含非故障状态下风险评价的配电网自愈性综合评价 *

doi:10.11985/2020.04.004

电气工程学报 ›› 2020, Vol. 15 ›› Issue (4): 35-44.doi: 10.11985/2020.04.004

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含非故障状态下风险评价的配电网自愈性综合评价 ^*

张籍¹(), 蔡勇²(), 桑子夏¹(), 鄢晶¹, 沈玉兰³, 陈艳波⁴

1.国网湖北省电力有限公司经济技术研究院武汉 430077
2.国网湖北省电力有限公司武汉 430077
3.江苏省电力公司扬州供电公司扬州 225000
4.华北电力大学电气与电子工程学院北京 102206

收稿日期:2020-08-19 修回日期:2020-11-13 出版日期:2020-12-25 发布日期:2020-12-25
作者简介:张籍,男,1985年生,高级工程师。主要研究方向为智能电网规划与设计。E-mail： ceeezj@qq.com
蔡勇,男,1984年生,高级工程师。主要研究方向为智能电网及环保技术。E-mail： hb_cy@qq.com
桑子夏,男,1985年生,高级工程师。主要研究方向为智能电网规划。E-mail： spadegadget@hotmail.com
基金资助:
* 国家自然科学基金(51777067);国网湖北省电力有限公司科技资助项目(52153817000X)

Comprehensive Evaluation of Self-healing Ability of Distribution Network with Risk Assessment Under Non-fault State

ZHANG Ji¹(), CAI Yong²(), SANG Zixia¹(), YAN Jing¹, SHEN Yulan³, CHEN Yanbo⁴

1. Hubei Electric Power Corporation Power Economic Research Institute, Wuhan 430077
2. Hubei Electric Power Company, SGCC, Wuhan 430077
3. Jiangsu Electric Power Company Yangzhou Power Supply Company, Yangzhou 225000
4. School of Electric and Electrical Engineering, North China Electric Power University, Beijing 102206

Received:2020-08-19 Revised:2020-11-13 Online:2020-12-25 Published:2020-12-25

摘要/Abstract

摘要：

全社会对供电可靠性的要求越来越高,这就要求配电网具有良好的自愈性。在配电网自愈性评价方面,已有研究往往忽视了对非故障状态下配电网自我消除故障隐患的评价。为全面评价配电网的自愈水平,既考虑了故障之后的配电网自愈情况,也考虑了非故障状态下的配电网风险评价。为定量评估配电网在非故障状态下面临的风险,基于风险理论提出了线路过载风险、电压越限风险以及丢失负荷风险三个定量指标;而在故障后的配电网自愈评价方面,分别从用户、电网公司和社会的需求出发提出了自愈速度、自愈率、自愈控制操作复杂度、电压/电流恢复率、切负荷率、自愈投入费用与效果比、平均停电频率以及平均停电持续时间共八个定量指标,从而构建了配电网自愈评价综合指标体系。针对以上指标体系的特点,采用基于拓展加权平均算子的改进层次分析法对配电网自愈性进行全面评价,最后通过仿真算例验证了所提方法的有效性。

关键词: 配电网, 自愈性, 非故障状态, 层次分析法, 评价

Abstract:

The whole society has higher requirements for power supply reliability, which requires the distribution network to have good self-healing properties. In terms of self-healing evaluation of distribution network, the existing researches often neglect the evaluation of the hidden trouble of self-elimination of the distribution network in the non-fault state. In order to comprehensively evaluate the self-healing level of distribution network, not only considers the self-healing situation of distribution network after fault, but also considers the risk assessment of distribution network under non fault state. In order to quantitatively evaluate the risk faced by distribution network in non fault state, based on the risk theory, three quantitative indicators are put forward: line overload risk, voltage overrun risk and load loss risk; in terms of self-healing evaluation of distribution network after fault, it puts forward self-healing speed, self-healing rate, self-healing control operation complexity, self-healing control operation complexity, self-healing rate and self-healing control operation complexity. There are eight quantitative indexes, including voltage/current recovery rate, load shedding rate, self-healing input cost to effect ratio, average outage frequency and average outage duration. According to the characteristics of the above index system, the improved analytic hierarchy process (AHP) based on the extended weighted average operator is used to comprehensively evaluate the self-healing of distribution network. Finally, a simulation example is given to verify the effectiveness of the proposed method.

Key words: Distribution network, self-healing, non-fault state, analytic hierarchy process, evaluation

中图分类号:

TM711

张籍, 蔡勇, 桑子夏, 鄢晶, 沈玉兰, 陈艳波. 含非故障状态下风险评价的配电网自愈性综合评价 ^*[J]. 电气工程学报, 2020, 15(4): 35-44.

