考虑用户满意度和热惯性的综合能源系统容量配置优化

doi:10.16180/j.cnki.issn1007-7820.2025.08.005

摘要/Abstract

摘要：

综合能源系统作为能源领域的新兴研究方向,在推动可再生能源利用和应对环境挑战中具有重要作用。需求响应作为其核心组成部分,旨在提升可再生能源的使用效率和系统可持续性。用户参与程度的不同限制了需求响应的潜力,因此在需求响应计划评估中考虑需用户满意度。文中提出了一种考虑用户满意度和热惯性的综合能源系统两阶段容量优化配置方法来进行长时间尺度规划。在第一阶段,通过最小化年度总成本确定设备容量配置,解决系统内负荷协调和互补问题。在第二阶段进一步精细调整,引入系统热惯性和用户满意度模型来改变室内供暖,调整设备输出和负荷曲线,实现经济和环境目标双重优化。研究结果表明,所提方法优化了综合能源系统调度,在有效缓解环境问题的同时提高了可再生能源的消纳能力。

关键词: 综合能源系统, 需求响应, 用户满意度, 热惯性, 容量优化配置, 可再生能源消纳, 两阶段, 时间尺度

Abstract:

As an emerging research direction in the field of energy, integrated energy system plays an important role in promoting the utilization of renewable energy and coping with environmental challenges. Demand response, as its core component, aims to improve the efficiency of renewable energy use and system sustainability. Different levels of user participation limit the potential of demand response, so user satisfaction should be considered in the evaluation of demand response plan. In this study, a two-stage capacity optimization configuration method of integrated energy system considering user satisfaction and thermal inertia is proposed to carry out long-term scale planning. In the first stage, the equipment capacity configuration is determined by minimizing the annual assembly cost, and the load coordination and complementarity problem in the system is solved. In the second stage, the system heat and user satisfaction model are introduced to change the indoor heating, adjust the equipment output and load curve, and realize the dual optimization of economic and environmental objectives. The research results show that the proposed method optimizes the integrated energy system scheduling, effectively alleviates environmental problems and improves the absorption capacity of renewable energy.

Key words: integrated energy system, demand response, user satisfaction, thermal inertia, capacity optimization configuration, renewable energy consumption, two-stage, time scale

中图分类号:

TK01

黎舜瑀, 叶永春, 何宇, 张靖. 考虑用户满意度和热惯性的综合能源系统容量配置优化[J]. 电子科技, 2025, 38(8): 33-41.

LI Shunyu, YE Yongchun, HE Yu, ZHANG Jing. Optimization of Capacity Allocation of Integrated Energy System Considering User Satisfaction and Thermal Inertia[J]. Electronic Science and Technology, 2025, 38(8): 33-41.

