Reliability evaluation on an electric-gas integrated energy system considering weather influence

doi:10.3969/j.issn.2097-0706.2023.02.004

Abstract

Abstract:

The reliability evaluation for electric-gas integrated energy system（EGIES） has drawn wide attention in recent years.Since the failure rates of components under different weather conditions are different，the result of the evaluation for EGIES considering weather influence is more objective than that obtained based on the average failure rate of various components. Firstly，the test weather condition of a component in the system are clustered into the existing groups of similar weather conditions by fuzzy clustering，and the correlation degree between the test weather condition and other weather samples in the same group is calculated. Then，the failure rate of the component under the test weather condition is obtained based on its correlation degree and the historical failure rate. Finally，the reliability of the EGIES is analyzed based on the optimal load-reduction model of the system by Monte Carlo method. The calculation results show that the proposed method can effectively obtain the failure rate of a component under a certain weather condition. The influence of taking weather into consideration on the reliability of the power subsystem is more prominent than that of the nature gas subsystem，and the reliability of the power subsystem will be reduced by this influence.

Key words: weather, failure rate, electric-gas integrated energy system, reliability, fuzzy clustering

CLC Number:

TK01：TM71

KONG Zhenyu, LI Hongzhong. Reliability evaluation on an electric-gas integrated energy system considering weather influence[J]. Integrated Intelligent Energy, 2023, 45(2): 30-36.

Figures/Tables 7

Fig.1

Fig.2

Table 1

Table 2

Table 3

Table 4

Comparison of the system reliability indexes

场景	$p L O L$	$e E N S$ /（MW·h）	$p L O G L$	e_GNS/(m³·a^-1)
1	0.072 3	1 165.21	0.106 2	3 668.84
2	0.086 1	1 349.62	0.106 9	3 696.49

