基于风电分时电价的虚拟电厂参与清洁供暖运营优化方法

doi:10.11930/j.issn.1004-9649.202306102

中国电力 ›› 2024, Vol. 57 ›› Issue (1): 51-60.DOI: 10.11930/j.issn.1004-9649.202306102

基于风电分时电价的虚拟电厂参与清洁供暖运营优化方法

冯云辰¹(), 加鹤萍¹(), 闫敏², 李根柱¹, 刘乐³, 刘敦楠¹

1. 华北电力大学经济与管理学院，北京　102206
2. 北京煜邦电力技术股份有限公司，北京　100029
3. 吉林电力交易中心有限公司，吉林长春　130021

收稿日期:2023-06-27 接受日期:2023-10-23 出版日期:2024-01-28 发布日期:2024-01-23
作者简介:冯云辰（2000—），女，硕士研究生，从事虚拟电厂、电力市场研究，E-mail：fengyunchen2022@ncepu.edu.cn
加鹤萍（1992—），女，通信作者，博士，副教授，从事电力需求侧资源运营优化、虚拟电厂、电力可靠性研究，E-mail：jiaheping@ncepu.edu.cn
基金资助:
国家自然科学基金资助项目（考虑性能共享与存储的广义多态备用系统可靠性优化研究，72001078）；第七届中国科协青年人才托举工程项目（面向新型电力系统的规模化虚拟电厂运营优化，2021QNRC001）。

Operation Optimization Method for Virtual Power Plant Participating in Clean Heating Based on Time-of-Use Tariff of Wind Power

Yunchen FENG¹(), Heping JIA¹(), Min YAN², Genzhu LI¹, Le LIU³, Dunnan LIU¹

1. School of Economics and Management, North China Electric Power University, Beijing 102206, China
2. Beijing Yupont Electric Power Technology Co., Ltd., Beijing 100029, China
3. Jilin Electricity Trading Center Co., Ltd., Changchun 130021, China

Received:2023-06-27 Accepted:2023-10-23 Online:2024-01-28 Published:2024-01-23
Supported by:
This work is supported by National Natural Science Foundation of China (Research on Reliability Optimization of Generalized Multi-state Standby Systems with Performance Sharing and Storage, No.72001078) and the Young Elite Scientists Sponsorship Program by China Association for Science and Technology (Operation Optimization of Large-Scale Virtual Power Plants for New Power Systems, No.2021QNRC001).

摘要/Abstract

摘要：

随着“碳达峰、碳中和”目标的提出，迅速发展的风电由于其随机性与波动性，面临突出的风电消纳问题。蓄热式电采暖作为中国北方地区主要供暖设备，虚拟电厂作为需求侧资源的主要聚合技术手段，聚合蓄热式电采暖的虚拟电厂可为消纳风电、提高风电利用率提供解决途径。对此，提出一种基于风电功率的分时电价划分方法，实现虚拟电厂聚合蓄热式电采暖参与基于分时电价的清洁供暖交易优化运营。首先，阐述虚拟电厂聚合蓄热式电采暖用户参与风电供暖的交易模式；其次，考虑热惯性对蓄热式电采暖和房屋进行精细化建模，提出基于层次凝聚聚类算法的分时电价方法，建立基于Weber-Fechner定律的负荷模糊响应模型，并构建多方主体综合收益最大、弃风量最小和负荷波动最小的虚拟电厂多目标运营优化模型；最后，通过算例分析风电消纳效果和虚拟电厂收益，验证该方法能够有效促进风电消纳、提高多方主体积极性，并具有一定的规模经济性，以期为缓解弃风问题提供参考。

关键词: 虚拟电厂, 分时电价, 蓄热式电采暖, 层次凝聚聚类算法, 负荷模糊响应

Abstract:

