对电力系统应用改进的狮算法
1School of Information Engineering, Shanxi Vocational University of Engineering Science and Technology, Taiyuan, China.
PloS one
|December 4, 2024
概括
改进的-狮子算法通过优化经济和环境目标来提高电力系统负载分配效率. 这种新的方法显著降低了燃料成本和排放,与现有方法相比,提供了更好的结果.
科学领域:
- 电气工程 电气工程
- 优化算法 优化算法
- 环境科学 环境科学
背景情况:
- 电力系统的负载分配对于效率至关重要.
- 现有的算法通常仅仅优化经济目标.
- 发电对环境的影响需要同时考虑.
研究的目的:
- 为电力系统负载分配提出一个改进的狮算法.
- 为了实现经济和环境目标的双重优化.
- 为了提高狮算法的全球搜索能力和性能.
主要方法:
- 将精英权重和混乱的搜索机制纳入狮算法.
- 在基准函数 (Sphere和Griebank) 上测试算法的性能.
- 适用于经济负载调度 (ELD) 和环境/经济负载调度 (EELD) 问题,包括点效应.
主要成果:
- 改进的-狮子算法显示了比其他算法更快的融合和更少的代.
- 在ELD模拟中实现了0.10%-2.39% (3单位) 和6% (6单位) 的燃料成本降低.
- 在EELD中,拟议的方案导致燃料总成本为每小时622.46美元,排放量为每小时0.20,总目标函数平均减少了每小时53.55美元.
结论:
- 增强的狮算法显著改善了电力系统负载分配的优化性能.
- 提出的方法有效地平衡了经济和环境方面的考虑.
- 这种方法为高效和可持续的电力系统运行提供了卓越的解决方案.
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