在极端气候条件下,具有风险意识的电力调度与大规模分布式可再生能源集成
Luo Xu1,2, Hongtai Zeng3, Ning Lin1,2
1Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544.
概括
一种名为REDUCER的新模式,在极端天气期间,利用可再生能源在发电网中管理风险. 它将运营成本降低30%,并提高电网应对气候挑战的弹性.
科学领域:
- 电气工程 电气工程
- 气候科学 气候科学
- 运营研究 运营研究
背景情况:
- 配电网络易受风等气候极端影响,尤其是在高度集成可再生能源的情况下.
- 当前的调度方法忽视了分布网络中的时空风险,导致电力失衡.
- 越来越多的极端气候和分布式可再生能源需要先进的风险管理策略.
研究的目的:
- 为面对气候极端和可再生能源整合的配电网络开发一个具有风险意识的电力调度模型.
- 加强对前一天发电中的时空风险的管理.
- 为了降低运营成本并提高电网弹性.
主要方法:
- 在气候极端情况下引入了风险意识的电力调度与可再生能源集成 (REDUCER) 模型.
- 集成的高分辨率的空间时间风险分析,用于配送网络.
- 使用了一个受限制的热值-风险值混合整数凸优化框架.
主要成果:
- 在菲奥纳风期间应用于2022年波多黎各电网,REDUCER有效地管理了风险.
- 减少对额外的灵活性资源的依赖,以管理电力不平衡.
- 与极端场景中的标准策略相比,运营成本降低了约30%.
- 有效地管理来自分布式太阳能集成的净需求变化,同时保持低运营成本.
结论:
- REDUCER提供了一种实用解决方案,以实现成本效益和弹性发电.
- 该模型解决了在气候极端和可再生能源整合下管理分布网络风险的关键差距.
- 它为面对不断变化的挑战的现代电力系统提供了一个强大的框架.
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