Table 4

Fig.3

References 23

[1]	安学民, 孙华东, 张晓涵, 等. 美国得州“2.15”停电事件分析及启示[J]. 中国电机工程学报, 2021, 41(10):3407-3415,3666.
	AN Xuemin, SUN Huadong, ZHANG Xiaohan, et al. Analysis and lessons of Texas power outage event on February 15, 2021[J]. Proceedings of the CSEE, 2021, 41(10):3407-3415,3666.
[2]	王建学, 张耀, 吴思, 等. 大规模冰灾对输电系统可靠性的影响分析[J]. 中国电机工程学报, 2011, 31(28):49-56.
	WANG Jianxue, ZHANG Yao, WU Si, et al. Influence of large-scale ice disaster on transmission system reliability[J]. Proceedings of the CSEE, 2011, 31(28):49-56.
[3]	BILLINTON R, ALLAN R N. Reliability evaluation of power systems[M]. 2nd ed. New York: Plenum Press, 1996.
[4]	BILLINTON R, ACHARYA J. Consideration of multi-state weather models in reliability evaluation of transmission and distribution systems[C]// Canadian Conference on Electrical and Computer Engineering, 2005. IEEE, 2005: 916-922.
[5]	LI W. Reliability assessment of electric power systems using Monte Carlo methods[M]. Boston: Springer Science & Business Media, 2013.
[6]	何剑, 程林, 孙元章, 等. 计及天气预测的电力系统运行可靠性短期评估[J]. 电力系统保护与控制, 2010, 38(10):31-38,51.
	HE Jian, CHENG Lin, SUN Yuanzhang, et al. Power system short-term operational reliability evaluation considering weather forecast[J]. Power System Protection and Control, 2010, 38(10):31-38,51.
[7]	王建. 输电线路气象灾害风险分析与预警方法研究[D]. 重庆: 重庆大学, 2016.
	WANG Jian. Research on meteorological disaster risk analysis and fault early warning methods for overhead transmission line[D]. Chongqing: Chongqing University, 2016.
[8]	谢云云, 薛禹胜, 文福拴, 等. 冰灾对输电线故障率影响的时空评估[J]. 电力系统自动化, 2013, 37(18):32-41,98.
	XIE Yunyun, XUE Yusheng, WEN Fushuan, et al. Space-time evaluation for impact of ice disaster on transmission line fault probability[J]. Automation of Electric Power Systems, 2013, 37(18):32-41,98.
[9]	冯伟明. 考虑冰灾的电网运行风险评估及网络化保护[D]. 哈尔滨: 哈尔滨工业大学, 2014.
	FENG Weiming. Operation risk assessment on power grid in ice storm and network protection[D]. Harbin: Harbin Institute of Technology, 2014.
[10]	WU J, SONG X, HU S, et al. Operational reliability analysis considering multi-factors in large-scale freezing weather[C]// IET International Conference on Sustainable Power Generation & Supply, 2012.
[11]	何剑, 程林, 孙元章, 等. 条件相依的输变电设备短期可靠性模型[J]. 中国电机工程学报, 2009, 29(7):39-46.
	HE Jian, CHENG Lin, SUN Yuanzhang, et al. Condition dependent short-term reliability models of transmission equipment[J]. Proceedings of the CSEE, 2009, 29(7):39-46.
[12]	QIN Z, LI W, XIONG X. Generation system reliability evaluation incorporating correlations of wind speeds with different distributions[J]. IEEE Transactions on Power Systems, 2013, 28(1):551-558. doi: 10.1109/TPWRS.2012.2205410
[13]	DEHGHANIAN P, ZHANG B, DOKIC T, et al. Predictive risk analytics for weather-resilient operation of electric power systems[J]. IEEE Transactions on Sustainable Energy, 2019, 10(1):3-15. doi: 10.1109/TSTE.2018.2825780
[14]	PANTELI M, MANCARELLA P. Modeling and evaluating the resilience of critical electrical power infrastructure to extreme weather events[J]. IEEE Systems Journal, 2015, 11(3): 1733-1742. doi: 10.1109/JSYST.2015.2389272
[15]	LI W, XIONG X, ZHOU J. Incorporating fuzzy weather-related outages in transmission system reliability assessment[J]. IET generation,transmission & distribution, 2009, 3(1): 26-37. doi: 10.1049/iet-gtd:20080187
[16]	China meteorological data service center[EB/OL].(2018-08-01)[2022-09-15]. http://data.cma.cn/en.
[17]	CHEN X, TANG J, LI W. Probabilistic operational reliability of composite power systems considering multiple meteorological factors[J]. IEEE Transactions on Power Systems, 2020, 35(1):85-97. doi: 10.1109/TPWRS.59
[18]	桑茂盛, 包铭磊, 丁一, 等. 考虑天然气网影响的电网脆弱线路辨识[J]. 电力系统自动化, 2019, 43(21):34-43.
	SANG Maosheng, BAO Minglei, DING Yi, et al. Identification of vulnerable lines in power grid considering impact of natural gas network[J]. Automation of Electric Power Systems, 2019, 43(21):34-43.
[19]	LI Q, AN S, GEDRA T W. Solving natural gas loadflow problems using electric loadflow techniques[C]// Proceedings of the North American Power Symposium. 2003: 1-7.
[20]	龚凌霄, 刘天琪, 何川, 等. 考虑综合需求响应的气电联合系统可靠性评估[J]. 电力自动化设备, 2021, 41(9):39-47.
	GONG Lingxiao, LIU Tianqi, HE Chuan, et al. Reliability evaluation of integrated electricity and natural-gas system considering integrated demand response[J]. Automation of Electric Power Systems, 2021, 41(9):39-47.
[21]	BAO M, DING Y, SINGH C, et al. A multi-state model for reliability assessment of integrated gas and power systems utilizing universal generating function techniques[J]. IEEE Transactions on Smart Grid, 2019, 10(6):6271-6283. doi: 10.1109/TSG.5165411
[22]	BILLINTON R, KUMAR S, CHOWDHURY N, et al. A reliability test system for educational purposes-basic data[J]. IEEE Transactions on Power Systems, 1989, 4(3):1238-1244. doi: 10.1109/59.32623
[23]	彭占磊, 杨之乐, 杨文强, 等. 电化学储能参与电力系统规划运行方法综述[J]. 综合智慧能源, 2022, 44(6): 37-44. doi: 10.3969/j.issn.2097-0706.2022.06.004
	PENG Zhanlei, YANG Zhile, YANG Wenqiang, et al. Review on planning and operation methods for power system with participation of electrochemical energy storage systems[J]. Integrated Intelligent Energy, 2022, 44(6): 37-44. doi: 10.3969/j.issn.2097-0706.2022.06.004

天气样本	最大风速	最高气温	平均相对湿度	降水量	线路故障率	变压器故障率
1	1.000 0	0.068 9	0.000 1	0.521 1	0.051 7	0.008 0
2	0.212 3	0.898 9	0.967 9	0.099 3	0.033 9	0.014 3
3	0.045 6	0.921 1	0.883 1	0.033 4	0.032 6	0.013 9
4	0.849 3	0.069 9	0.294 1	0.668 8	0.047 2	0.008 2
5	0.702 1	0.032 3	0.413 0	0.623 9	0.005 1	0.007 9
6	0.000 1	0.855 1	0.933 2	0.059 2	0.029 4	0.012 8
7	0.863 6	0.039 9	0.457 6	0.555 6	0.026 2	0.006 6
8	0.091 1	0.979 1	0.705 9	0.000 1	0.032 2	0.015 1

天气样本	输电线路故障率/%
天气样本	计算值	实际值	相对误差
7	2.73	2.62	4.13
8	3.17	3.22	1.41