With the proposal of carbon peaking and carbon neutrality targets, the rapid development of wind power is facing the prominent accommodation problem due to wind power’s randomness and volatility. Regenerative electric heating is a primary heating mode adopted in Northern China, and the virtual power plant (VPP) is the primary demand-side resource aggregation technology. The VPP, which aggregates regenerative electric heating, can provide a solution for wind power accommodation and increasing the wind power usage rate. In this regard, this paper proposes a wind power based time-of-use tariff division method to realize the optimal operation of VPP aggregating regenerative electric heating to participate in time-of-use tariff-based clean heating trading. Firstly, the transaction mode of VPP aggregating regenerative electric heating users to participate in wind power heating is described. Secondly, with consideration of the thermal inertia, the regenerative electric heating and buildings are modeled in detail, and a time-of-use tariff method based on hierarchical agglomerative clustering algorithm is proposed. A load fuzzy response model is established based on Weber-Fechner law, and a VPP operation optimization model is constructed with multi-objective of maximum comprehensive benefits of multiple entities, minimum wind curtailment and smallest load volatility. The wind power accommodation effects and VPP benefits are analyzed through case study. It is verified that the proposed method can effectively promote the wind power accommodation and raise the enthusiasm of multiple entities.

Key words: virtual power plant, time-of-use tariff, regenerative electric heating, hierarchical agglomerative clustering algorithm, load fuzzy response

冯云辰, 加鹤萍, 闫敏, 李根柱, 刘乐, 刘敦楠. 基于风电分时电价的虚拟电厂参与清洁供暖运营优化方法[J]. 中国电力, 2024, 57(1): 51-60.

Yunchen FENG, Heping JIA, Min YAN, Genzhu LI, Le LIU, Dunnan LIU. Operation Optimization Method for Virtual Power Plant Participating in Clean Heating Based on Time-of-Use Tariff of Wind Power[J]. Electric Power, 2024, 57(1): 51-60.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202306102

https://www.electricpower.com.cn/CN/Y2024/V57/I1/51

图/表 12

图 1 蓄热式电采暖参与风电供暖交易模式

Fig.1 The wind power heating trading mode with participation of regenerative electric heating

图 2 HAC算法流程

Fig.2 Flowchart of HAC algorithm

图 3 负荷响应机理

Fig.3 Load response mechanism

表 1 典型居民房屋计算建筑热力学模型参数

Table 1 Thermodynamic model parameters for typical residential buildings

参数		数值
k_wall		18
k_window		21
v/(m·s^–1)		3.2
G_S/(W·m^–2)		156
F_W/m²		7
k_v		12.1
ρ_air/(W·h·℃^–1)		3.2025

表 2 蓄热式电采暖设备参数

Table 2 Regenerative electric heating equipment parameters

参数		数值
η_h/%		99
η_xr/%		98
η_fr/%		95

表 3 基于Weber-Fechner定律的负荷模糊响应模型参数

Table 3 Weber-Fechner law based load fuzzy response model parameters

参数		数值
λ_fg	P_a/(元·(kW·h)^–1)	0.10
λ_fg	P_b/(元·(kW·h)^–1)	0.70
λ_fp	P_a/(元·(kW·h)^–1)	0.05
λ_fp	P_b/(元·(kW·h)^–1)	0.52
λ_pg	P_a/(元·(kW·h)^–1)	0.03
λ_pg	P_b/(元·(kW·h)^–1)	0.41

图 4 12月份典型日的24 h气温和风电出力曲线

Fig.4 Curves of 24-hour temperature and wind power output of typical days in December

表 4 场景2电采暖用户分时电价

Table 4 Time-of-use tariff for electric heating users in scenario 2

时段		价格/(元·(kW·h)^–1)
05:00—20:00		0.45
03:00—05:00；20:00—21:00		0.31
00:00—03:00；21:00—24:00		0.26

