Robust Evaluation Method of Integrated Energy System Based on Variable Step Simulation and Improved Entropy Weight Method

doi:10.16183/j.cnki.jsjtu.2022.186

Abstract

Abstract:

As an important manifestation of the energy Internet, the integrated energy system improves the energy utilization rate. However, it also brings more risks due to the high coupling and the large difference in the response speed between the various systems. From the perspective of system security, it becomes crucial to accurately identify the weak links in the system and evaluate the robustness of the system. Therefore, a robustness evaluation method combining variable step size simulation and improved entropy weight method is proposed in the complex network environment. First, the structure of the integrated energy system is introduced and the coupling links of the system are further explained. Then, the robustness indicators including network damage degree and connectivity factor are proposed, and a variable step according to the difference of the response time of different systems is adopted. Based on the simulation results, an improved entropy weight method is proposed, and a more objective evaluation method is constructed. Finally, the superiority of the evaluation method is verified by a case study.

Key words: integrated energy system, complex network, robustness, entropy method, evaluation method

CLC Number:

TM711

FAN Hong, HE Jie, TIAN Shuxin. Robust Evaluation Method of Integrated Energy System Based on Variable Step Simulation and Improved Entropy Weight Method[J]. Journal of Shanghai Jiao Tong University, 2024, 58(1): 59-68.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Tab.1

Tab.2

Fig.4

Tab.3

Disadvantages of traditional entropy weight method

示例	熵值			熵权					$ω 2 ω 1$	$ω 3 ω 2$
示例	H₁	H₂	H₃	ω₁	ω₂		ω₃		$ω 2 ω 1$	$ω 3 ω 2$
1	0.9999	0.9998	0.9997	0.1667		0.3333		0.5000	1.9994	1.5002
2	0.999	0.998	0.997	0.1667		0.3333		0.5000	1.9994	1.5002
3	0.99	0.98	0.97	0.1667		0.3333		0.5000	1.9994	1.5002
4	0.9	0.8	0.7	0.1667		0.3333		0.5000	1.9994	1.5002

