基于混合蛙跳算法的分布式风电源规划

Distributed Wind Generator Planning Based on Shuffled Frog Leaping Algorithm

对分布式风电源(DWG)出力的随机性和负荷的不确定性进行概率建模。在此基础上,以年综合费用最小为目标,利用机会约束规划方法建立了配电网DWG选址定容规划模型。采用基于拉丁超立方采样蒙特卡洛模拟(LHS-MCS)法的概率潮流判断规划方案是否满足节点电压机会约束和支路电流机会约束。设计了混合蛙跳算法(SFLA)求解DWG规划模型的具体实现方法。33节点配电网的DWG规划结果验证了模型的合理性、LHS-MCS检验机会约束条件的有效性以及SFLA的高效性。

The randomness of distributed wind generator （DWG） and the uncertainty of the load are firstly modeled. Based on that, a chance constrained programming method is proposed in the selection of site location and capacity in the distribution system aiming to minimize the total annual cost. The probabilistic power flow based on the Latin hypercube sampling-based Monte Carlo simulation （LHS-MCS） is applied to verify whether the planning scheme satisfies the chance constraints on the node voltage operation range and the feeder current limit. A procedure of solving the planning model by shuffled frog leaping algorithm （SFLA） is designed. The example of a 33-bus distribution network validates the feasibility of the model, the effectiveness of LHS-MCS and the high efficiency of SFLA.