
西安交通大学 电气工程学院,陕西 西安 710049
Received:17 September 2025,
Revised:2026-02-03,
Online First:10 February 2026,
Published:10 May 2026
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杨续松,罗先觉,王建学等.含大规模可再生能源的电力系统中长期时序-随机生产模拟方法[J].电力自动化设备,2026,46(05):199-207.
Yang Xusong,Luo Xianjue,Wang Jianxue,et al.Mid-long term sequential-probabilistic production simulation method of power system with large-scale renewable energy[J].Electric Power Automation Equipment,2026,46(05):199-207.
杨续松,罗先觉,王建学等.含大规模可再生能源的电力系统中长期时序-随机生产模拟方法[J].电力自动化设备,2026,46(05):199-207. DOI: 10.16081/j.epae.202602011.
Yang Xusong,Luo Xianjue,Wang Jianxue,et al.Mid-long term sequential-probabilistic production simulation method of power system with large-scale renewable energy[J].Electric Power Automation Equipment,2026,46(05):199-207. DOI: 10.16081/j.epae.202602011.
针对含大规模可再生能源的电力系统在中长期平衡存在的供电安全问题和可再生能源消纳问题,提出时序-随机生产模拟方法。上层模型采用时序生产模拟技术,以周为时间周期在全年范围内进行优化,可计及多种运行约束并搜索系统最优运行方式;下层模型采用随机生产模拟技术,在充分考虑多种不确定性的情况下对电力系统每周的供电裕度和消纳空间进行校核,再将校核结果转化为优化约束反馈给上层模型。该方法通过2层模型的相互配合,在满足供电安全和可再生能源消纳要求的情况下给出经济成本最优的中长期运行方式,有效结合了2类生产模拟技术的优点。通过测试系统验证了该方法的有效性和先进性。
Aiming at the power supply safety problem and renewable energy consumption problem in mid-long term balance for power system with large-scale renewable energy,a sequential-probabilistic production simulation method is proposed. The upper-layer model adopts sequential production simulation technology,optimizes in a weekly time scale over the entire year,which can consider multiple operation constraints and search optimal system operation mode. The lower-layer model adopts probabilistic production simulation technology,verifies the weekly power supply margin and consumption space of power system under the condition of fully considering multiple uncertainties,and converts the verification results into optimization constraints for feeding back to the upper-layer model. Through the cooperation of two-layer models,the method provides a mid-long term operation mode with optimal economy under the condition of satisfying power supply safety and renewable energy consumption requirements,effectively combining the advantages of the two types of production simulation technologies. The effectiveness and advancement of the method are verified through a test system.
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