基于多种群蚁群算法的多目标动态无功优化

为在负荷变动条件下提高动态无功优化控制变量的调节效率和满足全天动作次数的限制,将全天电能损耗最小、有载调压变压器分接头动作次数和电容器投切次数分别最少作为目标函数,建立新的多目标动态无功优化模型.针对该模型提出改进的多种群蚁群算法,利用多种信息素交换方式,满足动态无功优化多目标、强时空耦合的特点,避免了蚁群算法陷入局部最优解.通过对 IEEE14、IEEE 30系统计算验证模型和算法的可行性和有效性.结果表明:该模型和算法能够降低系统能量损耗,提高电压质量

Multi-Objective Dynamic Reactive Power Optimization Based on Multi-Population Ant Colony Algorithm

To improve the regulation efficiency of control variables for reactive power optimization and to suit to the restriction of action time in a whole day,taking the maximum network loss in a day,minimum tap changing times of on-load tap changer and minimum times of switching on/off capacitor banks as objective functions,a new multi-objective dynamic reactive power optimization model is built.For the built model,an improved multi-population ant colony algorithm is proposed,and by use of various information exchanging modes the features of multi-objective and strong space-time coupling can be satisfied and it is avoided for ant colony algorithm to fall into locally optimal solution.The feasibility and effectiveness of the proposed algorithm are verified by simulation results of IEEE 14-bus system and IEEE 30-bus system.Simulation results also show that the network loss can be reduced by use of the proposed algorithm as well as the voltage quality can be improved.