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山东大学学报 (工学版) ›› 2019, Vol. 49 ›› Issue (5): 1-8.doi: 10.6040/j.issn.1672-3961.0.2019.122

• 电气工程———人工智能应用专题 •    下一篇

人工智能在电力系统恢复中的应用综述

刘玉田1(),孙润稼1,王洪涛1,顾雪平2   

  1. 1. 电网智能化调度与控制教育部重点实验室(山东大学), 山东 济南 250061
    2. 华北电力大学电气与电子工程学院, 河北 保定 071003
  • 收稿日期:2019-03-28 出版日期:2019-10-20 发布日期:2019-10-18
  • 作者简介:刘玉田(1964—)，男，山东青州人，教授，博士生导师，博士，主要研究方向为电力系统运行与控制.E-mail:liuyt@sdu.edu.cn刘玉田，1964年7月生，工学博士，教授，博士生导师，山东省“泰山学者”特聘教授，“百千万人才工程”国家级人选，国务院政府特殊津贴专家，教育部新世纪优秀人才，山东省有突出贡献的中青年专家。专业方向为电力系统运行与控制，担任教育部“电网智能化调度与控制”重点实验室主任，IEEE高级会员，中国电机工程学会理事，电力系统自动化、电网技术、J. of Modern Power Systems and Clean Energy、CSEE J. of Power and Energy Systems、Int. J. of Electrical Power and Energy Systems编委
  • 基金资助:
    国家重点研发计划项目(2017YFB0902600)

Review on application of artificial intelligence in power system restoration

Yutian LIU1(),Runjia SUN1,Hongtao WANG1,Xueping GU2   

  1. 1. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong University), Jinan 250061, Shandong, China
    2. School of Electrical & Electronic Engineering, North China Electric Power University, Baoding 071003, Hebei, China
  • Received:2019-03-28 Online:2019-10-20 Published:2019-10-18
  • Supported by:
    国家重点研发计划项目(2017YFB0902600)

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摘要：

归纳总结专家系统、模糊数学、进化计算以及机器学习等人工智能方法应用于电力系统恢复的研究成果,指出现有研究仍以离线恢复方法为主,处于在线决策研究起步阶段,并展望人工智能技术在系统恢复中的应用潜力。

关键词: 电力系统恢复, 专家系统, 模糊数学, 进化计算, 机器学习, 深度学习

Abstract:

The research results of expert system, fuzzy mathematics, evolutionary algorithm and machine learning in power system restoration were summarized. It was pointed out that the existing researches were mainly offline restoration method and the researches about online decision-making were in the initial stage. In addition, the application potential of artificial intelligence technology in system restoration was prospected.

Key words: power system restoration, expert system, fuzzy mathematics, evolutionary computation, machine learning, deep learning

中图分类号: 

