基于用户分类的综合能源系统低碳运行策略

doi:10.16183/j.cnki.jsjtu.2022.321

摘要/Abstract

摘要：

综合能源系统 (IES) 是实现“双碳”目标的重要手段,然而系统内部不同类型用户用能行为各异,使得IES协调优化与低碳运行难度增加.为了充分发挥用户的主观能动性,基于用户行为分析对IES的用户行为进行建模,并通过卷积神经网络将用户分为激进型和保守型.构建IES运营商决策模型,确定电热能源的供应方式,针对不用类型用户设计相应的能源套餐.基于实际数据分析上述模型和方法的有效性,验证了用户分类在IES低碳运行中的价值.

关键词: 用户分类, 用户行为, 综合能源系统, 低碳运行

Abstract:

Integrated energy system (IES) is an important means to achieve the goal of “carbon peaking and carbon neutrality”. However, different types of users in the system have different energy consumption behaviors, which makes the coordinated optimization and low-carbon operation of the integrated energy system more difficult. In order to give full play to the subjective initiative of users, the user behavior of the integrated energy system is modelled based on user behavior analysis, and users are classified into aggressive and conservative types by convolutional neural network (CNN). Then, the decision model of integrated energy system operator is constructed to determine the supply mode of electric heating energy, and the corresponding energy package is designed for different types of users. Finally, the effectiveness of the above models and methods is analyzed based on actual data, and the value of user classification in low-carbon operation of integrated energy systems is verified.

Key words: user classification, user behavior, integrated energy system (IES), low-carbon operation

中图分类号:

TM732

张春雁, 窦真兰, 白冰青, 王玲玲, 蒋传文, 熊展. 基于用户分类的综合能源系统低碳运行策略[J]. 上海交通大学学报, 2024, 58(1): 1-10.

ZHANG Chunyan, DOU Zhenlan, BAI Bingqing, WANG Lingling, JIANG Chuanwen, XIONG Zhan. Low-Carbon Operation Strategy of Integrated Energy System Based on User Classification[J]. Journal of Shanghai Jiao Tong University, 2024, 58(1): 1-10.

