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Comparison between Deterministic methods and the Artificial Bee Colony Algorithm, for the Economic Load Dispatch, turning off the Generators of Higher Cost

机译:确定性方法与人工蜂群算法的比较,用于经济负荷分配,关闭了成本较高的生成器

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The reduction of fuel costs in the production of electric power in Power Plants (PP) is one of the most significant problems in this industry. This problem is known as optimization of the Economic Load Dispatch (ELD). The objective of this paper is to analyze the application of the Artificial Bee Colony Algorithm (ABC) metaheuristics, considering the incremental cost of fuel and the shutdown of the engines with the highest fuel cost per MWh in UTEs whose installed capacity exceeds the required power demand. Several techniques have been developed to solve the problem of ELD, among them: lambda iteration method, gradient method, Newton method and so on. The results for this study with the application of ABC, considering the shutdown of the generators of higher cost per MWh, obtaining a mean reduction of 6.54% in the total fuel cost, compared to the classic solutions that use all engines of the UTE. In addition to cost reduction, this proposal helps the specialist responsible for the management of the UTE in the decision making of the preventive maintenance of the engines that are not being used at the moment of the optimization, improving not only the generation efficiency, but also the generation planning of the plant.
机译:降低电厂(PP)中电力生产中的燃料成本是该行业最重要的问题之一。这个问题被称为经济负荷分配(ELD)的优化。本文的目的是分析人工蜂群算法(ABC)的元启发式方法的应用,其中考虑到燃料增量成本以及在装机容量超过要求的电力需求的UTE中每兆瓦时燃料成本最高的发动机停机的情况。已经开发出解决ELD问题的几种技术,其中包括:λ迭代法,梯度法,牛顿法等。与使用UTE所有引擎的经典解决方案相比,考虑到ABC的应用,本研究的结果是,考虑到关闭每兆瓦时成本较高的发电机,平均总燃料成本平均降低6.54%。除了降低成本外,该建议还帮助负责UTE管理的专家在优化时不使用的发动机的预防性维护决策中做出决定,不仅提高了发电效率,而且还提高了发电效率。工厂的发电计划。

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