and solar time series is constructed,which integrates improved particle swarm optimization algorithm and second-order cone programming technology.The dynamic inertia weight and nonlinear decreasing strategy are used in the planning layer to balance the global search and local optimization ability of the algorithm.In the operation layer,a mixed integer second-order cone model is established,and the Big-M method is used to deal with the logical constraints of energy storage charging and discharging.The double-layer target coupling is realized by the back propagation mechanism.The verification results based on IEEE 33-bus system show that this method can increase the new energy consumption rate by 12.7%,reduce the network loss by 14.6%,and achieve the optimal economic benefits of energy storage configuration,which can provide an effective way for the collaborative optimization of high-proportion new energy distribution network.