  • TM732
1 LINDENMEYER D , DOMMEL H W , ADIBI M M . Power system restoration—a bibliographical survey[J]. International Journal of Electrical Power & Energy Systems, 2001, 23 (3): 219- 227.
2 LIU Y , FAN R , TERZIJA V . Power system restoration: a literature review from 2006 to 2016[J]. Journal of Modern Power Systems & Clean Energy, 2016, 3 (4): 332- 341.
3 杨挺, 赵黎媛, 王成山. 人工智能在电力系统及综合能源系统中的应用综述[J]. 电力系统自动化, 2019, 43 (1): 2- 14.
YANG Ting , ZHAO Liyuan , WANG Chengshan . Review on application of artificial intellgence in power system and integrated energy system[J]. Automation of Electric Power Systems, 2019, 43 (1): 2- 14.
4 LIU Y , SUN P , WANG C . Group decision support system for backbone-network reconfiguration[J]. International Journal of Electrical Power & Energy Systems, 2015, 71, 391- 402.
5 薛禹胜, 肖世杰. 综合防御高风险的小概率事件:对日本相继天灾引发大停电及核泄漏事件的思考[J]. 电力系统自动化, 2011, 35 (8): 1- 11.
XUE Yusheng , XIAO Shijie . Comprehensively defending high risk events with low probability[J]. Automation of Electric Power Systems, 2011, 35 (8): 1- 11.
6 汤涌, 卜广全, 易俊. 印度"7.30"、"7.31"大停电事故分析及启示[J]. 中国电机工程学报, 2012, 32 (25): 167- 174.
TANG Yong , BU Guangquan , YI Jun . Analysis and lessons of the blackout in Indian power grid on July 30 and 31, 2012[J]. Proceedings of the CSEE, 2012, 32 (25): 167- 174.
7 易俊, 卜广全, 郭强, 等. 巴西"3·21"大停电事故分析及对中国电网的启示[J]. 电力系统自动化, 2019, 43 (2): 1- 9.
YI Jun , BU Guangquan , GUO Qiang , et al. Analysis on blackout in Brazilian power grid on march 21, 2018 and its enlightenment to power grid in China[J]. Automation of Electric Power Systems, 2019, 43 (2): 1- 9.
8 SUN W , LIU C , ZHANG L . Optimal generator start-up strategy for bulk power system restoration[J]. IEEE Transactions on Power Systems, 2011, 26 (3): 1357- 1366.
9 刘玉田, 王洪涛, 叶华. 电力系统恢复理论与技术[M]. 北京: 科学出版社, 2014.
10 SAKAGUCHI T , MATSUMOTO K . Development of a knowledge based system for power system restoration[J]. IEEE Transactions on Power Apparatus and Systems, 1983, 102 (2): 320- 329.
11 ZENG S , LIN Z , WEN F , et al. A new approach for power system black-start decision-making with vague set theory[J]. International Journal of Electrical Power & Energy Systems, 2012, 34 (1): 114- 120.
12 朱海南, 刘玉田. 考虑线路投入顺序的网架重构机组恢复多目标优化[J]. 电力系统自动化, 2014, 38 (16): 53- 59.
ZHU Hainan , LIU Yutian . Multi-objective optimization of unit restoration during network reconstruction considering line restoration sequence[J]. Automation of Electric Power Systems, 2014, 38 (16): 53- 59.
13 SILVER D , HUANG A , Maddison C J , et al. Mastering the game of go with deep neural networks and tree search[J]. Nature, 2016, 529 (7587): 484- 489.
14 LIU W , LIN Z , WEN F , et al. A wide area monitoring system based load restoration method[J]. IEEE Transactions on Power Systems, 2013, 28 (2): 2025- 2034.
15 SARMADI S A N , DOBAKHSHARI A S , AZIZI S , et al. A sectionalizing method in power system restoration based on WAMS[J]. IEEE Transactions on Smart Grid, 2011, 2 (1): 190- 197.
16 SUN R , LIU Y , WANG L . An online generator start-up algorithm for transmission system self-healing based on MCTS and sparse autoencoder[J]. IEEE Transactions on Power Systems, 2019, 34 (3): 2061- 2070.
