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

doi:10.11930/j.issn.1004-9649.202306102

Abstract

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

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.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202306102

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

Figures/Tables 12

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

Fig.2 Flowchart of HAC algorithm

Fig.3 Load response mechanism

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

Table 2 Regenerative electric heating equipment parameters

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

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

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

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

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

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

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

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

References 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]	WANG Jinfeng, LI Jinpeng, XU Yinliang, LIU Haitao, HE Jinxiong, XU Jianyuan. Distributed Optimization for VPP and Distribution Network Operation Considering Uncertainty and Green Certificate Market [J]. Electric Power, 2025, 58(4): 21-30, 192.
[2]	Mingbing LI, Qiang LI, Xiyang GUAN, Haoyang ZHOU, Rui LU, Yankun FENG. Market Oriented Low-Carbon Optimal Scheduling of Virtual Power Plants Considering Multiple User-Side Resources Coordination [J]. Electric Power, 2025, 58(2): 66-76.
[3]	Ke YANG, Dong WANG, Da LI, Wangjun ZHANG, Ga XIANG, Jun LI. Network Security Risk Assessment Index System and Calculation for Virtual Power Plant [J]. Electric Power, 2024, 57(8): 130-137.
[4]	Zhongkai YI, Langbo HOU, Ying XU, Yongfeng WU, Zhimin LI, Junfei WU, Teng FENG, Liu HAN. Aggregation and Operation Key Technology of Virtual Power Plant with Flexible Resources in Electricity Market Environment: Review [J]. Electric Power, 2024, 57(12): 82-96.
[5]	Ying ZHOU, Xuefeng BAI, Yang WANG, Min QIU, Chong SUN, Yajie WU, Bin LI. Analysis and Evolution Trend of Temperature-Sensitive Loads for Virtual Power Plant Operation [J]. Electric Power, 2024, 57(1): 9-17.
[6]	Tianqi SONG, Zhipeng LV, Zhenhao SONG, Yunting MA, Zhihui ZHANG, Shan ZHOU, Hao LI. Research and Thinking on the Aggregation and Dispatching Control Framework of Virtual Power Plant's Large Scale Flexible Resources [J]. Electric Power, 2024, 57(1): 2-8.
[7]	Rui ZHU, Yiding OU, Xiaotian LI, Xingyu LEI, Yuqing ZHOU, Poyang ZHANG, Rui OU. Evaluation of Virtual Power Plant Flexibility Resources Based on External Characteristic Equivalence [J]. Electric Power, 2024, 57(1): 30-39.
[8]	Mengfei XIE, Gaoquan MA, Bin LIU, Zhenning PAN, Yunfeng SHANG. Virtual Power Plant Quotation Strategy Based on Information Gap Decision Theory [J]. Electric Power, 2024, 57(1): 40-50.
[9]	Ting ZHOU, Yudong TAN, Jin SUN, Ming WEN, Jing LIAO, Yang LI, Gong LIU, Dunnan LIU. Collaborative Optimization Strategy for Virtual Power Plant Participating in Energy and Ancillary Service Market [J]. Electric Power, 2024, 57(1): 61-70.
[10]	Shuhan ZHANG, Qian AI, Xiaolu LI, Di WANG. Improved PBFT Consensus Mechanism for Multi-virtual Power Plant Transactions [J]. Electric Power, 2024, 57(1): 71-81, 157.
[11]	Ying ZHANG, Yan WEN, Yu JI, Juan ZUO, Wenbo WANG. Calculation of Day-Ahead Frequency Regulation Capacity for Virtual Power Plants Based on Analytical Target Cascading Method [J]. Electric Power, 2024, 57(1): 82-90.
[12]	Chao ZHANG, Dongmei ZHAO, Yu JI, Ying ZHANG. Real Time Optimal Dispatch of Virtual Power Plant Based on Improved Deep Q Network [J]. Electric Power, 2024, 57(1): 91-100.
[13]	Shijie WANG, Tianbo FENG, Ning SUN, Ke HE, Jiawen LI, Cheng YANG, Haoyang CUI. Optimal Scheduling Strategy for Virtual Power Plant Considering Electricity-Gas-Heat Coupling and Demand Response [J]. Electric Power, 2024, 57(1): 101-114.
[14]	WANG Zhen, LIU Dong, XU Chongyou, WENG Jiaming, CHEN Fei. Status Quo and Prospect of Multi-source Heterogeneous Data Fusion Technology for New Power System [J]. Electric Power, 2023, 56(4): 1-15.
[15]	SHI Shanshan, WEI Xinchi, ZHANG Yu, WANG Yufei, FANG Chen, WANG Haojing. Optimal Operation Strategy of Energy Storage System in Photovoltaic-Storage Charging Station Considering Multi-mode Integration [J]. Electric Power, 2023, 56(3): 144-153,161.