图 5 场景3分时电价

Fig.5 Time-of-use tariff in scenario 3

图 6 不同场景平均每户的负荷情况对比

Fig.6 Comparison of average load of each household in different scenarios

图 7 不同场景弃风消纳情况对比

Fig.7 Comparison of curtailed wind power accommodation under different scenarios

表 5 不同场景下收益成本对比

Table 5 Benefit comparison of VPP under different scenarios

场景	VPP收益/元	用户成本/(元·户^–1)
1	15189.17	50.09
2	18507.92	25.17
3	197957.53	24.38

参考文献 24

1	张智刚, 康重庆. 碳中和目标下构建新型电力系统的挑战与展望[J]. 中国电机工程学报, 2022, 42 (8): 2806- 2819.
	ZHANG Zhigang, KANG Chongqing. Challenges and prospects for constructing the new-type power system towards a carbon neutrality future[J]. Proceedings of the CSEE, 2022, 42 (8): 2806- 2819.
2	洪增林, 钞中东, 周阳, 等. 关中地区清洁能源供暖方案的经济环境效益研究[J]. 生态经济, 2021, 37 (1): 157- 163, 192.
	HONG Zenglin, CHAO Zhongdong, ZHOU Yang, et al. Study on the economic and environmental benefits of clean energy heating solutions in Guanzhong region[J]. Ecological Economy, 2021, 37 (1): 157- 163, 192.
3	王楠, 张辰, 何旭道, 等. 基于弃风消纳的热网主动储热优化[J]. 中国电力, 2023, 56 (2): 114- 122.
	WANG Nan, ZHANG Chen, HE Xudao, et al. Optimization of active heat storage in heat-supply network considering curtailed wind power consumption[J]. Electric Power, 2023, 56 (2): 114- 122.
4	程杉, 徐建宇, 何畅, 等. 计及不确定性的综合能源系统容量规划方法[J]. 电力系统保护与控制, 2021, 49 (18): 17- 24. DOI
	CHENG Shan, XU Jianyu, HE Chang, et al. Optimal capacity planning of an integrated energy system considering uncertainty[J]. Power System Protection and Control, 2021, 49 (18): 17- 24. DOI
5	陈家伦, 蒋欢春, 卞韶帅, 等. 660 MW梯级供热机组耦合电锅炉运行优化[J]. 中国电力, 2022, 55 (5): 189- 195.
	CHEN Jialun, JIANG Huanchun, BIAN Shaoshuai, et al. Study on operating optimization of 660 MW multi-stage heating unit combined with electric boiler[J]. Electric Power, 2022, 55 (5): 189- 195.
6	陈艺华, 张炜, 张成刚, 等. 新型电力系统中促进新能源消纳的电力现货市场交易机制研究[J]. 智慧电力, 2022, 50 (2): 97- 104. DOI
	CHEN Yihua, ZHANG Wei, ZHANG Chenggang, et al. Electricity spot market trading mechanism for promoting renewable energy integration in new power system[J]. Smart Power, 2022, 50 (2): 97- 104. DOI
7	张蓉. 新能源入市的风险应对及策略分析[J]. 中国电力企业管理, 2023, (10): 67- 69.
8	WANG Y W, SONG M H, JIA M Y, et al. Multi-objective distributionally robust optimization for hydrogen-involved total renewable energy CCHP planning under source-load uncertainties[J]. Applied Energy, 2023, 342, 121212. DOI
9	卫志农, 余爽, 孙国强, 等. 虚拟电厂的概念与发展[J]. 电力系统自动化, 2013, 37 (13): 1- 9. DOI
	WEI Zhinong, YU Shuang, SUN Guoqiang, et al. Concept and development of virtual power plant[J]. Automation of Electric Power Systems, 2013, 37 (13): 1- 9. DOI
10	国务院. 关于印发《大气污染防治行动计划》的通知(国发〔2013〕37号)[Z
11	国家能源局. 关于《完善风电供暖相关电力交易机制扩大风电供暖应用》的通知(国能发新能〔2019〕35号)[Z
12	WU S F, YAN T, KUAI Z H, et al. Preparation and thermal property analysis of a novel phase change heat storage material[J]. Renewable Energy, 2020, 150, 1057- 1065. DOI
13	尚庆晓, 孙鸣. 基于风电、储(热)供暖系统的电网优化调度研究[J]. 太阳能学报, 2021, 42 (7): 65- 70. DOI
	SHANG Qingxiao, SUN Ming. Optimal dispatching of power grid based on wind power and heat storage heating system[J]. Acta Energiae Solaris Sinica, 2021, 42 (7): 65- 70. DOI
14	许彦平, 王跃峰, 唐林, 等. 弃风供暖模式下风电接纳能力评估及效益分析[J]. 中国电力, 2017, 50 (2): 139- 143, 149. DOI