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参考文献 25

[1]	李晖, 刘栋, 姚丹阳. 面向碳达峰碳中和目标的我国电力系统发展研判[J]. 中国电机工程学报, 2021, 41(18): 6245-6259.
	LI Hui, LIU Dong, YAO Danyang. Analysis and reflection on the development of power system towards the goal of carbon emission peak and carbon neutrality[J]. Proceedings of the CSEE, 2021, 41(18): 6245-6259.
[2]	黄强, 郭怿, 江建华, 等. “双碳”目标下中国清洁电力发展路径[J]. 上海交通大学学报, 2021, 55(12): 1499-1509.
	HUANG Qiang, GUO Yi, JIANG Jianhua, et al. Development pathway of China’s clean electricity under carbon peaking and carbon neutrality goals[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1499-1509.
[3]	卫志农, 张思德, 孙国强, 等. 基于碳交易机制的电-气互联综合能源系统低碳经济运行[J]. 电力系统自动化, 2016, 40(15): 9-16.
	WEI Zhinong, ZHANG Side, SUN Guoqiang, et al. Carbon trading based low-carbon economic operation for integrated electricity and natural gas energy system[J]. Automation of Electric Power Systems, 2016, 40(15): 9-16.
[4]	刘哲远, 邢海军, 程浩忠, 等. 考虑碳排放流及需求响应的综合能源系统双层优化调度[J]. 高电压技术, 2023, 49(1): 169-178.
	LIU Zheyuan, XING Haijun, CHENG Haozhong, et al. Bi-level optimal scheduling of comprehensive energy system considering carbon emission flow and demand response[J]. High Voltage Engineering, 2023, 49(1): 169-178.
[5]	王舒萍, 张沈习, 程浩忠, 等. 计及用户热舒适度的综合能源系统可靠性指标及评估方法[J]. 电力系统自动化, 2023, 47(1): 86-95.
	WANG Shuping, ZHANG Shenxi, CHENG Hao-zhong, et al. Reliability indices and evaluation method of integrated energy system considering thermal comfort level of customers[J]. Automation of Electric Power Systems, 2023, 47(1): 86-95.
[6]	曾鸣, 武赓, 李冉, 等. 能源互联网中综合需求侧响应的关键问题及展望[J]. 电网技术, 2016, 40(11): 3391-3398.
	ZENG Ming, WU Geng, LI Ran, et al. Key issues and prospects of integrated demand side response in energy Internet[J]. Power System Technology, 2016, 40(11): 3391-3398.
[7]	张钦, 王锡凡, 王建学, 等. 电力市场下需求响应研究综述[J]. 电力系统自动化, 2008, 32(3): 97-106.
	ZHANG Qin, WANG Xifan, WANG Jianxue, et al. Summary of research on demand response in electricity market[J]. Automation of Electric Power Systems, 2008, 32(3): 97-106.
[8]	KIRSCHEN D S. Demand-side view of electricity markets[J]. IEEE Transactions on Power Systems, 2003, 18(2): 520-527. doi: 10.1109/TPWRS.2003.810692 URL
[9]	SHAO C Z, DING Y, WANG J H, et al. Modeling and integration of flexible demand in heat and electricity integrated energy system[J]. IEEE Transactions on Sustainable Energy, 2018, 9(1): 361-370. doi: 10.1109/TSTE.2017.2731786 URL
[10]	赵海彭, 苗世洪, 李超, 等. 考虑冷热电需求耦合响应特性的园区综合能源系统优化运行策略研究[J]. 中国电机工程学报, 2022, 42(2): 573-588.
	ZHAO Haipeng, MIAO Shihong, LI Chao, et al. Study on optimal operation strategy of comprehensive energy system in park considering coupling response characteristics of cooling, heating and power demand[J]. Proceedings of the CSEE, 2022, 42(2): 573-588.
[11]	徐箭, 胡佳, 廖思阳, 等. 考虑网络动态特性与综合需求响应的综合能源系统协同优化[J]. 电力系统自动化, 2021, 45(12): 40-48.
	XU Jian, HU Jia, LIAO Siyang, et al. Coordinated optimization of integrated energy system considering network dynamic characteristics and integrated demand response[J]. Automation of Electric Power Systems, 2021, 45(12): 40-48.
[12]	徐业琰, 廖清芬, 刘涤尘, 等. 基于综合需求响应和博弈的区域综合能源系统多主体日内联合优化调度[J]. 电网技术, 2019, 43(7): 2506-2518.
	XU Yeyan, LIAO Qingfen, LIU Dichen, et al. Multi-player intraday optimal dispatch of integrated energy system based on integrated demand response and games[J]. Power System Technology, 2019, 43(7): 2506-2518.
[13]	窦迅, 王俊, 王湘艳, 等. 基于演化博弈的区域电-气互联综合能源系统用户需求侧响应行为分析[J]. 中国电机工程学报, 2020, 40(12): 3775-3786.
	DOU Xun, WANG Jun, WANG Xiangyan, et al. Analysis of user demand side response behavior of regional integrated power and gas energy systems based on evolutionary game[J]. Proceedings of the CSEE, 2020, 40(12): 3775-3785.
[14]	田丰, 贾燕冰, 任海泉, 等. 计及用户行为及满意度的电-气综合能源系统优化调度[J]. 电测与仪表, 2021, 58(5): 31-38.
	TIAN Feng, JIA Yanbing, REN Haiquan, et al. Optimal dispatch of electricity-gas integrated energy system considering user behavior and satisfaction[J]. Electrical Measurement & Instrumentation, 2021, 58(5): 31-38.
[15]	王琪鑫, 刘涤尘, 吴军, 等. 计及用户行为分析的多能协同综合能源系统供需双侧综合优化[J]. 电力自动化设备, 2017, 37(6): 179-185.
	WANG Qixin, LIU Dichen, WU Jun, et al. Comprehensive optimization including user behavior analysis for supply and demand sides of IES-MEC[J]. Electric Power Automation Equipment, 2017, 37(6): 179-185.
[16]	NIKNAM T, AZIZIPANAH-ABARGHOOEE R, ROOSTA A, et al. A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch[J]. Energy, 2012, 42(1): 530-545. doi: 10.1016/j.energy.2012.02.041 URL
[17]	FUMO N, MAGO P J, CHAMRA L M. Emission operational strategy for combined cooling, heating, and power systems[J]. Applied Energy, 2009, 86(11): 2344-2350. doi: 10.1016/j.apenergy.2009.03.007 URL
[18]	丁雨昊, 吕干云, 刘永卫, 等. 考虑碳排放目标约束和需求侧响应的综合能源系统日前优化调度[J]. 南方电网技术, 2022, 16(8): 1-11.
	DING Yuhao, LÜ Ganyun, LIU Yongwei, et al. Day-ahead optimal scheduling of integrated energy system considering carbon emission target constraints and demand side response[J]. Southern Power System Technology, 2022, 16(8): 1-11.
[19]	江婷, 邓晖, 陆承宇, 等. 电能量和旋转备用市场下电-热综合能源系统低碳优化运行[J]. 上海交通大学学报, 2021, 55(12): 1650-1662.
	JIANG Ting, DENG Hui, LU Chengyu, et al. Low-carbon optimal operation of an integrated electricity-heat energy system in electric energy and spinning reserve market[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1650-1662.
[20]	吕祥梅, 刘天琪, 刘绚, 等. 考虑高比例新能源消纳的多能源园区日前低碳经济调度[J]. 上海交通大学学报, 2021, 55(12): 1586-1597.
	LÜ Xiangmei, LIU Tianqi, LIU Xuan, et al. Low-carbon economic dispatch of multi-energy park considering high proportion of renewable energy[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1586-1597.
[21]	王泽森, 石岩, 唐艳梅, 等. 考虑LCA能源链与碳交易机制的综合能源系统低碳经济运行及能效分析[J]. 中国电机工程学报, 2019, 39(6): 1614-16268.
	WANG Zesen, SHI Yan, TANG Yanmei, et al. Low carbon economy operation and energy efficiency analysis of integrated energy systems considering LCA energy chain and carbon trading mechanism[J]. Proceedings of the CSEE, 2019, 39(6): 1614-1626.
[22]	理查德·格里格, 菲利普·津巴多. 心理学与生活[M]. 第17版. 北京: 人民邮电出版社, 2005.
	GERRIG Richard J, ZIMBARDO Philip G. Psychology and life[M]. 17th ed. Beijing: Posts & Telecom Press, 2005.
[23]	李幸芝, 韩蓓, 李国杰, 等. 分布式绿色能源碳交易机制及碳数据管理的挑战[J]. 上海交通大学学报, 2022, 56(8): 977-993.
	LI Xingzhi, HAN Bei, LI Guojie, et al. Challenges of distributed green energy carbon trading mechanism and carbon data management[J]. Journal of Shanghai Jiao Tong University, 2022, 56(8): 977-993.
[24]	Commission for Energy Regulation. CER smart metering project-electricity customer behavior trial, 1st edition[DB/OL]. (2009-12-31) [2022-08-08]. https://www.ucd.ie/issda/data/commissionforenergyregulationcer/.
[25]	LI R, WEI W, MEI S W, et al. Participation of an energy hub in electricity and heat distribution markets: An MPEC approach[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 3641-3653. doi: 10.1109/TSG.5165411 URL

