A hybrid bacterial foraging-particle swarm optimization technique for solving optimal reactive power dispatch problem

P. L. Reddy, Yesuratnam Guduri
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引用次数: 1

Abstract

This paper presents a hybrid evolutionary computation algorithm termed as hybrid bacterial foraging-particle swarm optimization (HBFPSO) algorithm, to optimal reactive power dispatch (ORPD) problem. HBFPSO algorithm merges velocity and position updating strategy of particle swarm optimization (PSO) algorithm and reproduction and elimination dispersal of bacterial foraging algorithm (BFA). The ORPD is solved for minimization of two objective functions; system real power loss and voltage stability L-index. The objective is minimized by optimally choosing the control variables; generator excitations, tap positions of on-load tap changing transformers and switched var compensators while satisfying their constraints and also the constraints of dependent variabl es; voltages of all load buses and reactive power generation of all generators. The proposed approach has been evaluated on a standard IEEE 30 bus test system and 24 bus EHV southern region equivalent Indian power system. The results offered by the proposed algorithm are compared with those offered by other evolutionary computation algorithms reported in the recent state of the art literature and the superiority of the proposed algorithm is demonstrated.
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求解无功最优调度问题的混合细菌觅食-粒子群优化技术
针对无功优化调度问题,提出了一种混合进化计算算法——混合细菌觅食-粒子群优化算法(HBFPSO)。HBFPSO算法将粒子群优化算法(PSO)的速度和位置更新策略与细菌觅食算法(BFA)的繁殖和消除扩散相结合。求解了两个目标函数的最小化问题;系统实际功率损耗和电压稳定l指数。通过最优选择控制变量使目标最小化;发电机励磁、有载分接变换变压器分接位置和开关无功补偿器分接位置同时满足它们的约束和因变量的约束;所有负载母线的电压和所有发电机的无功功率。该方法已在标准IEEE 30总线测试系统和24总线超高压南部地区等效印度电力系统上进行了评估。将所提算法的计算结果与近年来文献报道的其他进化计算算法的计算结果进行了比较,证明了所提算法的优越性。
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