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| Resilience Assessment and Enhancement Methods for Urban Energy System Considering Electricity-Gas-Heat-Transport Interdependency |
| Tao Ran1, Zhao Dongmei1, Xu Chenyu1, Lin Chujie1, Xia Xuan2 |
1. School of Electrical & Electronic Engineering North China Electric Power University Beijing 102206 China;
2. State Grid Shaoxing Power Supply Company Shaoxing 312000 China |
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Abstract With the rapid changes in the global environment, high-impact and low-probability （HILP） events, represented by natural disasters, have attracted widespread attention. In the face of HILP events, the urban energy system (UES) may suffer more significant losses due to the complex interdependencies between the energy subsystems. Due to the geographical location of the access nodes of the coupling elements, the effects of extreme events on the subsystems may not be simultaneous or of equal severity. As a result, there may be "time differences" and "spatial differences" in the impact of extreme events between subsystems. With this characteristic, the interdependence of the subsystems in the UES can have a “positive” and “negative” impact on system performance. On the one hand, the effects of inadequate power supply propagate through the coupling elements to the other subsystems, resulting in a degradation of their performance. The degradation of the performance of each subsystem will in turn lead to a further undersupply of the urban distribution network through the coupling elements, exacerbating the deterioration of the UES performance. On the other hand, when one form of energy supply is lost, other forms of energy can be substituted and complemented by energy conversion equipment, supporting the performance of the UES.
To address this issue, this paper proposes a resilience assessment and enhancement method for UESs that considers the interdependence of electricity-gas-heat-transport. Firstly, the multidimensional resilience assessment metrics that include both holistic and targeted perspectives are proposed for the whole process of extreme events. Then, the models of electricity, gas, heat and transport subsystems and coupling elements are established. The resilience assessment assesses the resilience of the UES in 2 areas and 7 dimensions. It includes both an overall grasp of UES resilience (performance maintenance, resistance, responsiveness, resilience) and a targeted assessment of system performance of particular concern (island connectivity, number of islands covered by power supply, critical load maintenance time). In terms of resilience enhancement, this paper aims to minimise the sum of weighted electrical, gas and thermal load losses and develop a system-level co-optimisation model. The resilience enhancement of the UES is achieved using power generator scheduling, maintenance staff scheduling, topology reconfiguration, and building thermal inertia. Due to the reliance on the traffic network in the resilience enhancement measures taken, the transport network subsystem is considered in this paper to establish a model for mobile emergency generators routing and repair crews dispatching. Finally, case studies are analysed in a 92-node integrated electricity-gas-heat-transport system.
The following conclusions can be drawn from the simulation analysis: (1) A comprehensive study of UES resilience assessment and enhancement can consider the correlation between each resilience enhancement measure and each resilience assessment metric, which is conducive to decision-makers to avoid risks better and take advantage of multi-energy integration to achieve system resilience enhancement. (2) The proposed resilience assessment index assesses the system performance at different stages from two perspectives: holistic and targeted. The multidimensional resilience assessment metrics provide a comprehensive picture of system performance in terms of its characteristics and topological features, allowing more targeted solutions and countermeasures to be developed. (3) The proposed resilience enhancement method achieves effective coordination and synergistic optimisation of various subsystems and measures; enhances the resilience of the UES to extreme events; improves the coverage of energy supply; and facilitates the rapid recovery of the UES after HILP events.
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Received: 03 August 2022
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[1] 张儒峰, 李雪, 姜涛, 等. 城市综合能源系统韧性评估与提升综述[J]. 全球能源互联网, 2021, 4(2): 122-132.
Zhang Rufeng, Li Xue, Jiang Tao, et al.Review on resilience assessment and enhancement of urban integrated energy system[J]. Journal of Global Energy Interconnection, 2021, 4(2): 122-132.
[2] 贾宏杰, 穆云飞, 侯恺, 等. 能源转型视角下城市能源系统的形态演化及运行调控[J]. 电力系统自动化, 2021, 45(16): 49-62.