层	输入	输出	超参数
卷积层	233×1	233×64	ReLU
卷积层	233×64	233×64	ReLU
最大池化层	77×64	77×64	3
Dropout层	64	64	0.2
全连接层	77×64	77×64	ReLU
全连接层	77×64	77×32	ReLU
平均池化层	77×32	32
Dropout层	32	32	0.5
Softmax输出层	32	2

用户类型	谷时电价	峰时电价	平时电价
保守型	0.60±0.05	1.00±0.05	0.70±0.05
过渡型	0.55±0.08	1.45±0.08	0.65±0.08
激进型	0.50±0.10	1.90±0.10	0.60±0.10

参数	取值	参数	取值
CHP机组容量/MW	2	电锅炉容量/MW	0.5
爬坡功率/(MW·h^-1)	1	转热效率	0.8
产电效率	0.3	燃气锅炉容量/MW	0.5
产热效率	1.2	产热效率	0.9
储能容量/(MW·h)	5	外购电碳排比例	0.8244
充电效率	0.95	燃气碳排比例	0.5704
放电效率	0.95	天然气价格/(元·m^-3)	2
最大充放电功率/MW	0.5	碳交易价格/(元·t^-1)	200
外购电容量/MW	3	热价/[元·(kW·h)^-1]	0.1

名称	数值/万元
名称	方案1	方案2	方案3
外购电成本	1.747	2.022	1.498
外购气成本	2.937	2.937	2.937
碳交易成本	0.510	0.593	0.439
用户购电成本	7.680	7.943	7.274
用户购热成本	1.358	1.358	1.358
运营商总收益	3.843	3.749	3.758

变化状态	电价/[元·(kW·h)^-1]			运营商收益/万元	用户购电成本/万元	用户购电量/ (MW·h^-1)
变化状态	谷时	峰时	平时	运营商收益/万元	用户购电成本/万元	用户购电量/ (MW·h^-1)
修订前	0.55	1.45	0.65	3.088	7.776	106.3
修订后	0.63	1.53	0.73	3.843	7.679	94.6