基于机组承诺问题的多目标粒子群算法在经济调度中的应用

Chefai Dhifaoui, T. Guesmi, H. Hadj Abdallah
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引用次数: 7

摘要

本文提出了一种利用MOPSO算法求解基于机组承诺问题的最优经济调度问题的新方法。机组承诺问题可以定义为发电机组在每天到每周的时间范围内为完成某一目标而进行的生产调度。问题解决方案必须同时考虑发电机的限制(如斜坡速率限制和最小启动或关闭时间)和系统的限制(储备和能源需求,以及潜在的传输限制)。第一个函数是生产成本。第二个是过渡成本。对比研究了可靠性约束对得到的最优解的影响。采用10机39总线系统,结果表明了MOPSO的有效性,并证实了其解决机组承诺问题的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of multi-objective PSO algorithm for Economic Dispatch (ED) through Unit Commitment Problems (UCP)
This paper presents a new approach via MOPSO algorithm to solve optimal Economic Dispatch (ED) via Unit Commitment Problems (UCP). The unit commitment problem can be defined as the scheduling of production of electric power generating units over a daily to weekly time horizon in order to accomplish some objective. The problem solution must respect both generator constraints (such as ramp rate limits and minimum up or down times) and system constraints (reserve and energy requirements and, potentially, transmission constraints). The first function is the production cost. While the second one is the transition cost. A comparative study is conducted to examine the impact of reliability constraint on the optimal solution obtained. The ten machine thirty nine-bus system is used and the results show the effectiveness of MOPSO and confirm its potential to solve the unit commitment problem.
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