Medium scale multi-constraint economic load dispatch using hybrid metaheuristics

D. Santra, A. Mukherjee, K. Sarker, S. Mondal
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引用次数: 1

Abstract

This paper reports the application of a hybrid metaheuristic — a combination of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) methods, in midscale thermal power dispatch problem with transmission losses. The hybrid technique applies ACO over output obtained by PSO to get an economic load dispatch (ELD) solution close to global optima. In the present study the hybrid technique has been experimented with a 15-generator system by considering generator capacity constraints, prohibited operating zones (POZ), ramp rate limits (RRL) and valve point loading (VPL) in addition to transmission loss. MATLAB simulation has been done for three test cases involving different combinations of constraints. This unique study comes up with encouraging results wherein the generation cost, loss and convergence are better than that yielded by other hybrid methods.
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基于混合元启发式的中等规模多约束经济负荷调度
本文将粒子群优化(PSO)和蚁群优化(ACO)相结合的混合元启发式算法应用于具有传输损耗的中型火电调度问题。混合算法将蚁群算法应用于粒子群算法的输出,得到接近全局最优的经济负荷调度解。在目前的研究中,混合技术已经在一个15台发电机的系统中进行了实验,考虑了发电机容量限制、禁止操作区域(POZ)、斜坡速率限制(RRL)和阀点负载(VPL)以及传输损耗。对涉及不同约束组合的三个测试用例进行了MATLAB仿真。这项独特的研究取得了令人鼓舞的结果,其中发电成本,损失和收敛性优于其他混合方法。
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