计及建筑热负荷弹性的综合能源系统调度方法

doi:10.16183/j.cnki.jsjtu.2021.534

上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (7): 803-813.doi: 10.16183/j.cnki.jsjtu.2021.534

所属专题：《上海交通大学学报》2023年“新型电力系统与综合能源”专题

• 新型电力系统与综合能源 • 上一篇下一篇

计及建筑热负荷弹性的综合能源系统调度方法

胡博¹, 程欣², 邵常政¹(), 黄威¹, 孙悦³, 谢开贵¹

1.重庆大学输配电装备及系统安全与新技术国家重点实验室,重庆 400044
2.国网山西省电力公司经济技术研究院,太原 030001
3.中国长江电力股份有限公司,湖北宜昌,443002

收稿日期:2021-12-28 修回日期:2022-02-18 接受日期:2022-04-02 出版日期:2023-07-28 发布日期:2023-07-28
通讯作者: 邵常政 E-mail:cshao@cqu.edu.cn.
作者简介:胡博(1983-),教授,博士生导师,从事电力系统可靠性评估及综合能源系统优化运行研究.
基金资助:
国家自然科学基金项目(52107072);中国博士后科学基金项目(2021M693711);中央高校基本科研业务费项目(2021CDJQY-037)

Optimal Dispatch of Integrated Energy System Based on Flexibility of Thermal Load

HU Bo¹, CHENG Xin², SHAO Changzheng¹(), HUANG Wei¹, SUN Yue³, XIE Kaigui¹

1. State Key Laboratory of Power Transmission Equipment and System Security and New Technology,Chongqing University, Chongqing 400044, China
2. Economic and Technical Research Institute,State Grid Shanxi Electric Power Company, Taiyuan 030001, China
3. China Yangtze Power Co., Ltd., Yichang 443002, Hubei, China

Received:2021-12-28 Revised:2022-02-18 Accepted:2022-04-02 Online:2023-07-28 Published:2023-07-28
Contact: SHAO Changzheng E-mail:cshao@cqu.edu.cn.

摘要/Abstract

摘要：

具有一定弹性的建筑热负荷被视为电-热综合能源系统运行优化的重要调节资源.考虑建筑热负荷具有规模大、单体容量小的特点,非侵入式的数据驱动方法成为量化建筑热负荷弹性的有效手段.然而,由于数据不足或模型精度不够,该方法将不可避免地产生误差,给电-热综合能源系统的优化调度带来认知不确定性.因此,提出一种考虑建筑热负荷弹性并兼容相关认知不确定性的电-热综合能源系统优化调度方法.分析基于数据驱动的建筑热负荷需求弹性评估方法,将评估过程中产生的误差建模为认知不确定性,并通过改进的D-S证据理论对多源误差进行融合;采用拉丁超立方抽样方法生成表征热负荷弹性认知不确定性的场景,并通过模糊聚类法进行场景削减;将构造的场景集嵌入电-热综合能源系统的协调优化调度中,实现对建筑热负荷弹性及相关认知不确定性的综合考虑.算例仿真结果表明,考虑建筑热负荷需求弹性及认知不确定性对减少弃风、提高电热综合能源系统的运行灵活性至关重要.

关键词: 需求弹性, 认知不确定性, 电热综合能源系统, 优化调度

Abstract:

The flexibility of thermal loads of buildings is a valuable balancing resource for operation of the heat and electricity integrated energy system (HE-IES). Considering the characteristics of large scale and small single load capacity of the themal load, the non-intrusive data-driven method has become an effective means to quantify the flexibility of building thermal load. However, due to the inaccuracy of the model or the lack of data, this method inevitably produces errors and brings epistemic uncertainty to the optimal dispatch of the HE-IES. An optimal dispatch model of the HE-IES that is compatible with the epistemic uncertainty of demand flexibility in the thermal loads of buildings is proposed. First, a data-driven flexible demand assessment method for building thermal load is described. The measurement errors are modeled as epistemic uncertainty and the multiple error sources are combined by using the D-S evidence theory. Then, the representative scenarios are selected to represent the epistemic uncertainty of the demand flexibility based Latin hypercube sampling(LHS) method, and the scenarios are reduced by the fuzzy clustering method. Finally, the representative scenarios are embedded in the coordinated and optimized dispatch of the HE-IES to realize the comprehensive consideration of the thermal load flexibility and related epistemic uncertainty of the building. The results demonstrate that considering the epistemic uncertainties of the thermal load demand is crucial for reducing the wind power curtailments and improving the operational flexibility of HE-IES.

Key words: demand flexibility, epistemic uncertainty, heat and electricity integrated energy system(HE-IES), optimal dispatch

中图分类号:

TM73

胡博, 程欣, 邵常政, 黄威, 孙悦, 谢开贵. 计及建筑热负荷弹性的综合能源系统调度方法[J]. 上海交通大学学报, 2023, 57(7): 803-813.

HU Bo, CHENG Xin, SHAO Changzheng, HUANG Wei, SUN Yue, XIE Kaigui. Optimal Dispatch of Integrated Energy System Based on Flexibility of Thermal Load[J]. Journal of Shanghai Jiao Tong University, 2023, 57(7): 803-813.

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参数	误差来源(误差数量级)
k_p_,_r_,_t	提取过程(10^-3)
	训练过程(10^-2)
C_p_,_r_,_t	提取过程(10^-6)
	训练过程(10^-3)

计及建筑热负荷弹性的综合能源系统调度方法

Optimal Dispatch of Integrated Energy System Based on Flexibility of Thermal Load

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