优化太阳能发电场互连网络使用图形理论和元启发算法与经济和可靠性分析
Ali Ghias-Nodoushan1, Alireza Sedighi-Anaraki2, Mohammad Rasoul Jannesar3
1Electrical Engineering Department, Yazd University, Yazd, Iran.
Scientific reports
|September 27, 2025
概括
本研究提出了使用Prim算法的图形理论框架,以实现最佳的太阳能农场电网互连,减少能源损失和成本. 该方法的性能优于粒子集群优化,可提供高效可靠的太阳能基础设施.
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:
- 全球能源需求不断增长,需要有效整合太阳能发电场等可再生能源.
- 将分布式太阳能发电场与电网互连,在优化传输损失和基础设施成本方面存在挑战.
研究的目的:
- 引入一个新的图形理论框架,用于设计分布式太阳能发电场的最佳互连网络.
- 为了比较Prim算法的效率与粒子集群优化 (PSO) 的效率,用于网络设计.
- 开发基于图表的可靠性指标来评估网络的稳定性.
主要方法:
- 使用Prim的算法来构建网络设计的最小跨度树.
- 与粒子优化 (PSO) 相比,确定性方法的基准测试.
- 开发和应用基于图形的新型可靠性指标来评估网络的稳定性.
主要成果:
- 在最大限度地减少功耗损失和资本投资方面,Prim的算法表现出了比PSO更好的性能.
- 基于图形的方法实现了较高的拓可靠性,而不是PSO.
- PSO提供了更好的负载平衡,但基于图表的方法对损失敏感和成本驱动的设计更有效.
结论:
- 拟议的图形理论框架提供了一个计算效率高,经济可行的解决方案,以实现最佳的太阳能发电场集成.
- 该方法可扩展,并适应实际约束,为动态优化中的AI/ML集成奠定了基础.
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