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Particle Swarm Optimization based Optimal Power Flow for Units with Non-Smooth Fuel Cost Functions

机译:基于粒子群优化基于具有非平滑燃料成本功能的单位的最佳功率流量

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This paper presents a Particle Swarm Optimization (PSO) based algorithm for optimal flow with generating units having non-smooth fuel costs curves while satisfying the constraints such as generator capacity limits, power balance, line flow limits, bus voltages and transformer tap setting, The conventional loed flow and incorporation of the proposed method using PSO has been examined and tested for standard IEEE 30 bus system. The PSO method is demonstrated and compared with conventional OPF method and the intelligence heuristic algorithm such as genetic algorithm, evolutionary programming. The superiority of th method over other methods has been demonstrated on two test cases. From simulation results, it has been found that PSO method is highly competitive for its better general convergence performance.
机译:本文提出了一种基于粒子群优化(PSO)的算法,用于最佳流动,产生具有非平滑燃料成本曲线的产生单元,同时满足发电机容量限制,功率平衡,线流量限制,总线电压和变压器抽头设置的限制已经检查并测试了使用PSO的常规行动流程和所提出的方法,并对标准IEEE 30总线系统进行测试。对PSO方法进行了说明并与常规OPF方法和智能启发式算法(如遗传算法,进化编程)进行比较。在两个测试用例上证明了TH方法的优越性。从仿真结果来看,已经发现PSO方法对其更好的一般收敛性能具有竞争力。

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