混合Salp群优化方法在OPF问题中的应用

A. Khelifi, B. Bentouati, S. Chettih, R. A. Sehiemy
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引用次数: 2

摘要

针对最优潮流问题,提出了一种新的混合求解方法。为了实现这一目标,提出了一种新的混合Salp群算法(HSSA)来寻找OPF问题的最优边界。该混合算法结合了salp swarm算法(SSA)和particle swarm optimization (PSO)算法的优点。建议的HSSA甚至为冲突约束提供了更有效的解决方案。该方法应用于发电成本、环境污染排放、有功损耗、电压偏差和电压稳定性五个目标函数。在IEEE 30总线测试系统中进行了测试和结果验证,与文献中其他优化方法相比,该优化方法具有较高的性能。对单目标和双目标研究案例进行了测试,以证明所提出的HSSA与原始SSA和PSO以及文献中现有方法相比的能力。
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Application of Hybrid Salp Swarm optimization Method for Solving OPF Problem
In this paper, a new hybrid solution to the Optimal Power Flow (OPF) problem is proposed. In order to achieve this goal, a new hybrid Salp Swarm Algorithm (HSSA) is proposed to find the optimal frontier of OPF problem. The proposed hybrid algorithm combines the advantages of the salp swarm algorithm (SSA) and particle swarm optimization (PSO) algorithm. The proposed HSSA provides more efficient solutions even for conflict constraints. This method is applied on five objective functions called power generation cost, environmental pollution emissions, active power loss, voltage deviation and voltage stability. The tests and results of the proposed HSSA have been applied to IEEE 30 bus test system to demonstrate the high performance compared with other optimization methods in the literature. Single and bi-objectives studied cases are tested to prove the capability of the proposed HSSA compared with the original SSA and PSO as well as the existing methods in the literature.
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