使用新的优化方法,为能源可持续性提供以自然为灵感的解决方案
Abdulwahab Ali Almazroi1, Ch Anwar Ul Hassan2
1Department of Information Technology, College of Computing and Information Technology at Khulais, Univeristy of Jeddah, Jeddah, Saudi Arabia.
PloS one
|November 27, 2023
概括
本研究介绍了一种家庭电力管理 (HEM) 系统,使用像草算法 (SWA) 和社会蜘蛛算法 (SSA) 这样的元启发学来实现高效的能源使用. 该HEM系统显著降低了住宅电力成本,并减少了峰值电力需求,增强了家庭能源供应链.
科学领域:
- 电气工程 电气工程
- 计算机科学 计算机科学
- 运营研究 运营研究
背景情况:
- 越来越多的电力需求和现代家庭能源供应链的复杂性需要高效的管理系统.
- 智能家居小工具需要优化调度,以平衡能源消耗和降低成本.
- 现有的能源管理元启发式分析显示,节约成本和减少峰值负载存在局限性.
研究的目的:
- 开发和评估家庭电力管理 (HEM) 系统,以优化住宅能源消耗.
- 为了比较社会蜘蛛算法 (SSA) 和草算法 (SWA) 在家庭能源管理方面的有效性.
- 评估HEM系统对成本节约,峰值与平均功率比率 (PAR) 和碳排放的影响.
主要方法:
- 开发一个包含先进元启发学的家庭电力管理 (HEM) 系统.
- 实施和模拟社会蜘蛛算法 (SSA) 以减少峰值与平均值的功率比率.
- 实施和模拟草算法 (SWA) 以优化成本节约.
- 对SSA和SWA进行比较分析,与现有的元启发式和基线场景进行比较.
主要成果:
- 草算法 (SWA) 在节省成本方面表现出卓越的表现,将住宅电力开支降低了高达3.5%.
- 社会蜘蛛算法 (SSA) 在降低峰值与平均功率比率 (PAR) 中被证明更有效,表明更好的负载平衡.
- 拟议的HEM系统在降低成本和 PAR 改进方面都超过了现有的元启发术.
结论:
- 开发的HEM系统为在供应链中管理家庭电力消耗提供了实用和可持续的解决方案.
- 该系统通过节省成本和通过减少碳排放带来环境优势,提供了显著的经济效益.
- 该研究强调了SWA和SSA等元启发式算法的潜力,以提高住宅能源部门的效率和可持续性.
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