Distribution System Restoration Method Considering the Function Restoration Requirements of Critical Loads

doi:10.12204/j.issn.1000-7229.2022.08.007

Abstract

Abstract:

After a major power outage, using the local distributed generators of the urban distribution system to restore critical loads is an effective method to mitigate outage and improve the resilience. The loads in urban power grid include the customer loads that can only be functioned with the joint support of various resources such as electricity, water and gas, as well as the critical infrastructure loads such as traffic lights and water pumps. Besides, there exists closed interdependency among power grid, customer loads, and critical infrastructure loads. In this paper, a multi-period restoration method for distribution system critical loads considering the load function requirements is proposed. On the load side, the power, water, and gas demand of customer loads and the power demand of traffic loads are considered. On the grid side, the operation constraints of power distribution system, water network, and gas network are considered. On the source side, the flexible access of mobile resources and limited resources of local distributed generators are considered. The results of case studies show that the proposed method can maximize the social function of various loads and realize the optimal allocation of limited generation resources.

Key words: resilience, distribution system restoration, customer function, restoration requirement

CLC Number:

TM615

LIU Jiayu, SHEN Bing, ZHOU Jian, DU Yang, FENG Yuyao, TANG Min, CHEN Yunhan, LI Jiaxu, WANG Ying. Distribution System Restoration Method Considering the Function Restoration Requirements of Critical Loads[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(8): 66-75.

Figures/Tables 11

Fig.1 The electricity-water-gas integrated system

Fig.2 Algorithm flowchart

Fig.3 Topology of electricity-water-gas integrated system

Table 1 Parameters of water pumps and gas compressors

Table 2 Parameters of DGs

Table 3 Parameters of MPSs

Fig.4 Number of restored loads

Fig.5 Distribution of electricity energy

Fig.6 Outputs of DGs and MPSs

Table 4 Result comparison for different restoration strategies

Fig.7 Comparison of the distribution of electricity for different restoration strategies

