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Single-objective optimal power flow for electric power systems based on crow search algorithm

机译:基于乌鸦搜索算法的电力系统单观最优功率流量

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This paper presents the application of a recent meta-heuristic optimization technique named a crow search algorithm (CSA) in solving the problem of an optimal powerflow (OPF) for electric power systems. Various constrained objective functions, total fuelcost, active power loss and pollutant emission are proposed. The generators’ output powers, generators’ terminal voltages, transmission lines’ taps and the shunt capacitors’ reactive powers are considered as variables to be designed. The proposed methodology basedon the CSA is applied on an IEEE 30-bus system and IEEE 118-bus system. The obtainedresults via the CSA are compared to others and they ensure the superiority of the CSA insolving the OPF problem in electric power systems.
机译:本文介绍了最近名为乌鸦搜索算法(CSA)的元启发式优化技术的应用,解决了电力系统的最佳动力流(OPF)的问题。 提出了各种约束的客观功能,总燃料,有源功率损耗和污染物排放。 发电机的输出功率,发电机的端子电压,传输线路和分流电容器的无功功率被认为是要设计的变量。 所提出的方法基于CSA应用于IEEE 30-BUS系统和IEEE 118总线系统。 通过CSA获得的方法与他人进行比较,并确保CSA在电力系统中溶解OPF问题的CSA的优势。

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