Tab.3

Fig.5

Fig.6

Fig.7

Fig.8

Tab.4

Fig.9

Tab.5

References 14

[1]	Fairley Peter. The troubled link between gas and electricity grids [News][J]. IEEE Spectrum, 2016, 53(6).
[2]	陈胜, 卫志农, 孙国强, 等. 电-气互联综合能源系统安全分析与优化控制研究综述[J]. 电力自动化设备, 2019, 39(8): 3-11.
	CHEN Sheng, WEI Zhinong, SUN Guoqiang, et al. Review on security analysis and optimal control of electricity-gas integrated energy system[J]. Electric Power Automation Equipment, 2019, 39(8): 3-11.
[3]	CHEN S, WEI Z N, SUN G Q, et al. Convex hull based robust security region for electricity-gas integrated energy systems[J]. IEEE Transactions on Power Systems, 2019, 34(3): 1740-1748. doi: 10.1109/TPWRS.59 URL
[4]	马瑞, 王大朔. 考虑天然气N-1的多能流系统静态安全耦合分析[J]. 中国电机工程学报, 2019, 39(6): 1627-1636.
	MA Rui, WANG Dashuo. Static safety coupling analysis of multi-energy flow system considering natural gas N-1[J]. Proceedings of the CSEE, 2019, 39(6): 1627-1636.
[5]	骆柏锋, 穆云飞, 赵波, 等. 基于统一潮流模型的电-气耦合综合能源系统静态灵敏度分析[J]. 电力系统自动化, 2018, 42(13): 29-35.
	LUO Bofeng, MU Yunfei, ZHAO Bo, et al. Static sensitivity analysis of integrated electricity and gas system based on unified power flow model[J]. Automation of Electric Power Systems, 2018, 42(13): 29-35.
[6]	赵莹, 李琰, 徐天奇. 基于复杂网络的电力信息相依网络鲁棒性研究[J]. 云南民族大学学报(自然科学版), 2022, 31(1): 76-80.
	ZHAO Ying, LI Yan, XU Tianqi. Research on the robustness of power information dependent networks based on complex networks[J]. Journal of Yunnan University of Nationalities (Natural Sciences Edition), 2022, 31(1): 76-80.
[7]	陈柏森, 廖清芬, 刘涤尘, 等. 区域综合能源系统的综合评估指标与方法[J]. 电力系统自动化, 2018, 42(4): 174-182.
	CHEN Baisen, LIAO Qingfen, LIU Dichen, et al. Comprehensive evaluation indices and methods for regional integrated energy system[J]. Automation of Electric Power Systems, 2018, 42(4): 174-182.
[8]	朱晔, 刘欣, 慕小斌, 等. 基于层次分析和风险熵权的多站融合综合能源系统多指标综合评估[J]. 电测与仪表, 2022, 59(4): 128-136.
	ZHU Ye, LIU Xin, MU Xiaobin, et al. Multi-index comprehensive evaluation of multi-station integrated energy system based on analytic hierarchy process and risk entropy weight[J]. Electrical Measurement & Instrumentation, 2022, 59(4): 128-136.
[9]	薛屹洵, 潘昭光, 王彬, 等. 多能流多尺度综合安全评估关键技术研发与应用[J]. 电网技术, 2021, 45(2): 437-447.
	XUE Yixun, PAN Zhaoguang, WANG Bin, et al. Security assessment module in integrated energy management system: Development and application[J]. Power System Technology, 2021, 45(2): 437-446.
[10]	刘国丹, 纪铱行, 滕润, 等. 基于熵权法的光热耦合综合能耗的百叶外遮阳控制策略[J]. 太阳能学报, 2022, 43(3): 236-241. doi: 10.19912/j.0254-0096.tynxb.2020-0706
	LIU Guodan, JI Yihang, TENG Run, et al. Control strategy of outer louver shading considering light-thermal coupling comprehensive energy consumption based on entropy weight method[J]. Acta Energiae Solaris Sinica, 2022, 43(3): 236-241. doi: 10.19912/j.0254-0096.tynxb.2020-0706
[11]	周惠成, 张改红, 王国利. 基于熵权的水库防洪调度多目标决策方法及应用[J]. 水利学报, 2007, 38(1): 100-106.
	ZHOU Huicheng, ZHANG Gaihong, WANG Guoli. Multi-objective decision making approach based on entropy weights for reservoir flood control operation[J]. Journal of Hydraulic Engineering, 2007, 38(1): 100-106.
[12]	李英海, 周建中. 基于改进熵权和Vague集的多目标防洪调度决策方法[J]. 水电能源科学, 2010, 28(6): 32-35.
	LI Yinghai, ZHOU Jianzhong. Multi-objective flood control dispatching decision method based on improved entropy weight and Vague set[J]. Water Resources and Power, 2010, 28(6): 32-35.
[13]	欧阳森, 石怡理. 改进熵权法及其在电能质量评估中的应用[J]. 电力系统自动化, 2013, 37(21): 156-159.
	OUYANG Sen, SHI Yili. A new improved entropy method and its application in power quality evaluation[J]. Automation of Electric Power Systems, 2013, 37(21): 156-159.
[14]	陈超洋, 周勇, 池明, 等. 基于复杂网络理论的大电网脆弱性研究综述[J]. 控制与决策, 2022, 37(4): 782-798.
	CHEN Chaoyang, ZHOU Yong, CHI Ming, et al. Review of large power grid vulnerability based on complex network theory[J]. Control and Decision, 2022, 37(4): 782-798.

时间常数	主导变量	故障演变过程
小于秒级	电压、电流	潮流过程
秒级~分钟级	压力、流量	水力过程
分钟级~小时级	管道温度	热力过程

模型	阶段0	阶段1	阶段2	阶段3	阶段4
潮流模型	√	√	√	√	√
气网模型	√	×	√	√	√
换热站水力模型	√	√	√	√	√
换热站热力模型	√	×	×	√	√
热负荷模型	√	×	×	×	√

节点	度值	聚合系数	节点	度值	聚合系数
6	7	0.143	39	4	0.333
9	5	0.100	40	4	0
10	6	0.133	45	4	0
24	4	0	51	3	0
25	5	0	54	2	0
35	4	0.167	58	2	0

节点	鲁棒性评分	节点	鲁棒性评分
25	0.2590	10	0.3163
40	0.2600	45	0.3215
51	0.2721	6	0.3271
9	0.2806	24	0.3415
58	0.2819	54	0.3673
39	0.2930	35	0.3900