	XU Yanping, WANG Yuefeng, TANG Lin, et al. Benefit analysis and evaluation of wind power integration capability based on abandoned wind power heating mode[J]. Electric Power, 2017, 50 (2): 139- 143, 149. DOI
15	黄畅, 颜逸贤, 白尧, 等. 促进风电消纳的太阳能-燃煤热电联产系统性能研究[J]. 中国电力, 2022, 55 (5): 182- 188.
	HUANG Chang, YAN Yixian, BAI Yao, et al. Performance analysis of solar-coal cogeneration system for wind power consumption[J]. Electric Power, 2022, 55 (5): 182- 188.
16	金国锋, 邢敬舒, 张林, 等. 考虑用户舒适度的蓄热式电采暖参与风电消纳的多目标优化[J]. 电力建设, 2022, 43 (3): 12- 21.
	JIN Guofeng, XING Jingshu, ZHANG Lin, et al. Multi-objective optimization of wind power accommodation with regenerative electric heating considering user comfort[J]. Electric Power Construction, 2022, 43 (3): 12- 21.
17	崔屹峰, 李珍国, 杨金庆, 等. 考虑需求差异的户用蓄热式电采暖优化运行策略[J]. 电力系统自动化, 2021, 45 (7): 116- 122. DOI
	CUI Yifeng, LI Zhenguo, YANG Jinqing, et al. Optimal operation strategy for household electric thermal storage heating considering demand difference[J]. Automation of Electric Power Systems, 2021, 45 (7): 116- 122. DOI
18	袁桂丽, 贾新潮, 房方, 等. 虚拟电厂源荷双侧热电联合随机优化调度[J]. 电网技术, 2020, 44 (8): 2932- 2940. DOI
	YUAN Guili, JIA Xinchao, FANG Fang, et al. Joint stochastic optimal scheduling of heat and power considering source and load sides of virtual power plant[J]. Power System Technology, 2020, 44 (8): 2932- 2940. DOI
19	张立辉, 辛禾, 李秋燕, 等. 考虑需求响应的风光燃储集成虚拟电厂双层随机调度优化模型[J]. 可再生能源, 2017, 35 (10): 1514- 1522. DOI
	ZHANG Lihui, XIN He, LI Qiuyan, et al. A bi-level stochastic scheduling optimization model for virtual power plant connecting with wind-photovoltaic-gas-energy storage system with considering uncertainty and demand response[J]. Renewable Energy Resources, 2017, 35 (10): 1514- 1522. DOI
20	KILKKI O, ALAHÄIVÄLÄ A, SEILONEN I. Optimized control of price-based demand response with electric storage space heating[J]. IEEE Transactions on Industrial Informatics, 2015, 11 (1): 281- 288. DOI
21	杨玉龙, 王彤, 赵磊洋, 等. 分布式电采暖负荷群建模及备用优化[J]. 电测与仪表, 2020, 57 (2): 81- 87. DOI
	YANG Yulong, WANG Tong, ZHAO Leiyang, et al. Distributed electric heating load group modeling and standby optimization[J]. Electrical Measurement & Instrumentation, 2020, 57 (2): 81- 87. DOI
22	孙鹏, 滕云, 冷欧阳, 等. 考虑供热系统多重热惯性的电热联合系统协调优化[J]. 中国电机工程学报, 2020, 40 (19): 6059- 6071. DOI
	SUN Peng, TENG Yun, LENG Ouyang, et al. Coordinated optimization of combined heat and power systems considering multiple thermal inertia of heating system[J]. Proceedings of the CSEE, 2020, 40 (19): 6059- 6071. DOI
23	王华昕, 张高丽, 刘隽, 等. 计及用户贡献度的电动汽车主从博弈差异化充电套餐设计[J]. 电力自动化设备, 2022, 42 (10): 21- 29.
	WANG Huaxin, ZHANG Gaoli, LIU Jun, et al. Design of differentiated charging package for electric vehicle based on Stackelberg game considering user contribution[J]. Electric Power Automation Equipment, 2022, 42 (10): 21- 29.
24	刘思强, 叶泽, 姚军, 等. 负荷价格弹性的季节特性及尖峰电价政策福利效应估算[J]. 中国电力, 2016, 49 (10): 165- 170. DOI
	LIU Siqiang, YE Ze, YAO Jun, et al. Seasonal characteristics of load price elasticity and estimation of the welfare effects of peak price policy[J]. Electric Power, 2016, 49 (10): 165- 170. DOI