Jia Hongjie, Mu Yunfei, Hou Kai, et al.Morphology evolution and operation regulation of urban energy system from perspective of energy transition[J]. Automation of Electric Power Systems, 2021, 45(16): 49-62.
[3] 阮前途, 谢伟, 许寅, 等. 韧性电网的概念与关键特征[J]. 中国电机工程学报, 2020, 40(21): 6773-6784.
Ruan Qiantu, Xie Wei, Xu Yin, et al.Concept and key features of resilient power grids[J]. Proceedings of the CSEE, 2020, 40(21): 6773-6784.
[4] 周晓敏, 葛少云, 李腾, 等. 极端天气条件下的配电网韧性分析方法及提升措施研究[J]. 中国电机工程学报, 2018, 38(2): 505-513, 681.
Zhou Xiaomin, Ge Shaoyun, Li Teng, et al.Assessing and boosting resilience of distribution system under extreme weather[J]. Proceedings of the CSEE, 2018, 38(2): 505-513, 681.
[5] Gautam P, Piya P, Karki R.Resilience assessment of distribution systems integrated with distributed energy resources[J]. IEEE Transactions on Sustainable Energy, 2021, 12(1): 338-348.
[6] 王守相, 黄仁山, 潘志新, 等. 极端冰雪天气下配电网弹性恢复力指标的构建及评估方法[J]. 高电压技术, 2020, 46(1): 123-132.
Wang Shouxiang, Huang Renshan, Pan Zhixin, et al.Construction and evaluation of resilience restoration capability indices for distribution network under extreme ice and snow weather[J]. High Voltage Engineering, 2020, 46(1): 123-132.
[7] 别朝红, 林超凡, 李更丰, 等. 能源转型下弹性电力系统的发展与展望[J]. 中国电机工程学报, 2020, 40(9): 2735-2745.
Bie Zhaohong, Lin Chaofan, Li Gengfeng, et al.Development and prospect of resilient power system in the context of energy transition[J]. Proceedings of the CSEE, 2020, 40(9): 2735-2745.
[8] Salimi M, Nasr M A, Hosseinian S H, et al.Information gap decision theory-based active distribution system planning for resilience enhancement[J]. IEEE Transactions on Smart Grid, 2020, 11(5): 4390-4402.
[9] 卞艺衡, 别朝红. 面向弹性提升的智能配电网远动开关优化配置模型[J]. 电力系统自动化, 2021, 45(3): 33-39.
Bian Yiheng, Bie Zhaohong.Resilience-enhanced optimal placement model of remote-controlled switch for smart distribution network[J]. Automation of Electric Power Systems, 2021, 45(3): 33-39.
[10] Yan Mingyu, Shahidehpour M, Paaso A, et al.Distribution system resilience in ice storms by optimal routing of mobile devices on congested roads[J]. IEEE Transactions on Smart Grid, 2021, 12(2): 1314-1328.
[11] Lei Shunbo, Chen Chen, Li Yupeng, et al.Resilient disaster recovery logistics of distribution systems: Co-optimize service restoration with repair crew and mobile power source dispatch[J]. IEEE Transactions on Smart Grid, 2019, 10(6): 6187-6202.
[12] 彭寒梅, 李才宝, 刘健锋, 等. 基于异质依存网络的电-气区域综合能源系统弹性评估[J]. 电网技术, 2021, 45(7): 2811-2821.
Peng Hanmei, Li Caibao, Liu Jianfeng, et al.Resilience assessment of electricity-gas regional integrated energy system based on heterogeneous interdependent network[J]. Power System Technology, 2021, 45(7): 2811-2821.
[13] Zhang Huajun, Wang Peng, Yao Shuhan, et al.Resilience assessment of interdependent energy systems under hurricanes[J]. IEEE Transactions on Power Systems, 2020, 35(5): 3682-3694.