[1]	You Minghao, Gu Jie, Liu Shuqi. Regional Integrated Energy System Resilience Enhancement Strategy at the Integrated Stage of Disaster Response and Post-Disaster Recovery [J]. J Shanghai Jiaotong Univ Sci, 2026, 31(2): 515-527.
[2]	Wu Lizhen, Zhao Yifan, Qin Wenbin, Chen Wei. Knowledge-Data Fusion Model for Multivariate Load Short-Term Forecasting of Integrated Energy System [J]. J Shanghai Jiaotong Univ Sci, 2026, 31(2): 499-514.
[3]	NI Yu, XU Yazhou, LUO Yizhe, YU Mengxin, JIN Zhao, FENG Shuo, SHI Yucheng, XU Mingliang. System Effectiveness Evaluation Method for Multi-Spacecraft Operational Systems Based on Complex Network Theory [J]. Air & Space Defense, 2026, 9(1): 132-144.
[4]	SHEN Tong, CHEN Jingxian, ZHONG Ping. Robustness of Radar Intelligent Recognition Models Under Adversarial Samples Attacks [J]. Air & Space Defense, 2026, 9(1): 46-51.
[5]	LIU Donglin, ZHOU Xia, DAI Jianfeng, XIE Xiangpeng, TANG Yi, LI Juanshi. Bi-Level Optimization Scheduling Strategy for Building Integrated Energy System Considering Virtual Energy Storage [J]. Journal of Shanghai Jiao Tong University, 2026, 60(1): 61-73.
[6]	SHEN Fu, YANG Zhiwen, XU Xiaoyuan, ZHANG Wei, WANG Zhe, CAO Yang. Unit Model of Integrated Energy System Based on Statistical Clustering [J]. Journal of Shanghai Jiao Tong University, 2025, 59(9): 1348-1358.
[7]	PENG Chuxuan, BIAN Xiaoyan, JIN Haixiang, LIN Shunfu, XU Bo, ZHAO Jian. Two-Stage Optimal Dispatch for Integrated Energy System with Oxy-Combustion Based on Multi-Energy Flexibility Constraints [J]. Journal of Shanghai Jiao Tong University, 2025, 59(9): 1281-1291.
[8]	LIN Jiayu, HAN Juntao, WANG Yongzhen, HAN Kai, HAN Yibo, LI Jian. Capacity Planning and Operational Optimization for Low-Carbon Data Center Integrated Energy System Considering Exergy Efficiency [J]. Journal of Shanghai Jiao Tong University, 2025, 59(9): 1327-1337.
[9]	FU Shenglai, CHEN Li, CHEN Ziqiang. Mode Transition Control of Parallel Gas-Electric Hybrid Power System with Uncertain Delay [J]. Journal of Shanghai Jiao Tong University, 2025, 59(9): 1225-1236.
[10]	ZHANG Chenwei, WANG Ying, LI Yaping, ZHANG Kaifeng. Optimization Model for Safeguarding Vulnerable Components in Integrated Energy Systems Based on Weighted Betweenness [J]. Journal of Shanghai Jiao Tong University, 2025, 59(7): 923-937.
[11]	DENG Qianwen, LI Qi, QIU Yibin, LI Doumeng, HUO Shasha, CHEN Weirong. Optimal Allocation Method of Integrated Energy System Considering Joint Operation of Multiple Flexible Resources [J]. Journal of Shanghai Jiao Tong University, 2025, 59(7): 912-922.
[12]	LU Bin, WANG Yixiao, PU Chuanqing, CHEN Yunhui, CHEN Bobo, FAN Feilong. Asynchronous Coordinated Control Method for Regional Multi-Agent Integrated Energy Systems Considering Voltage Deviation [J]. Journal of Shanghai Jiao Tong University, 2025, 59(6): 758-767.
[13]	HUANG Yixiang, DOU Xun, LI Linxi, YANG Hanyu, YU Jiancheng, HUO Xianxu. Quantitative Method of Response Value of Integrated Energy Equipment Based on Global Sensitivity Analysis [J]. Journal of Shanghai Jiao Tong University, 2025, 59(5): 569-579.
[14]	GAO Bo, LI Fei, SHI Lun, TAO Peng, SHI Zhengang, ZHANG Chao, PENG Jie, ZHAO Yiyi. A Low-Carbon Interactive Management Strategy for Community Integrated Energy System Based on Real-Time Carbon Intensity Assessment [J]. Journal of Shanghai Jiao Tong University, 2025, 59(5): 580-591.
[15]	ZHOU Yu, JIA Jun, LI Hao, DU Yihui, QIAO Wenyuan. Scene Generation Technology for Cognitive Deception of Intelligent Flying Vehicles [J]. Air & Space Defense, 2025, 8(4): 9-19.