[1]	李明冰, 李强, 管西洋, 周皓阳, 卢瑞, 冯延坤. 市场环境下考虑多元用户侧资源协同的虚拟电厂低碳优化调度[J]. 中国电力, 2025, 58(2): 66-76.
[2]	杨珂, 王栋, 李达, 张王俊, 向尕, 李军. 虚拟电厂网络安全风险评估指标体系构建及量化计算[J]. 中国电力, 2024, 57(8): 130-137.
[3]	唐文升, 王阳, 张煜, 刘席洋, 谭清坤, 吴鹏, 陈宋宋, 杨菁. 基于多维价格弹性系数的分时电价对负荷特性影响机理[J]. 中国电力, 2024, 57(2): 202-211.
[4]	仪忠凯, 侯朗博, 徐英, 吴永峰, 李志民, 吴俊飞, 冯腾, 韩柳. 市场环境下灵活性资源虚拟电厂聚合调控关键技术综述[J]. 中国电力, 2024, 57(12): 82-96.
[5]	李骏龙, 尤培培, 张超, 方鲁睿, 张文哲. 基于双重差分模型的分时电价机制对用电成本的影响分析[J]. 中国电力, 2024, 57(11): 173-182.
[6]	宋天琦, 吕志鹏, 宋振浩, 马韵婷, 张智慧, 周珊, 李昊. 虚拟电厂规模化灵活资源聚合调控框架研究与思考[J]. 中国电力, 2024, 57(1): 2-8.
[7]	周颖, 白雪峰, 王阳, 邱敏, 孙冲, 武亚杰, 李彬. 面向虚拟电厂运营的温度敏感负荷分析与演变趋势研判[J]. 中国电力, 2024, 57(1): 9-17.
[8]	朱睿, 欧乙丁, 李筱天, 雷星雨, 周宇晴, 张珀扬, 欧睿. 基于外特性等值的虚拟电厂灵活性资源价值评估[J]. 中国电力, 2024, 57(1): 30-39.
[9]	谢蒙飞, 马高权, 刘斌, 潘振宁, 商云峰. 基于信息差距决策理论的虚拟电厂报价策略[J]. 中国电力, 2024, 57(1): 40-50.
[10]	周挺, 谭玉东, 孙晋, 文明, 廖菁, 李杨, 刘巩, 刘敦楠. 虚拟电厂参与能量与辅助服务市场的协同优化策略[J]. 中国电力, 2024, 57(1): 61-70.
[11]	张书涵, 艾芊, 李晓露, 王帝. 适用于多虚拟电厂交易的改进拜占庭容错算法共识机制[J]. 中国电力, 2024, 57(1): 71-81, 157.
[12]	张颖, 文艳, 季宇, 左娟, 王文博. 基于目标级联法的虚拟电厂日前调频容量计算方法[J]. 中国电力, 2024, 57(1): 82-90.
[13]	张超, 赵冬梅, 季宇, 张颖. 基于改进深度Q网络的虚拟电厂实时优化调度[J]. 中国电力, 2024, 57(1): 91-100.
[14]	王世杰, 冯天波, 孙宁, 何可, 李嘉文, 杨程, 崔昊杨. 考虑电-气-热耦合和需求响应的虚拟电厂优化调度策略[J]. 中国电力, 2024, 57(1): 101-114.
[15]	王臻, 刘东, 徐重酉, 翁嘉明, 陈飞. 新型电力系统多源异构数据融合技术研究现状及展望[J]. 中国电力, 2023, 56(4): 1-15.

基于风电分时电价的虚拟电厂参与清洁供暖运营优化方法

Operation Optimization Method for Virtual Power Plant Participating in Clean Heating Based on Time-of-Use Tariff of Wind Power

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 24

相关文章 15

编辑推荐

Metrics

模态框（Modal）标题

基于风电分时电价的虚拟电厂参与清洁供暖运营优化方法

Operation Optimization Method for Virtual Power Plant Participating in Clean Heating Based on Time-of-Use Tariff of Wind Power

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 24

相关文章 15

编辑推荐

Metrics