发电技术 ›› 2025, Vol. 46 ›› Issue (2): 209-218.DOI: 10.12096/j.2096-4528.pgt.24179

• 基于群体智能的综合能源系统建模仿真及优化运行 •    

抽水蓄能灰启动下冷热电互补综合能源系统优化调度

侯慧1, 王燕1, 刘超1, 张炜2, 周杨珺2, LI Zhengmao3, 李正天4, 林湘宁4   

  1. 1.武汉理工大学自动化学院,湖北省 武汉市 430070
    2.广西电网有限责任公司电力科学研究院,广西壮族自治区 南宁市 530023
    3.阿尔托大学电气与自动化工程系,南芬兰省 埃斯波市 00076,芬兰
    4.华中科技大学电气与电子工程学院,湖北省 武汉市 430074
  • 收稿日期:2024-08-15 修回日期:2024-10-27 出版日期:2025-04-30 发布日期:2025-04-23
  • 作者简介:侯慧(1981),女,博士,教授,研究方向为电力系统风险评估、能源互联网、电动汽车与电网互动等, houhui@whut.edu.cn
    王燕(2001),女,硕士研究生,研究方向为电力系统风险评估, 302867@whut.edu.cn
    LI Zhengmao(1991),男,博士,助理教授,研究方向为综合能源系统最优规划和运行, Zhengmao.li@aalto.fi
    林湘宁(1970),男,博士,教授,研究方向为电力系统分析与控制、电力系统继电保护, xiangning.lin@hust.edu.cn
  • 基金资助:
    国家自然科学基金项目(U22B20106)

Optimization Scheduling of Cold-Heat-Electricity Integrated Energy System Under Pumped Storage Gray Start

Hui HOU1, Yan WANG1, Chao LIU1, Wei ZHANG2, Yangjun ZHOU2, Zhengmao LI3, Zhengtian LI4, Xiangning LIN4   

  1. 1.School of Automation, Wuhan University of Technology, Wuhan 430070, Hubei Province, China
    2.Electric Power Research Institute, Guangxi Power Grid Co. , Ltd. , Nanning 530023, Guangxi Zhuang Autonomous Region, China
    3.Department of Electrical Engineering and Automation, Aalto University, Espoo 00076, South Finland, Finland
    4.School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei Province, China
  • Received:2024-08-15 Revised:2024-10-27 Published:2025-04-30 Online:2025-04-23
  • Supported by:
    National Natural Science Foundation of China(U22B20106)

摘要:

目的 抽水蓄能机组具有灰启动潜力,将其与综合能源系统(integrated energy system,IES)的多能互补优势相结合,可适用于系统在极端事件下恢复运行。为研究灾后IES的恢复机制,提出一种抽水蓄能灰启动下冷热电互补综合能源系统(cold-heat-electricity IES,CHEIES)优化调度模型。 方法 首先,通过随机场景优化处理风光冷热功率不确定性问题,采用拉丁超立方抽样生成大量随机风光冷热场景,并使用概率距离快速削减法对场景数量进行削减。然后,针对灰启动下的CHEIES,以抽水蓄能作为灰启动电源为热电联产机组提供启动电源,并以灰启动效益为核心考量因素,综合构建单目标优化调度模型,引入冷热电功率平衡约束,确保IES在各种负荷情况下的稳定运行。最后,对模型进行仿真求解,并分析了各种运行方案下的优化调度策略和经济效益。 结果 配置抽水蓄能灰启动的CHEIES在应对极端自然灾害情境下展现出较高的灵活性和运行效率,与未配置抽水蓄能灰启动的方案相比,系统运行成本降低了12.14%。 结论 所提方法可充分挖掘紧急状态下CHEIES的可靠性、经济性与灵活性,为极端事件灾后IES的快速恢复提供了策略支持。

关键词: 综合能源系统(IES), 抽水蓄能, 灰启动, 黑启动, 冷热电互补综合能源系统(CHEIES), 优化调度, 极端事件

Abstract:

Objectives Pumped storage units have gray start potential. Integrating this capability with the multi-energy complementary advantages of an integrated energy system (IES) makes it suitable for system recovery under extreme events. To investigate the post-disaster recovery mechanism of IES, this paper proposes an optimization scheduling model for a cold-heat-electricity integrated energy system (CHEIES) under pumped storage gray start. Methods First, stochastic scenario optimization is employed to address the uncertainties in wind, solar, cold, and thermal power. Latin hypercube sampling is used to generate a large number of random wind-solar-cold-heat scenarios, and a probability distance-based rapid reduction method is applied to reduce the number of scenarios. Then, for CHEIES under gray start, pumped storage serves as the gray start power source to provide startup power for the combined heat and power unit. A single-objective optimization scheduling model is established with gray start benefit as the core consideration, incorporating cold-heat-electricity power balance constraints to ensure the stable operation of IES under various load conditions. Finally, simulations are conducted to solve the model, and optimization scheduling strategies and economic benefits under different operation schemes are analyzed. Results CHEIES with pumped storage ash start-up shows high flexibility and operation efficiency in response to extreme natural disasters. Compared with the scheme without pumped storage ash start-up, the system operation cost is reduced by 12.14%. Conclusions The proposed method fully explores the reliability, economic efficiency, and flexibility of CHEIES under emergency conditions, providing strategic support for the rapid recovery of IES after extreme events.

Key words: integrated energy system (IES), pumped storage, gray start, black start, cold-heat-electricity integrated energy system (CHEIES), optimization scheduling, extreme events

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