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A bacterial foraging PSO — DE algorithm for solving reserve constrained Dynamic Economic Dispatch problem

机译:求解储备受限动态经济调度问题的细菌觅食PSO-DE算法。

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This paper introduces a solution to Dynamic Economic Dispatch (DED) problem using a hybrid optimization methodology bacterial foraging and PSO-DE (BPSO-DE) by integrating Bacterial foraging optimization Algorithm (BFOA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). In the proposed method BFOA performs local search and global search for entire search space is accomplished through PSO-DE operators in this way they move to reach the global optimization. The BFOA also takes care of the constraints such as ramp-rate limits, valve-point loading effects, system load demand, prohibited operating zones, power losses and spinning reserve capacity. A ten unit test system is considered to show the effectiveness of the proposed method over other existing methods.
机译:本文通过结合细菌觅食优化算法(BFOA),粒子群优化(PSO)和差异进化(DE)的混合优化方法,针对细菌觅食和PSO-DE(BPSO-DE)提出了动态经济调度(DED)问题的解决方案。 )。在提出的方法中,BFOA进行局部搜索,并通过PSO-DE运算符以这种方式移动它们以达到全局优化,从而对整个搜索空间进行全局搜索。 BFOA还考虑了诸如斜坡率限制,阀点负载影响,系统负载需求,禁止的操作区域,功率损耗和旋转备用容量之类的约束。十单元测试系统被认为可以证明该方法相对于其他现有方法的有效性。

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