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Hybrid integer coded differential evolution - dynamic programming approach for economic load dispatch with multiple fuel options

机译：混合整数编码差分进化-具有多种燃料选择的经济负荷分配动态规划方法

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摘要

This paper presents a novel and efficient approach through a hybrid integer coded differential evolution - dynamic programming (ICDEDP) scheme to solve the economic dispatch (ED) problem with multiple fuel options. A dynamic programming (DP) based simplified recursive algorithm is developed for optimal scheduling of the generating units in the ED problem. The proposed hybrid scheme is developed in such a way that an integer coded differential evolution (ICDE) is acting as a main optimizer to identify the optimal fuel options, and the DP is used to find the fitness of each agent in the population of the ICDE, which makes a quick decision to direct the search towards the optimal region. The hybrid ICDEDP decision vector consists of a sequence of integer numbers representing the fuel options of each unit to optimize quality of search and computation time. A gene swap operator is introduced in the proposed algorithm to improve its convergence characteristics. In order to show the efficiency and effectiveness, the proposed hybrid ICDEDP approach has been examined and tested with numerical results using the ten generation unit economic dispatch problem with multiple fuel options. The test result shows that the proposed hybrid ICDEDP algorithm has high quality solution, superior convergence characteristics and shorter computation time.
机译：本文提出了一种通过混合整数编码差分进化-动态规划（ICDEDP）方案来解决多种燃料选择的经济调度（ED）问题的新颖有效的方法。开发了一种基于动态规划（DP）的简化递归算法，用于ED问题中发电单元的最佳调度。提出的混合方案以如下方式开发：整数编码差分进化（ICDE）作为主要的优化器，以识别最佳燃料选择，而DP用于查找ICDE群体中每种因子的适合度。 ，这可以快速做出决定，将搜索引导至最佳区域。混合ICDEDP决策向量由代表每个单元的燃料选项的整数序列组成，以优化搜索和计算时间的质量。该算法引入了一种基因交换算子，以提高算法的收敛性。为了显示效率和有效性，已经使用具有多种燃料选择的十代机组经济调度问题，对提出的混合ICDEDP方法进行了数值测试和测试。测试结果表明，提出的混合ICDEDP算法具有高质量的解决方案，优异的收敛性和较短的计算时间。

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