基于增量成本的混合差分进化经济与排放联合调度

J. Gunda, P. Acharjee, Sharmila Biswas
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引用次数: 7

摘要

经济负荷调度是电力系统运行规划中需要解决的重要问题之一。如今,由于环保意识的增强,除了燃料成本外,发电设施还应优化其排放。近年来,研究人员正在开发各种软计算技术来解决经济与排放的联合调度问题。针对传统差分进化算法存在局部最优或停滞问题,提出了考虑安全约束的混合差分进化算法(HDEA)。为评价所提方法的准确性、收敛速度和适用性,将所提方法应用于具有6台发电机组的标准IEEE-30总线系统中求解CEED问题,并将CEED问题的求解结果与传统PSO和DE进行了比较。测试结果表明,所提方法在燃料成本、排放、总损耗和计算次数等方面均优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incremental cost based combined economic and emission dispatch using hybrid differential evolution
Economic load dispatch (ELD) is one of the most important problems to be solved in the operation and planning of a power system. Nowadays due to increased environmental awareness, generating utilities should optimize their emission in addition to the fuel cost. Recently researchers are developing different soft computing techniques to solve the combined economic and emission dispatch (CEED) problem. In this paper, Hybrid differential evolution Algorithm (HDEA) is developed to solve CEED problem considering security constraints as the traditional Differential evolution (DE) is suffers from local optima or stagnation problem. To evaluate the accuracy, convergence speed and applicability of the proposed method, it is implemented on the standard IEEE-30 bus system having six generating units to solve CEED problem and the results of CEED problem are compared with traditional PSO and DE. The tested results indicate that the proposed method is more efficient than the others in terms of fuel costs, emission, total losses and computational times.
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