Application of shuffled frog leaping algorithm for economic dispatch with multiple fuel options

R. Balamurugan
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引用次数: 7

Abstract

Economic dispatch with multiple fuel options is one of the important optimization problems in a power system. The cost curve of a thermal unit with multiple fuel options is highly nonlinear, containing discontinuities, and it is more realistically denoted as a segmented piecewise quadratic function. In this paper, a recent evolutionary algorithm called the shuffled frog leaping algorithm (SFLA) is applied for the solution of economic dispatch problem with multiple fuel options. The decision vector of SFLA consists of a sequence of integer numbers which represents the fuel options of generating units. In the proposed approach, SFLA is used to identify the optimal combinations of fuel options for the committed generating units and fitness of each decision vector in the population of SFLA is evaluated through the non-iterative lagrangian multiplier method. The combination of evolutionary algorithm with analytical approach proposed in this paper makes a quick decision to direct the search towards the optimal region. The proposed algorithm has been implemented to ten-unit economic dispatch problem with piecewise objective functions. The simulation results of the proposed algorithm are compared with the results of various methods reported in the literature. The comparison of results shows that the proposed SFLA algorithm provides quality solutions with lesser computation time.
混合青蛙跳跃算法在多燃料选择经济调度中的应用
多燃料经济性调度是电力系统优化中的重要问题之一。具有多种燃料选择的热力装置的成本曲线是高度非线性的,包含不连续,更实际地表示为分段的分段二次函数。本文将一种新的进化算法——洗阵青蛙跳跃算法(SFLA)应用于求解多燃料选择的经济调度问题。SFLA的决策向量由代表发电机组燃料选择的整数序列组成。在该方法中,使用SFLA来识别承诺发电机组燃料选择的最优组合,并通过非迭代拉格朗日乘数法评估SFLA种群中每个决策向量的适应度。本文提出的进化算法与解析法相结合的方法,可以快速决策,将搜索导向最优区域。该算法已应用于具有分段目标函数的十单元经济调度问题。将所提算法的仿真结果与文献中报道的各种方法的结果进行了比较。结果对比表明,本文提出的SFLA算法以较少的计算时间提供了高质量的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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