基于偏好知识的多目标优化算法求解计及电源侧的配电网故障恢复  

Multi-objective optimization algorithm based on decision preferences to solve distribution network service restoration considering power supply

作　　者：姚玉海 王增平 张首魁 郭昆亚[2] 金鹏[2] 齐郑 

机构地区：[1]新能源电力系统国家重点实验室(华北电力大学),北京102206 [2]沈阳供电公司,辽宁沈阳110811

出　　处：《电力系统保护与控制》2016年第4期1-8,共8页Power System Protection and Control

基　　金：国家电网公司科技项目资助(合同号:沈阳供电公司信息化工作办公室KJ[2013]896)

摘　　要：针对传统故障恢复在处理电源侧问题上的不足,基于变电站主变在实际运行时要尽量满足N-1准则的要求,提出了变压器越限个数和变压器平均负载率两个目标函数。在求解故障恢复的算法上,针对基于传统占优机制的经典多目标智能算法在迭代过程中没有考虑决策者的偏好知识,从而导致算法收敛缓慢和无法得到最优解的问题,将g占优机制和TOPSIS方法引入多目标智能算法。g占优机制中的参考点可以根据故障恢复问题的特殊要求进行灵活设计,TOPSIS方法可将决策者的偏好知识融入算法的迭代过程中。这些措施可以有效地提高解的质量和算法的收敛性能。最后,通过算例验证了该算法的可行性和有效性。Traditional distribution network service restoration cannot completely satisfy the requirements of N-1 security verification of transformer in station, and the corresponding mathematical model is constructed. Without considering the preference of decision maker in the iterative process, the classic multi-objective evolutionary algorithm, based on Pareto dominance criteria and crowding distance sorting method, is of slow convergence speed. This paper proposes a multi-objective binary particle swarm optimization based on g dominance and technique for order preference by similarity to an ideal solution （TOPSIS） to solve distribution network service restoration. The reference point ofg dominance can design flexibly according to the requirements of service restoration, and TOPSIS makes the preference of decision maker into the iteration. These improved measures are of great significance on improving the quality of solution and enhancing convergence velocity. Finally, an example is illustrated to verify feasibility and validity of the proposed method.

关 键 词：配电网 故障恢复 g占优机制 TOPSIS方法 

分 类 号：TM732[电气工程—电力系统及自动化]