大规模风电接入的电力系统优化调度新方法

A New Optimized Dispatch Method for Power Grid Connected With Large-Scale Wind Farms

针对风电功率的反调峰和不确定等特性,建立水电调峰效益模型,并结合风、火电运行价格模型,构建了考虑机组组合的新型多目标动态优化调度模型。同时,为应对多目标优化问题中粒子群算法陷入局部最优和效率问题,提出了基于优先排序和多子群协同进化的多目标粒子群算法(multi-objective particle swarm optimization algorithm withmulti-swarm co-evolution,MOPSO-MC)的优化调度新方法,即通过优先排序法确定机组最优组合状态,对负荷分配规划分为两层,并采用MOPSO-MC求解。将该方法应用于含大规模风电的甘肃电网优化调度问题,结果表明所提模型和算法为解决风电并网运行提供了一种对策。

In allusion to such features of wind power as counter peak-shaving,uncertainty and intermittence,a peak-shaving benefit model of hydropower is built,and combining with price models of thermal and wind generation operation a new type of dynamic multi-objective optimized dispatch model considering unit commitment is constructed.To cope with the trouble that in multi-objecitve optimization problem the particle swarm optimization（PSO） algorithm falls into local optimum and to improve its efficiency,a new optimized dispatch method based on priority ordering and multi-objective particle swarm optimization algorithm with multi-swarm co-evolution（MOPSO-MC） is proposed,namely the optimal unit commitment is determined by priority ordering and the load distribution is divided into two layers and then solved by MOPSO-MC.Applying the proposed method to optimized dispatch of Gansu power grid connected with large-scale wind farms,the results show that the proposed method and models can offer a kind of countermeasure for the operation of grid-connected wind farms.