17 KOJIMA Y , WARASHINA S , NAKAMURA S , et al. Development of a guidance method for power system restoraiton[J]. IEEE Transactions on Power Systems, 1989, 4 (3): 1219- 1227.
18 KIRSCHEN D S , VOLKMANN T L . Guiding a power-system restoration with an expert system[J]. IEEE Transactions on Power Systems, 1991, 6 (2): 558- 566.
19 周云海, 胡翔勇, 罗斌. 基于案例推理的大停电恢复系统设计[J]. 电力系统自动化, 2007, 32 (18): 87- 90.
ZHOU Yuhai , HU Xiangyong , LUO Bin . Design of a case based reasoning system for power system restoration[J]. Automation of Electric Power Systems, 2007, 32 (18): 87- 90.
20 王洪涛, 刘玉田, 邱夕兆. 基于分层案例推理的黑启动决策支持系统[J]. 电力系统自动化, 2004, 28 (11): 49- 52.
WANG Hongtao , LIU Yutian , QIU Xizhao . Hierarchical case-based reasoning decision-making system for power system balck start[J]. Automation of Electric Power Systems, 2004, 28 (11): 49- 52.
21 刘玉田, 王春义. 基于数据仓库的网架恢复群体智能决策支持系统[J]. 电力系统自动化, 2009, 33 (1): 45- 50.
LIU Yutian , WANG Chunyi . A group intellgent decision support system for power system seleton restoration based on data warehouse[J]. Automation of Electric Power Systems, 2009, 33 (1): 45- 50.
22 张志毅, 陈允平. 基于模糊多属性决策的黑启动方案优选[J]. 高电压技术, 2007, 33 (3): 42- 45.
ZHANG Zhiyi , CHEN Yunping . Optimization of power system black-start schemes based on the fuzzy multiple attribute decision-making method[J]. High Voltage Engineering, 2007, 33 (3): 42- 45.
23 LIU W , LIN Z , WEN F , et al. Analysis and optimisation of the preferences of decision-makers in black-start group decision-making[J]. IET Generation Transmission & Distribution, 2013, 7 (1): 14- 23.
24 钟慧荣, 顾雪平. 基于模糊层次分析法的黑启动方案评估及灵敏度分析[J]. 电力系统自动化, 2010, 34 (16): 34- 37.
ZHONG Huirong , GU Xueping . Assessment of power system black-start schemes based on fuzzy analytic hierarchy process and its sensitivity analysis[J]. Automation of Electric Power Systems, 2010, 34 (16): 34- 37.
25 SUN P , LIU Y , QIU X , et al. Hybrid multiple attribute group decision-making for power system restoration[J]. Expert Systems with Applications, 2015, 42 (19): 6795- 6805.
26 刘艳, 王涛, 王文炎. 用于网架重构方案运行风险评估的线路投运模型[J]. 中国电机工程学报, 2014, 34 (7): 1124- 1131.
LIU Yan , WANG Tao , WANG Wenyan . Model of restoring transmission lines for operational risk assessment of network-reconfiguration scheme[J]. Proceedings of the CSEE, 2014, 34 (7): 1124- 1131.
27 张雪丽, 梁海平, 朱涛, 等. 基于模糊机会约束规划的电力系统网架重构优化[J]. 电力系统自动化, 2015, 39 (14): 68- 74.
ZHANG Xueli , LIANG Haiping , ZHU Tao , et al. Optimization of power netowrk reconfiguraiton based on fuzzy chance constrained programming[J]. Automation of Electric Power Systems, 2015, 39 (14): 68- 74.
28 陈彬, 王洪涛, 曹曦. 计及负荷模糊不确定性的网架重构后期负荷恢复优化[J]. 电力系统自动化, 2016, 40 (20): 6- 12.
CHEN Bin , WANG Hongtao , CAO Xi . Load restoration optimization during the last stage of network reconfiguration considering load fuzzy uncertainty[J]. Automation of Electric Power Systems, 2016, 40 (20): 6- 12.
29 蔺呈倩, 王洪涛, 赵瑾, 等. 基于可信性理论的含直流落点系统风电与负荷协调恢复优化[J]. 电网技术, 2019, 43 (2): 410- 417.