ZHANG Ji, CAI Yong, SANG Zixia, YAN Jing, SHEN Yulan, CHEN Yanbo. Comprehensive Evaluation of Self-healing Ability of Distribution Network with Risk Assessment Under Non-fault State[J]. Journal of Electrical Engineering, 2020, 15(4): 35-44.

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参考文献 24

[1]	陈艳波, 刘洋, 张籍, 等. 基于改进SEC模型的新一代智能变电站设计方案评价[J]. 电网技术, 2017,41(4):1308-1314.
	CHEN Yanbo, LIU Yang, ZHANG Ji, et al. Evaluation of a new generation intelligent substation design based on improved SEC model[J]. Power Grid Technology, 2017,41(4):1308-1314.
[2]	ZHANG Baohui, HAO Zhiguo, BO Zhiqian. New development in relay protection for smart grid[J]. Protection and Control of Modern Power Systems, 2016,1(14):1-7. doi: 10.1186/s41601-016-0016-y
[3]	SHEN Yulan, CHEN Yanbo, ZHANG Ji, et al. Self-healing evaluation of smart distribution network based on uncertainty theory[J]. IEEE Access, 2019,7:140022-140029. doi: 10.1109/Access.6287639
[4]	戴观权, 蔡泽祥, 蔡煜, 等. 基于动态拓扑的配电网分布式保护自愈方法[J]. 供用电, 2019(9):22-27.
	DAI Guanquan, CAI Zexiang, CAI Yu, et al. Distributed protection and self-healing method for distribution network based on dynamic topology[J]. Distribution & Utilization, 2019(9):22-27.
[5]	CHEN Yanbo, MA Jin, ZHANG Pu, et al. Robust state estimator based on maximum exponential absolute value[J]. IEEE Transactions on Smart Grid. 2017,8(4):1537-1544. doi: 10.1109/TSG.2015.2485280
[6]	CHEN Yanbo, YAO Yuan, ZHANG Ying. A Robust state estimation method based on SOCP for integrated electricity-heat system[J]. IEEE Trans. on Smart Grid. doi: 10.1109/TSG.2020.3022563.
[7]	CHEN Yanbo, YAO Yuan, LIN Yuzhang, et al. Dynamic state estimation for integrated electricity-gas systems based on Kalman filter[J]. CSEE Journal of Power and Energy Systems. doi: 10.17775/ CSEEJPES.2020.02050.4.
[8]	IBM Corporation. IBM end-to-end security for smart grids[R]. New York:IBM Corporation, 2009.
[9]	XU Yan, DONG Zhaoyang, XU Zhao, et al. An intelligent dynamic security assessment framework for power systems with wind power[J]. IEEE Transactions on Industrial Informatics, 2012,8(4):995-1003. doi: 10.1109/TII.2012.2206396
[10]	U.S. Department of Energy. Smart grid system report annex A and B[R]. New York:U.S. Department of Energy, 2009.
[11]	DAVIS K R, DAVIS C M, ZONOUZ S A, et al. A cyber-physical modeling and assessment framework for power grid infrastructures[J]. IEEE Trans. on Smart Grid, 2015,6(5):2464-2475. doi: 10.1109/TSG.5165411
[12]	European Smart Grids Technology Platform. Vision and strategy for Europe’s electricity networks of the future[R]. Brussels:European Commission, 2010.
[13]	QUEVEDO de P M, CONTRERAS J, MAZZA A, et al. Reliability assessment of microgrids with local and mobile generation, time-dependent profiles, and intraday reconfiguration[J]. IEEE Transactions on Industry Applications, 2018,54(1):61-72. doi: 10.1109/TIA.28
[14]	国网北京经济技术研究院. “两型”电网指标体系研究[R]. 北京:国网北京经济技术研究院, 2007.
	State Grid Beijing Institute of Economics and Technology. Research on the “two-type” grid index system[R]. Beijing:State Grid Beijing Institute of Economics and Technology, 2007.
[15]	国网北京经济技术研究院. 电网发展评估方法与模型研究[R]. 北京:国网北京经济技术研究院, 2010.
	State Grid Beijing Institute of Economics and Technology. Research on power grid development assessment methods and models[R]. Beijing: State Grid Beijing Institute of Economics and Technology, 2010.
[16]	蒋菱, 袁月, 王峥, 等. 智能电网创新示范能源互联网评估指标及评价方法[J]. 电力系统及其自动化学报, 2016,28(1):39-45.
	JIANG Ling, YUAN Yue, WANG Zheng, et al. Evaluation index system and comprehensive evaluation method of energy internet in innovative demonstration area of smart grid[J]. Proceedings of the CSU-EPSA, 2016,28(1):39-45.
[17]	姚玉海. 基于预想事故集的配电网自愈控制研究[D]. 北京:华北电力大学, 2016.
	YAO Yuhai. Research on distribution network self-healing control based on contingency set[D]. Beijing:North China Electric Power University, 2016.
[18]	李天友, 徐丙垠. 智能配电网自愈功能与评价指标[J]. 电力系统保护与控制, 2010,38(22):105-108.
	LI Tianyou, XU Bingzhen. Self-healing function and evaluation index of smart distribution network[J]. Power System Protection and Control, 2010,38(22):105-108.
[19]	ZHAO Huiru, LI Tianyou, FU Liwen, et al. The research on comprehensive benefits evaluation of smart grid self-healing[C]// 2012 China International Conference on Electricity Distribution,Shanghai, 2012: 1-12.
[20]	李振坤, 赵向阳, 朱兰, 等. 智能配电网故障后自愈能力评估[J]. 电网技术, 2018,42(3):789-796.
	LI Zhenkun, ZHAO Xiangyang, ZHU Lan, et al. Evaluation of self-healing ability after faults in smart distribution network[J]. Power System Technology, 2018,42(3):789-796.
[21]	赵晓琦, 张智, 姚琪, 等. 面向韧性提升的配电网开关优化配置模型[J]. 电气工程学报, 2020,15(3):128-134.
	ZHAO Xiaoqi, ZHANG Zhi, YAO Qi, et al. Optimal configuration model of switch for distribution network based on resilience improvement[J]. Journal of Electrical Engineering, 2020,15(3):128-134.
[22]	高翔. 智能配电网自愈控制的理论与技术研究[D]. 北京:华北电力大学, 2011.
	GAO Xiang. Study on theories and technologies of self-healing control on smart distribution network[D]. Beijing:North China Electric Power University, 2011.
[23]	陈为化. 基于风险的电力系统静态安全分析与预防控制[D]. 杭州:浙江大学, 2007.
	CHEN Huawei. Risk-based security analysis and preventive control in power system[D]. Hangzhou: Zhejiang University, 2007.
[24]	徐斌, 马骏, 陈青, 等. 基于改进AHP-TOPSIS法的经济开发区配电网综合评价指标体系和投资策略研究[J]. 电力系统保护与控制, 2019,47(22):35-44.
	XU Bin, MA Jun, CHEN Qing, et al. Research on comprehensive evaluation index system and investment strategy of distribution network in economic development zone based on improved AHP-TOPSIS method[J]. Power System Protection and Control, 2019,47(22):35-44.

