一个基于分布式发电和对天气和负载波动进行补偿装置的多目标最佳集成的pareto策略
Khaled Fettah1, Talal Guia1, Ahmed Salhi2
1Electrical Engineering Department, Laboratory (LNTDL), Hamma Lakhdar University of El Oued, 39000, El Oued, Algeria.
Scientific reports
|May 6, 2024
概括
多目标多节优化 (MOMVO) 算法有效地将分布式发电和电容库集成到电网中. 这种优化将能耗损失降低高达50%,并改善电压稳定性,提高网络效率和可靠性.
科学领域:
- 电气工程 电气工程
- 优化算法 优化算法
- 电力系统 电力系统
背景情况:
- 电力配电网络面临能源损失和电压偏差的挑战.
- 集成分布式发电 (DG) 和电容银行 (CB) 需要复杂的优化策略.
- 现有的算法在处理多目标电力系统优化时可能缺乏效率.
研究的目的:
- 开发并提出一个全面的优化框架,以实现总局和中央集团的最佳整合.
- 为了最大限度地减少能源损失和电力分布网络中的电压偏差.
- 评估多目标多节优化 (MOMVO) 算法的性能与其他领先的算法相比.
主要方法:
- 使用多目标多节优化 (MOMVO) 算法.
- 模拟了标准IEEE 33总线和IEEE 69总线测试系统的框架.
- 通过多目标水母搜索 (MOJS),多目标花粉算法 (MOFPA) 和多目标利赫伯格算法 (MOLA) 进行了比较分析.
主要成果:
- 实现了高达50.15%的能源损耗降低,并显著改善了电压稳定性 (例如,0.89到0.94pu).
- 通过降低能源损失的年度成本 (高达47.59%),证明了实质性的经济效益.
- 与其他测试的算法相比,MOMVO显示出优越的融合速度和解决方案质量.
结论:
- MOMVO算法对于优化配送网络的技术和经济效率是强大而有效的.
- 像MOMVO这样的先进优化技术对于可持续的可再生能源整合至关重要.
- 该研究为提高电力基础设施的系统效率,可靠性和可持续性提供了一条途径.
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