基于改进灰狼优化算法的有源配电网重构方法

Reconstruction Method of Active Distribution Network Based on Improved Grey Wolf Optimization Algorithm

为了提高有源配电网系统运行的经济性和稳定性,提出了一种基于改进灰狼算法的有源配电网重构方法。以配电网系统网损最小和电压偏移最小为目标函数建立有源配电网重构模型,并将多目标转化为单目标进行求解。采用Tent混沌映射、收敛系数指数调整和自适应位移等策略对灰狼优化算法进行改进,使IGWO算法的寻优能力得到显著提升。利用改进IEEE33节点系统进行仿真测试,并将IGWO算法的重构效果与GWO算法和PSO算法进行对比,结果表明,采用IGWO算法重构后的最低网损和最小电压偏移分别为54.89kW和0.00772,两项指标均优于GWO算法和PSO算法,验证了所提有源配电网重构方法的实用性和优越性。

In order to improve the economy and stability of the operation of active distribution network systems,an active distribution network reconstruction method based on the improved grey wolf optimization(IGWO)algorithm based is proposed.The active distribution network reconstruction model is established with the objective function of minimizing network loss and voltage offset in the distribution network system,and the multiple objectives is transformed into single objectives for solution.The grey wolf optimization algorithm is improved by employing strategies such as Tent chaotic mappeing,convergence coefficient index adjustment,and adaptive displacement,which significantly improve the optimization ability of the IGWO algorithm.Simulation testing is conducted using an improved IEEE 33 node system,and the reconstruction effect of the IGWO algorithm is compared with the GWO algorithm and PSO algorithm.The results show that the minimum network loss and minimum voltage offset after reconstruction using the IGWO algorithm are 54.89 kW and 0.00772,respectively.Both indicators are better than those of the GWO algorithm and PSO algorithm,which verifies the practicality and superiority of the proposed active distribution network reconstruction method.