基于GA-PSO算法计及风电时序特性的主动配电网双层规划

Bi-level Planning for Active Distribution Network Considering Wind Power Timing Characteristics Based on GA-PSO Algorithm

合理规划配电网是提高风电消纳能力的重要一环,但风电出力与负荷时序特性场景应用较多,会增加模型求解难度,对优化配置结果有不利影响。引入拉丁超立方抽样结合K-means聚类技术削减样本数量得到典型风电与负荷多场景模型以提高模型计算效率。考虑风电运营商与国网公司利益,建立计及风电时序特性的主动配电网双层规划模型,即上层以风电运营商收益最大为目标确定风电规划方案,下层以配电网络损耗最小优化系统运行状态。基于IEEE 33节点系统进行算例分析,验证规划模型的有效性。研究结果表明:采用GA-PSO联合优化算法规划后配电系统损耗成本为26.04万元,比单一GA算法和PSO算法规划分别降低了5.03%和0.77%,场景成本减少了4.0万元。因此,验证了所提规划模型的有效性。

Reasonable planning of the active distribution network is an important part to improve the wind energy accommodation capability,however,the overuse of the wind power output and load timing characteristics increase the difficulty of model solving and have adverse effects on the optimal results.The Latin hypercube sampling(LHS)combined with the K-means clustering was employed to reduce the number of samples,thus a typical wind power and load multi-scenario model with higher calculation efficiency can be obtained.Considering the interests of wind power operators and the State Grid Corporation,a bi-level planning model of active distribution network considering the wind power timing characteristics was established.The upper level determines the wind power planning scheme with the goal of maximizing benefit of wind power operators,and the lower level optimizes the system operation state with the minimum loss of distribution network.The effectiveness verification of the planning mode was conducted based on the IEEE 33-bus distribution system.The results show that the loss cost of the distribution system is 260400￥after planning based on the GA-PSO joint optimization algorithm,which is 5.03%and 0.77%lower than that of single GA algorithm and PSO algorithm respectively,and the scenario cost is reduced by 40000￥compared to that of the results calculated by GA algorithm and PSO algorithm.Therefore,the validity of the planning model proposed was verified.