LIN Chengqian , WANG Hongtao , ZHAO Jin , et al. Wind power-load coordinated restoration optimization of power system with DC terminal location based on credibility theory[J]. Power System Technology, 2019, 43 (2): 410- 417.
30 HOU Y , LIU C , SUN K , et al. Computation of milestones for decision support during system restoration[J]. IEEE Transactions on Power Systems, 2011, 26 (3): 1399- 1409.
31 CHOU Y , LIU C , WANG Y , et al. Development of a black start decision supporting system for isolated power systems[J]. IEEE Transactions on Power Systems, 2013, 28 (3): 2202- 2210.
32 陈彬, 王洪涛. 电力系统恢复过程中的工频过电压动态优化控制[J]. 电力系统自动化, 2015, 39 (14): 54- 59.
CHEN Bin , WANG Hongtao . Dynamic optimal control of sustained overvoltage during power system restoration[J]. Automation of Electric Power Systems, 2015, 39 (14): 54- 59.
33 LIU Y , GU X . Skeleton-network reconfiguration based on topological characteristics of scale-free networks and discrete particle swarm optimization[J]. IEEE Transactions on Power Systems, 2007, 22 (3): 1267- 1274.
34 王江宇, 刘艳. 基于重构方案线路投运风险最小的机组恢复顺序优化[J]. 电力系统保护与控制, 2016, 44 (11): 68- 75.
WANG Jiangyu , LIU Yan . Optimization of unit′s restoration sequence based on minimizing of lines′ restoration risk corresponding to reconfiguration scheme[J]. Power System Protection and Control, 2016, 44 (11): 68- 75.
35 王洪涛, 刘玉田. 基于NSGA-Ⅱ的多目标输电网架最优重构[J]. 电力系统自动化, 2009, 33 (23): 14- 18.
WANG Hongtao , LIU Yutian . Multi-objective optimization of power system reconsturuction based on NSGA-Ⅱ[J]. Automation of Electric Power Systems, 2009, 33 (23): 14- 18.
36 陈亮, 顾雪平, 贾京华. 基于病毒进化改进NSGA-Ⅱ算法的扩展黑启动多目标优化[J]. 电力系统保护与控制, 2014, 42 (2): 35- 42.
CHEN Liang , GU Xueping , JIA Jinghua . Multi-objective extended black-start schemes optimization based on virus evolution improved NSGA-Ⅱ algorithm[J]. Power System Protection and Control, 2014, 42 (2): 35- 42.
37 SUN L , WANG X , LIU W , et al. Optimisation model for power system restoration with support from electric vehicles employing battery swapping[J]. IET Generation Transmission & Distribution, 2016, 10 (3): 771- 779.
38 顾雪平, 刘文轩, 王佳裕, 等. 一种机组恢复决策的多时段协调优化方法[J]. 电工技术学报, 2016, 31 (21): 114- 124.
GU Xueping , LIU Wenxuan , WANG Jiayu , et al. An optimization approach based on multiple time-step coordination for decision making of unit restoration[J]. Transactions of China Electrotechnical Society, 2016, 31 (21): 114- 124.
39 SUN R, ZHU H, LIU Y. A r-NSGA-Ⅱ algorithm based generator start-up for network reconfiguration[C]//5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Changsha, China: IEEE, 2015: 1332-1335.
40 谢彦祥, 刘天琪, 苏学能. Hadoop架构下基于分布式粒子群算法的骨架网络重构方法[J]. 电网技术, 2018, 42 (3): 886- 893.
XIE Yanxiang , LIU Tianqi , SU Xueneng . A novel skeleton network reconfiguraiton method based on distributed PSO algorithm and hadoop architecture[J]. Power System Technology, 2018, 42 (3): 886- 893.
41 瞿寒冰, 刘玉田. 网架重构后期的负荷恢复优化[J]. 电力系统自动化, 2011, 35 (19): 43- 48.
QU Hanbin , LIU Yutian . Load restoration optimization during last stage of network reconfiguration[J]. Automation of Electric Power Systems, 2011, 35 (19): 43- 48.
