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Power economic dispatch using particle swarm optimization

机译:使用粒子群算法的电力经济调度

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Current market environment, ever growing difference between depleting energy resources and increasing power demand and increased expectations of customers from utility companies has made it necessary to adopt some good operational policies by electric utility companies. So the focus of utility companies has shifted towards increased customer focus, enhanced performance and to provide reliable supply at low cost. The electric power system must be operated in a way to schedule generations economically of generation facilities. In last two decades many evolutionary techniques has been developed to solve the optimization problems. Particle swarm optimization has acquired much recognition due to less memory requirement and its inherent simplicity. Particle swarm optimization technique proved to be having strong potential for solving complex and high dimensional optimization problem. PSO is free from local minimum solution convergence which is often encountered while solving nonlinear and non-convex optimization problem through conventional techniques. This paper presents a summarized view of application of PSO for solving power economic dispatch problem.
机译:当前的市场环境,能源消耗和电力需求增加之间的差异越来越大,以及公用事业公司对客户的期望越来越高,使得电力公用事业公司必须采取一些良好的运营政策。因此,公用事业公司的重点已转向增加客户关注度,增强性能并以低成本提供可靠的供应。电力系统必须以一种经济地调度发电设施的发电方式的方式进行操作。在最近的二十年中,已经开发了许多进化技术来解决优化问题。由于较少的内存需求及其固有的简单性,粒子群优化已获得广泛认可。事实证明,粒子群优化技术具有解决复杂高维优化问题的强大潜力。 PSO没有局部最小解收敛,而在通过常规技术解决非线性和非凸优化问题时经常会遇到。本文概述了PSO在解决电力经济调度问题中的应用。

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