基于混合核搜索优化与麻雀算法的经济排放调度问题研究

doi:10.16039/j.cnki.cn22-1249.2023.01.007

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摘要

随着人们对环境保护的日益关注，经济性、环保性电力调度已成为电力系统运行控制研究的热点之一。它本质上是一个多目标优化问题，在不违反操作约束的前提下，使燃料成本和排放污染同时最小化。为了解决这一问题，提出了一种基于核搜索优化(KSO)和麻雀算法（SSA）预警的改进算法(HKSOSSA)。采用提出的(HKSOSSA)优化算法求解6机IEEE30节点的EED问题。结果表明，HHKSOSSA算法能够很好地权衡燃料成本与排放目标之间的关系。

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	董如意
	马龙

关键词: 经济排放调度多目标优化核搜索算法麻雀算法

Abstract:

With the increasing concern over environment protection, economic and environmental power dispatch has become one of the active research areas in the power system operation and control. It is essentially a Multi-Objective Optimization Problem, which minimizes both fuel cost and emission pollution simultaneously without violating the operational constraints. To solve this problem, this article presents a new hybrid algorithm based on kernel search optimization (KSO) and sparrow search algorithm (SSA) (HKSOSSA). The proposed HKSOSSA optimization algorithm is employed to solve IEEE 6-unit EED problem. The results show that the proposed HHKSOSSA algorithm for EED problem can obtain a better trade-off between fuel cost and emission objectives compared to those reported algorithms in the recent literature.

Key words: economic emission dispatch multiple objective optimization kernel search optimization sparrow search algorithm

出版日期: 2023-01-25 发布日期: 2023-01-25 整期出版日期: 2023-01-25

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引用本文:

董如意, 马龙. 基于混合核搜索优化与麻雀算法的经济排放调度问题研究 [J]. 吉林化工学院学报, 2023, 40(1): 29-33.
DONG Ruyi, MA Long. Study on Economic Emission Scheduling Problem based on Hybrid Kernel Search Optimization and Sparrow Algorithm . Journal of Jilin Institute of Chemical Technology, 2023, 40(1): 29-33.

链接本文:

https://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2023.01.007 或 https://xuebao.jlict.edu.cn/CN/Y2023/V40/I1/29

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