42 刘文轩, 顾雪平, 王佳裕, 等. 考虑系统安全因素的负荷恢复方案优化[J]. 电力系统自动化, 2016, 40 (12): 87- 93.
LIU Wenxuan , GU Xueping , WANG Jiayu , et al. Optimization of load recovery scheme considering system security factors[J]. Automation of Electric Power Systems, 2016, 40 (12): 87- 93.
43 顾雪平, 赵宝斌, 刘文轩. 结合多目标优化与灰色关联决策的负荷恢复方法[J]. 电力自动化设备, 2015, 35 (9): 6- 13.
GU Xueping , ZHAO Baobin , LIU Wenxuan . Load restoration based on multi-objective optimization and grey incidence decision-making[J]. Electric Power Automation Equipment, 2015, 35 (9): 6- 13.
44 李膨源, 顾雪平. 基于神经网络的黑启动操作过电压快速预测[J]. 电网技术, 2006, 30 (3): 66- 70.
LI Pengyuan , GU Xueping . Fast determination of switching overvoltage in black start process based on artificial neural netowrks[J]. Power System Technology, 2006, 30 (3): 66- 70.
45 THUKARAM D , KHINCHA H P , KHANDELWAL S . Estimation of switching transient peak overvoltages during transmission line energization using artificial neural network[J]. Electric Power Systems Research, 2006, 76 (4): 259- 269.
46 TAHER S A , SADEGHKHANI I . Estimation of magnitude and time duration of temporary overvoltages using ANN in transmission lines during power system restoration[J]. Simulation Modelling Practice and Theory, 2010, 18 (6): 787- 805.
47 SADEGHKHANI I , KETABI A , FEUILLET R . Radial basis function neural network application to power system restoration studies[J]. Computational Intelligence and Neuroscience, 2012, (654895): 1- 10.
48 BRETAS A S , PHADKE A G . Artificial neural networks in power system restoration[J]. IEEE Transactions on Power Delivery, 2003, 18 (4): 1181- 1186.
49 YE D , ZHANG M , SUTANTO D . A hybrid multiagent framework with Q-Learning for power grid systems restoration[J]. IEEE Transactions on Power Systems, 2011, 26 (4): 2434- 2441.
50 SILVER D , SCHRITTWIESER J , SIMONYAN K , et al. Mastering the game of Go without human knowledge[J]. Nature, 2017, 550 (7676): 354- 359.
51 程乐峰, 余涛, 张孝顺, 等. 机器学习在能源与电力系统领域的应用和展望[J]. 电力系统自动化, 2019, 43 (1): 15- 43.
CHENG Lefeng , YU Tao , ZHANG Xiaoshun , et al. Machine learning for energy and electric power systems:state of the art and prospects[J]. Automation of Electric Power Systems, 2019, 43 (1): 15- 43.
52 YU X , XUE Y . Smart grids: a cyber-physical systems perspective[J]. Proceedings of the IEEE, 2016, 104 (SI): 1058- 1070.
53 田世明, 栾文鹏, 张东霞, 等. 能源互联网技术形态与关键技术[J]. 中国电机工程学报, 2015, 35 (14): 3482- 3494.
TIAN Shiming , LUAN Wenpeng , ZHANG Dongxia , et al. Technical forms and key technologies on energy internet[J]. Proceedings of the CSEE, 2015, 35 (14): 3482- 3494.
54 王毅, 陈启鑫, 张宁, 等. 5G通信与泛在电力物联网的融合:应用分析与研究展望[J]. 电网技术, 2019, 43 (5): 1575- 1585.
WANG Yi , CHEN Qixin , ZHANG Ning , et al. Fusion of the 5G Communication and the ubiquitous electric internet of things: application analysis and research prospects[J]. Power System Technology, 2019, 43 (5): 1575- 1585.
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[9] 黄乐建,王建明 . 稳定相容节点积分无网格法动力学分析[J]. 山东大学学报(工学版), 2007, 37(5): 68 -72 .
[10] 马其华 王宜泰. 高密度电阻率法在煤矿界外巨空水探测上的应用[J]. 山东大学学报(工学版), 2009, 39(4): 107 -111 .
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