克隆遗传算法与模拟退火算法相结合的配电网络重构

Distribution network reconstruction based on the combination of CGA and SA

配电网重构可以提高配电网运行的安全性、经济性和供电质量,对于当前国内配电自动化系统建设和应用具有重要意义。将克隆遗传算法(CGA)与退火算法(SA)结合起来,把退火算法中的Metropolis抽样准则融入到克隆遗传算法中,形成克隆遗传退火算法(CGSA)。以网损最小为目标函数,以配电网电压降的限制、线路电流量的限制等为约束条件,在考虑配电网自身特点的基础上,以IEEE33节点为算例,利用克隆遗传退火算法求解。结果证明该优化算法具有较好的全局收敛性和收敛速度。

Distribution network reconstruction can improve security and quality of network operation as well as minimize the power loss, and it is of great importance for construction and application of distribution automation system at present in China.Clonal Genetic Simulated Annealing Algorithm（CGSA）,which combines CGA（Clonal Genetic Algorithm） and SA（Simulated Annealing Algorithm）,and puts the Metropolis sample rule of the SA into the CGA, is proposed for distribution network reconfiguration.An optimization model of distribution network reconfiguration is established,in which the minimum network loss is taken as objective function, the restrictions to the decline of voltage and current are taken as constraint conditions. Based on the features of distribution network, the CGSA is used in the IEEE 33 bus system for network reconstruction. Reconfiguration results show that the algorithm is efficient and practical, and has good global convergence and can accelerate the speed of convergence.