粒子群优化技术在经济电力调度中的应用

A. Jaini, I. Musirin, N. Aminudin, Muhammad Murtadha Othman, T. Rahman
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引用次数: 17

摘要

电力经济调度问题在电力系统的运行中起着重要的作用。它是一种通过调度可用的发电资源来供应系统负荷来确定电力系统最有效、低成本和可靠运行的方法。经济调度的主要目标是在保持发电资源运行约束的前提下,使发电总成本最小化。本文提出了一种加速系数为常数的粒子群优化算法(PSO)来解决电力经济调度问题。粒子群优化(PSO)是一种以群体智能为模型的算法,它在搜索空间中找到优化问题的解,或者在存在目标的情况下对社会行为进行建模和预测。在本研究中,使用IEEE 26-BUS RTS标准对所提出的技术进行了测试,结果表明所提出的技术在解决问题方面具有最佳解决方案的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Particle swarm optimization (PSO) technique in economic power dispatch problems
Economic power dispatch problem plays an important role in the operation of the power systems. It is a method of determine the most efficient, low cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. The primary objective of economic dispatch is to minimize the total cost of generation while maintaining the operational constraints of the available generation resources. In this paper, a particle swarm optimization algorithms (PSO) with one of the accelerating coefficients being constant are proposed to solve the economic power dispatch problem. Particle swarm optimization (PSO) is algorithms modeled on swarm intelligence that finds a solution to an optimization problem in a search space, or model and predict social behavior in the presence of objectives. In this study, the proposed technique was tested using the standards IEEE 26-BUS RTS and the results revealed that the proposed technique has the merit in achieving optimal solution for addressing the problems.
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