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Artificial bee colony algorithm for solving multi-objective optimal power flow problem

机译:人工蜂群算法求解多目标最优潮流问题

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摘要

This paper presents a new and efficient method for solving optimal power flow (OPF) problem in electric power systems. In the proposed approach, artificial bee colony (ABC) algorithm is employed as the main optimizer for optimal adjustments of the power system control variables of the OPF problem. The control variables involve both continuous and discrete variables. Different objective functions such as convex and non-convex fuel costs, total active power loss, voltage profile improvement, voltage stability enhancement and total emission cost are chosen for this highly constrained nonlinear non-convex optimization problem. The validity and effectiveness of the proposed method is tested with the IEEE 9-bus system, IEEE 30-bus system and IEEE 57-bus system, and the test results are compared with the results found by other heuristic methods reported in the literature recently. The simulation results obtained show that the proposed ABC algorithm provides accurate solutions for any type of the objective functions.
机译:本文提出了一种解决电力系统中最佳潮流(OPF)问题的有效方法。在所提出的方法中,人工蜂群(ABC)算法被用作优化OPF问题的电力系统控制变量的主要优化器。控制变量包括连续变量和离散变量。对于这个高度受限的非线性非凸优化问题,选择了不同的目标函数,例如凸和非凸燃料成本,总有功功率损耗,电压分布改善,电压稳定性增强和总排放成本。通过IEEE 9总线系统,IEEE 30总线系统和IEEE 57总线系统对所提方法的有效性和有效性进行了测试,并将测试结果与最近文献报道的其他启发式方法的结果进行了比较。获得的仿真结果表明,所提出的ABC算法可为任何类型的目标函数提供准确的解决方案。

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