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参考文献 20

[1]	贾宏杰, 王丹, 徐宪东, 等. 区域综合能源系统若干问题研究[J]. 电力系统自动化, 2015, 39(7):198-207.
	Jia Hongjie, Wang Dan, Xu Xiandong, et al. Research on some key problems related to integrated energy systems[J]. Automation of Electric Power Systems, 2015, 39(7):198-207.
[2]	刘金芝, 张会林, 马立新, 等. 考虑可平移负荷的综合能源系统动态优化调度策略[J]. 电子科技, 2023, 36(4):78-83.
	Liu Jinzhi, Zhang Huilin, Ma Lixin, et al. Dynamic optimal scheduling strategy for integrated energy systems considering shiftable loads[J]. Electronic Science and Technology, 2023, 36(4):78-83.
[3]	郭尊, 李庚银, 周明, 等. 考虑网络约束和源荷不确定性的区域综合能源系统两阶段鲁棒优化调度[J]. 电网技术, 2019, 43(9):3090-3100.
	Guo Zun, Li Gengyin, Zhou Ming, et al. Two-stage robust optimal scheduling of regional integrated energy system considering network constraints and uncertainties in source and load[J]. Power System Technology, 2019, 43(9):3090-3100.
[4]	张沈习, 王丹阳, 程浩忠, 等. 双碳目标下低碳综合能源系统规划关键技术及挑战[J]. 电力系统自动化, 2022, 46(8):189-207.
	Zhang Shenxi, Wang Danyang, Cheng Haozhong, et al. Key technologies and challenges of low-carbon integrated energy system planning for carbon emission peak and carbon neutrality[J]. Automation of Electric Power Systems, 2022, 46(8):189-207.
[5]	Wu Z C, Qian W X, Ji Z Y. A demand response transaction method for integrated energy systems with a trigonometric membership function-based uncertainty model of costumers' responsive behaviors[J]. Sustainability, 2022, 14(24):16472-16473.
[6]	Gao H J, Zhao Y B, He S J, et al. Demand response management of community integrated energy system:A multi-energy retail package perspective[J]. Applied Energy, 2023, 330(1):120278-120279.
[7]	Ma K, Zhang R C, Yang J, et al. Collaborative optimization scheduling of integrated energy system considering user dissatisfaction[J]. Energy, 2023, 274(5):2217-2220.
[8]	Liu R H, Yang T, Sun G P, et al. Optimal dispatch of community integrated energy system considering comprehensive user satisfaction method[J]. IEEE Transactions on Electrical and Electronic Engineering, 2022, 17(11):1580-1589.
[9]	周任军, 吴燕榕, 潘轩, 等. 考虑电热需求响应的区域综合能源系统储能容量优化配置[J]. 电力科学与技术学报, 2023, 38(1):11-17.
	Zhou Renjun, Wu Yanrong, Pan Xuan, et al. Optimal placement of energy storage in a regional integrated energy system considering electric and thermal demand response[J]. Journal of Electric Power Science and Technology, 2023, 38(1):11-17.
[10]	姚志力, 王志新. 计及风光不确定性的综合能源系统两层级协同优化配置方法[J]. 电网技术, 2020, 44(12):4521-4531.
	Yao Zhili, Wang Zhixin. Two-level collaborative optimal allocation method of integrated energy system considering wind and solar uncertainty[J]. Power System Technology, 2020, 44(12):4521-4531.
[11]	栗然, 孙帆, 刘会兰, 等. 考虑能量特性差异的用户级综合能源系统混合时间尺度经济调度[J]. 电网技术, 2020, 44(10):3615-3624.
	Li Ran, Sun Fan, Liu Huilan, et al. Economic dispatch with hybrid time-scale of user-level integrated energy system considering differences in energy characteristics[J]. Power System Technology, 2020, 44(10):3615-3624.
[12]	左逢源, 张玉琼, 赵强, 等. 计及源荷不确定性的综合能源生产单元运行调度与容量配置两阶段随机优化[J]. 中国电机工程学报, 2022, 42(22):8205-8215.
	Zuo Fengyuan, Zhang Yuqiong, Zhao Qiang, et al. Two-stage stochastic optimization for operation scheduling and capacity allocation of integrated energy production unit considering supply and demand uncertainty[J]. Proceedings of the CSEE, 2022, 42(22):8205-8215.
[13]	马一鸣, 周夕然, 董鹤楠, 等. 考虑电转气与冷热负荷惯性的综合能源系统优化调度[J]. 电网与清洁能源, 2021, 37(8):118-127,138.
	Ma Yiming, Zhou Xiran, Dong Henan, et al. Optimal dispatch of integrated energy system considering power-to-gas and load inertia[J]. Power System and Clean Energy, 2021, 37(8):118-127,138.
[14]	黄易君成, 王志强, 刘文霞, 等. 基于个体时空行为模拟的区域电供暖负荷特性建模[J]. 电力系统自动化, 2022, 46(11):85-93.
	Huang Yijuncheng, Wang Zhiqiang, Liu Wenxia, et al. Individual spatial-temporal behavior simulation[J]. Automation of Electric Power Systems, 2022, 46(11):85-93.
[15]	孙鹏, 滕云, 回茜, 等. 考虑热惯性不确定性的多能源系统两阶段鲁棒优化调度模型[J]. 中国电机工程学报, 2021, 41(21):7249-7261.
	Sun Peng, Teng Yun, Hui Qian, et al. Two-stage robust optimal scheduling model for multi-energy systems considering thermal inertia uncertainty[J]. Proceedings of the CSEE, 2021, 41(21):7249-7261.
[16]	Lin F, Yi J. Optimal operation of a CHP plant for space heating as a peak load regulating plant[J]. Energy, 2000, 25(3):283-298.
[17]	邹云阳, 杨莉, 李佳勇, 等. 冷热电气多能互补的微能源网鲁棒优化调度[J]. 电力系统自动化, 2019, 43(14):65-72.
	Zou Yunyang, Yang Li, Li Jiayong, et al. Robust optimal dispatch of micro-energy grid with multi-energy complementation of cooling heating power and natural gas[J]. Automation of Electric Power Systems, 2019, 43(14):65-72.
[18]	张帅, 刘文霞, 张艺伟, 等. 计及多重热惯性特征的区域综合能源系统可靠性评估[J]. 电工技术学报, 2023, 38(12):3289-3305.
	Zhang Shuai, Liu Wenxia, Zhang Yiwei, et al. Reliability assessment of regional integrated energy system considering with multiple thermal inertia characteristics[J]. Transactions of China Electrotechnical Society, 2023, 38(12):3289-3305.
[19]	Zhang S, He W P, Chen D K, et al. Thermal comfort analysis based on PMV/PPD in cabins of manned submersibles[J]. Building and Environment, 2019, 148(1):668-676.
[20]	Li X Y, Yao R M, Liu M, et al. Developing urban residential reference buildings using clustering analysis of satellite images[J]. Energy and Bulidings, 2018, 169(6):417-429.

PMV		舒适度
-3	寒冷
-2	凉
-1	微冷
0	适中
1	稍暖
2	温暖
3	炎热

符号	数值
X/W·m^-2	75
Y/W·m^-2	0
P_a/Pa	2 500
S_cl	1.25
h_c/W·(m²·K)^-1	4.80
T_cl/℃	28
T_r/℃	26.70

j	α_j	β_j	γ_j	θ_j	φ_j	ω_j
0	-	0.223 0	0.325 6	-	-	-
1	0.572 0	-0.024 3	-0.316 8	0.699 1	0.100 1	0.199 8
2	0.060 5	-0.010 4	0.174 1	-	-	-
0	-	0.223 0	0.325 6	-	-	-

设备名称	年限/年	投资/元·kW^-1	容量限值/kW
光伏发电装置	15	2 000	2 000
蓄电池	10	1 000	650
燃气轮机	15	1 000	1 650
燃气锅炉	15	550	1 200
电锅炉	15	350	550
余热锅炉	10	730	1 500
储热装置	10	505	770
吸收式制冷机	15	870	750
电制冷机	10	670	630

类型	起止时间/h	购价/元·(kW·h)^-1
峰时段	07:00~12:00,19:00~22:00	1.21
平时段	13:00~18:00	0.73
谷时段	23:00~06:00	0.45