负荷类别	实际自愈速度	评价
严格负荷	一级速度	很好
	二级速度	差
	三级速度	差
	四级速度	差
敏感负荷	一级速度	很好
	二级速度	好
	三级速度	一般
	四级速度	差
普通负荷	一级速度	很好
	二级速度	很好
	三级速度	好
	四级速度	一般

等级($m_{ij}$的值)	语言描述的程度
1	同等
3	稍微
5	明显
7	强烈
9	极端
2,4,6,8	上述相邻判断的中间值

区段号	1	2	3	4	5	6	7
$Ris{{k}_{L}}$	8.9×10^-5	7.3×10^-5	7.1×10^-5	5.6×10^-5	5.1×10^-5	2.1×10^-5	2.3×10^-5
$Ris{{k}_{V}}$	7.4×10^-4	7.0×10^-4	6.6×10^-4	4.9×10^-4	4.8×10^-4	4.2×10^-4	3.7×10^-4
${{R}_{Li}}$	8.8×10^-4	5.0×10^-4	4.9×10^-4	3.3×10^-4	3.2×10^-4	1.2×10^-4	1.1×10^-4

区段号	1	2	3	4	5	6	7
${{R}_{SHC}}$	6	10	10	6	6	6	6
${{\eta }_{RR}}$	0.88	0.93	0.90	0.89	0.98	0.89	0.99
${{R}_{CL}}$	0.15	0.09	0.13	0.12	0.04	0.14	0.05
${{R}_{ECB}}$	2.77	3.09	2.87	3.04	3.73	2.45	5.12

区段号	1	2	3	4	5	6	7
${{R}_{AOF}}$	5.6	5.2	4.8	1.4	1.2	2.7	0.9
${{R}_{AOD}}$	4.3	4.1	3.9	1.6	1.1	2.5	0.8

含非故障状态下风险评价的配电网自愈性综合评价 ^*

Comprehensive Evaluation of Self-healing Ability of Distribution Network with Risk Assessment Under Non-fault State

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