References 24

[1]	中共北京市委, 北京市人民政府. 北京城市总体规划(2016年—2035年)[Z]. 北京: 2017-9-29.
[2]	孙建平. 上海城市运行安全发展报告-2019-2020[M]. 上海: 同济大学出版社, 2021.
[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]	高鑫, 唐飞, 张童彦, 等. 配电网防风抗灾加固措施优化决策方法[J]. 发电技术, 2021, 42(1): 78-85.
	GAO Xin, TANG Fei, ZHANG Tongyan, et al. Optimal decision-making method of wind-proof and disaster-resistant reinforcement measures for distribution network[J]. Power Generation Technology, 2021, 42(1): 78-85.
[5]	马晨霄, 刘洋, 许立雄, 等. 同时考虑孤岛与重构的配电网故障恢复运行策略[J]. 电力建设, 2018, 39(8): 128-136.
	MA Chenxiao, LIU Yang, XU Lixiong, et al. Fault recovery operation strategy for distribution network coordinating islanding and reconfiguration[J]. Electric Power Construction, 2018, 39(8): 128-136.
[6]	GE Leijiao, XIAN Yiming, WANG Zhongguan, et al. Short-term load forecasting of regional distribution network based on generalized regression neural network optimized by grey wolf optimization algorithm[J]. CSEE Journal of Power and Energy Systems, 2021, 7(5): 1093-1101.
[7]	GORDO E, CAMPOS A, COELHO D. Energy efficiency in a hospital building case study: Hospitais da universidade de Coimbra[C]// Proceedings of the 2011 3rd International Youth Conference on Energetics (IYCE). Leiria, Portugal: IEEE, 2011: 1-6.
[8]	SINGH M K, KEKATOS V. Optimal scheduling of water distribution systems[J]. IEEE Transactions on Control of Network Systems, 2020, 7(2): 711-723. doi: 10.1109/TCNS.2019.2939651 URL
[9]	SINGH M K, KEKATOS V. Natural gas flow solvers using convex relaxation[J]. IEEE Transactions on Control of Network Systems, 2020, 7(3): 1283-1295. doi: 10.1109/TCNS.2020.2972593 URL
[10]	王颖, 和敬涵, 王小君, 等. 配电网多时段在线恢复决策问题的两阶段求解算法[J]. 电力系统自动化, 2021, 45(3): 121-129.
	WANG Ying, HE Jinghan, WANG Xiaojun, et al. Two-stage solving algorithm for online decision-making on multi-period distribution network restoration[J]. Automation of Electric Power Systems, 2021, 45(3): 121-129.
[11]	陈春, 吴宜桐, 李锰, 等. 基于网络拓扑有向遍历的配电网故障快速恢复方法[J]. 电力系统自动化, 2021, 45(7): 44-52.
	CHEN Chun, WU Yitong, LI Meng, et al. Method for fast recovery from distribution network fault based on directed traversal of network topology[J]. Automation of Electric Power Systems, 2021, 45(7): 44-52.
[12]	许寅, 王颖, 和敬涵, 等. 多源协同的配电网多时段负荷恢复优化决策方法[J]. 电力系统自动化, 2020, 44(2): 123-131.
	XU Yin, WANG Ying, HE Jinghan, et al. Optimal decision-making method for multi-period load restoration in distribution network with coordination of multiple sources[J]. Automation of Electric Power Systems, 2020, 44(2): 123-131.
[13]	AHMADI H, ALSUBAIE A, MARTÍ J R. Distribution system restoration considering critical infrastructures interdependencies[C]// 2014 IEEE PES General Meeting \| Conference & Exposition. National Harbor, MD, USA: IEEE, 2014: 1-5.
[14]	陈玮, 丁筱, 施云辉, 等. 考虑双向耦合的电-气综合能源系统时序故障恢复方法[J]. 电力自动化设备, 2019, 39(8): 86-94.
	CHEN Wei, DING Xiao, SHI Yunhui, et al. Sequential fault restoration method for electricity-gas integrated energy system considering two-way coupling[J]. Electric Power Automation Equipment, 2019, 39(8): 86-94.
[15]	LIN Y L, CHEN B, WANG J H, et al. A combined repair crew dispatch problem for resilient electric and natural gas system considering reconfiguration and DG islanding[J]. IEEE Transactions on Power Systems, 2019, 34(4): 2755-2767. doi: 10.1109/TPWRS.2019.2895198 URL
[16]	刘家权, 刘珅, 周金涛, 等. 基于鲁棒优化的电-气互联型主动配电网故障恢复方法[J]. 电力系统保护与控制, 2021, 49(7): 66-74.
	LIU Jiaquan, LIU Shen, ZHOU Jintao, et al. Fault recovery method of an integrated electricity and natural-gas active distribution network based on robust optimization[J]. Power System Protection and Control, 2021, 49(7): 66-74.
[17]	LV C X, YU H, LI P, et al. Coordinated operation and planning of integrated electricity and gas community energy system with enhanced operational resilience[J]. IEEE Access, 2020, 8: 59257-59277. doi: 10.1109/ACCESS.2020.2982412 URL
[18]	李穆寅, 曹志远, 李佳旭, 等. 计及供电-供水系统耦合关系的配电网故障恢复优化决策方法[J]. 电力建设, 2021, 42(3): 54-60.
	LI Muyin, CAO Zhiyuan, LI Jiaxu, et al. Optimization decision-making method for distribution system restoration considering the interdependency between power and water distribution systems[J]. Electric Power Construction, 2021, 42(3): 54-60.
[19]	ALKHALEEL B A, LIAO H T, SULLIVAN K M. Model and solution method for mean-risk cost-based post-disruption restoration of interdependent critical infrastructure networks[J]. Computers & Operations Research, 2022, 144: 105812. doi: 10.1016/j.cor.2022.105812 URL
[20]	高天乐, 李佳旭, 王颖, 等. 计及负荷侧关键基础设施耦合性的配电网恢复优化决策方法[J]. 电力建设, 2019, 40(12): 38-44.
	GAO Tianle, LI Jiaxu, WANG Ying, et al. Optimization decision-making method for distribution network restoration considering the interdependency of critical infrastructure on load side[J]. Electric Power Construction, 2019, 40(12): 38-44.
[21]	LI J X, XU Y, WANG Y, et al. Resilience-motivated distribution system restoration considering electricity-water-gas interdependency[J]. IEEE Transactions on Smart Grid, 2021, 12(6): 4799-4812. doi: 10.1109/TSG.2021.3105234 URL
[22]	SCHNEIDER K P, MATHER B A, PAL B C, et al. Analytic considerations and design basis for the IEEE distribution test feeders[J]. IEEE Transactions on Power Systems, 2018, 33(3): 3181-3188. doi: 10.1109/TPWRS.2017.2760011 URL
[23]	OIKONOMOU K, PARVANIA M. Optimal coordination of water distribution energy flexibility with power systems operation[J]. IEEE Transactions on Smart Grid, 2019, 10(1): 1101-1110. doi: 10.1109/TSG.2018.2824308 URL
[24]	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.