1.清华大学电机工程与应用电子技术系,北京市 100084
2.阿里巴巴达摩院,浙江省杭州市 311121
3.北京清能互联科技有限公司,北京市 100080
4.中国南方电网有限责任公司,广东省广州市 510663
钟海旺(1986—),男,博士,副教授,IEEE高级会员,主要研究方向:电力系统优化运行、电力市场。E-mail:zhonghw@tsinghua.edu.cn
虞泽宽(2000—),男,博士研究生,主要研究方向:电力系统优化运行、机组组合高效求解算法。E-mail:yzk22@mails.tsinghua.edu.cn
王孟昌(1983—),男,博士,主要研究方向:运筹优化算法及应用。E-mail:mengchang.wmc@alibaba-inc.com
陈亦平(1978—),男,通信作者,博士,教授级高级工程师,主要研究方向:电力系统稳定与控制、电力系统调度运行。E-mail:chenyiping@csg.cn
收稿:2025-05-29,
修回:2025-10-04,
网络首发:2025-11-26,
纸质出版:2026-09-25
移动端阅览
钟海旺,虞泽宽,王孟昌等.电力系统优化求解引擎构建及应用[J].电力系统自动化,2026,50(18):155-165.
ZHONG Haiwang,YU Zekuan,WANG Mengchang,et al.Construction and Application of Power System Optimization Engine[J].Automation of Electric Power Systems,2026,50(18):155-165.
钟海旺,虞泽宽,王孟昌等.电力系统优化求解引擎构建及应用[J].电力系统自动化,2026,50(18):155-165. DOI: 10.7500/AEPS20250529001.
ZHONG Haiwang,YU Zekuan,WANG Mengchang,et al.Construction and Application of Power System Optimization Engine[J].Automation of Electric Power Systems,2026,50(18):155-165. DOI: 10.7500/AEPS20250529001.
电力系统优化求解引擎作为电力系统规划运行与电力市场出清的底层数学工具,对于新型电力系统建设与电力市场高效运营具有重要支撑作用。文中对电力系统优化求解引擎的研发构建及在中国南方电网的应用进展进行了介绍。首先,介绍了优化求解引擎的框架和功能模块,并阐述了求解引擎采用的大规模优化通用求解方法与电力系统优化高效求解方法原理。然后,基于南方电网实际场景开展电力系统优化求解引擎应用的实证分析,验证了其求解效率与准确性。最后,对优化求解引擎在电力系统领域的应用前景进行了展望。
The power system optimization engine
as a fundamental mathematical tool for the planning and operation of power systems and the clearing of electricity markets
plays a crucial supporting role in the construction of new power systems and the effective operation of electricity markets. This paper introduces the development and construction of the power system optimization engine and its application progress in China Southern Power Grid (CSG). First
the framework and functional modules of the optimization engine are presented
along with the generic large-scale optimization methods and the principles of efficient solving techniques for power system optimization adopted by the engine. Then
case studies of the power system optimization engine based on the application scenarios in CSG are introduced
and the solving efficiency and accuracy are verified. Finally
the prospects of the optimization engine in power systems are analyzed.
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