[14] 张亚超, 易杨, 胡志鹏, 等. 基于分布鲁棒优化的电-气综合能源系统弹性提升策略[J]. 电力系统自动化, 2021, 45(13): 76-84.
Zhang Yachao, Yi Yang, Hu Zhipeng, et al.Resilience enhancement strategy of electricity-gas integrated energy system based on distributionally robust optimization[J]. Automation of Electric Power Systems, 2021, 45(13): 76-84.
[15] 陈厚合, 丛前, 姜涛, 等. 多能协同的配电网供电恢复策略[J]. 电工技术学报, 2022, 37(3): 610-622, 685.
Chen Houhe, Cong Qian, Jiang Tao, et al.Distribution systems restoration with multi-energy synergy[J]. Transactions of China Electrotechnical Society, 2022, 37(3): 610-622, 685.
[16] Li Jiaxu, Xu Yin, Wang Ying, et al.Resilience-motivated distribution system restoration considering electricity-water-gas interdependency[J]. IEEE Transactions on Smart Grid, 2021, 12(6): 4799-4812.
[17] 许寅, 和敬涵, 王颖, 等. 韧性背景下的配网故障恢复研究综述及展望[J]. 电工技术学报, 2019, 34(16): 3416-3429.
Xu Yin, He Jinghan, Wang Ying, et al.A review on distribution system restoration for resilience enhancement[J]. Transactions of China Electrotechnical Society, 2019, 34(16): 3416-3429.
[18] 徐玉琴, 方楠. 基于分段线性化与改进二阶锥松弛的电-气互联系统多目标优化调度[J]. 电工技术学报, 2022, 37(11): 2800-2812.
Xu Yuqin, Fang Nan.Multi objective optimal scheduling of integrated electricity-gas system based on piecewise linearization and improved second order cone relaxation[J]. Transactions of China Electrotechnical Society, 2022, 37(11): 2800-2812.
[19] Correa-Posada C M, Sánchez-Martín P. Integrated power and natural gas model for energy adequacy in short-term operation[J]. IEEE Transactions on Power Systems, 2015, 30(6): 3347-3355.
[20] Gu Wei, Wang Jun, Lu Shuai, et al.Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings[J]. Applied Energy, 2017, 199: 234-246.
[21] 张亚超, 郑峰, 舒胜文, 等. 考虑多重不确定性的电-气-交通网络耦合系统数据驱动鲁棒优化调度[J]. 中国电机工程学报, 2021, 41(13): 4450-4462.
Zhang Yachao, Zheng Feng, Shu Shengwen, et al.A data-driven robust optimization scheduling of coupled electricity-gas-transportation systems considering multiple uncertainties[J]. Proceedings of the CSEE, 2021, 41(13): 4450-4462.
[22] 张津珲, 王旭, 蒋传文, 等. 计及交通流量不确定性的多网耦合综合能源系统优化调度方法[J]. 电网技术, 2019, 43(9): 3081-3093.
Zhang Jinhui, Wang Xu, Jiang Chuanwen, et al.Optimal scheduling method of multi-network regional integrated energy system based on traffic flow uncertainty[J]. Power System Technology, 2019, 43(9): 3081-3093.
[23] Wang Xu, Shahidehpour M, Jiang Chuanwen, et al.Resilience enhancement strategies for power distribution network coupled with urban transportation system[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 4068-4079.
[24] 麻秀范, 丁宁, 李龙. 配电网重构中网络辐射形与连通性的判断[J]. 电工技术学报, 2014, 29(8): 289-293.
Ma Xiufan, Ding Ning, Li Long.Judging radial and connectivity of network in distribution networks reconfiguration[J]. Transactions of China Electrotechnical Society, 2014, 29(8): 289-293.
[25] Ma Shanshan, Chen Bokan, Wang Zhaoyu.Resilience enhancement strategy for distribution systems under extreme weather events[J]. IEEE Transactions on Smart Grid, 2018, 9(2): 1442-1451. |
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2023, Vol. 38 
