于改进抽样法的电力系统可靠性评估

doi:10.11930.2015.5.56

中国电力 ›› 2015, Vol. 48 ›› Issue (5): 56-63.DOI: 10.11930.2015.5.56

于改进抽样法的电力系统可靠性评估

张巍峰¹，车延博¹，林济铿²，胡世骏³，刘辉³，魏文辉⁴，林昌年⁴

1.天津大学智能电网教育部重点实验室，天津 300072；
2. 同济大学电子与信息工程学院，上海 201804；
3. 国网安徽省电力公司调度控制中心，安徽合肥 230061；
4. 北京科东电力控制系统有限责任公司，北京 100192

收稿日期:2014-10-19 出版日期:2015-05-25 发布日期:2015-11-27
作者简介:张巍峰（1988—），男，山东烟台人，硕士研究生，从事电力系统可靠性评估过研究。E-mail: 674720828@qq.com

Power System Reliability Evaluation Based on Improved Sampling Method

ZHANG Weifeng¹, CHE Yanbo¹, LIN Jikeng², HU Shijun³, LIU Hui³, WEI Wenhui⁴, LIN Changnian⁴

1. Key Laboratory of Power System Simulation and Control of Ministry of Education, Tianjin University, Tianjin 300072, China;
2. College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China;
3. Dispatching and Control Center of State Grid Anhui Electric Power Company, Hefei 230061, China;
4. Beijing Kedong Power System Control Co., Ltd., Beijing 100192, China

Received:2014-10-19 Online:2015-05-25 Published:2015-11-27

摘要/Abstract

摘要： 由于电力系统的元件故障为小概率事件，在应用传统非序贯蒙特卡洛抽样法进行系统可靠性评估时，存在抽样次数大，仿真时间长等缺点。通过将对偶变数抽样法与交叉熵重要抽样法相结合，提出了一种适用于电力系统可靠性评估的改进抽样方法。该方法首先通过交叉熵重要抽样确定元件最优参数，构造元件的零方差概率密度函数的近似函数，然后根据最优参数进行对偶抽样，进一步降低抽样过程的方差，提高了传统蒙特卡洛法的抽样效率。应用该方法及传统随机抽样法、对偶变数抽样法和交叉熵重要抽样法对IEEE-RTS（可靠性校验系统）与变参数后的IEEE-RTS进行可靠性评估，计算结果表明：提出的方法在保证一定计算精度的条件下，相比其他方法，进一步提高了仿真速度。越是小概率事件，方法的优势越明显。

关键词: 电力系统, 可靠性评估, 非序贯蒙特卡洛模拟法, 对偶变数抽样法, 交叉熵重要抽样

Abstract: In the case of random simulation of small probability events of component faults in power system, the traditional non sequential Monte Carlo simulation method for power system reliability evaluation has such defects as needing large sampling number and long simulation time. By combining antithetic variable sampling method with cross entropy importance sampling method, an improved sampling method, which is suitable for power system reliability evaluation, is therefore proposed. An approximate function with zero variance probability, whose optimal parameters of component are obtained using cross entropy importance sampling density function of component, is constructed first. Then the variances of reliability indices are further reduced through antithetic variable sampling according to the obtained optimal parameters. The sampling efficiency is thus improved and advantages of the two aforementioned methods are complemented. The proposed method, the traditional random sampling method, the antithetic variable sampling method and the cross entropy importance sampling method are respectively applied to reliability evaluation of IEEE-RTS and modified IEEE-RTS test system. A comparison of the results shows that, compared with the other three methods, the proposed method has higher sampling efficiency is improved, and its advantage is more obvious in rarer events.

Key words: power system, reliability evaluation, non sequential Monte Carlo method, antithetic variable sampling, cross entropy importance sampling

中图分类号:

TM863

张巍峰，车延博，林济铿，胡世骏，刘辉，魏文辉，林昌年. 于改进抽样法的电力系统可靠性评估[J]. 中国电力, 2015, 48(5): 56-63.

ZHANG Weifeng, CHE Yanbo, LIN Jikeng, HU Shijun, LIU Hui, WEI Wenhui, LIN Changnian. Power System Reliability Evaluation Based on Improved Sampling Method[J]. Electric Power, 2015, 48(5): 56-63.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930.2015.5.56

https://www.electricpower.com.cn/CN/Y2015/V48/I5/56

参考文献

[1] 郭永基.电力系统及电力设备的可靠性[J]. 电力系统自动化， 2001，25（17）：53－56．
GUO Yongji. Reliability of power systems and power equipent [J]. Automation of Electric Power Systems, 2001, 25(17): 53-56.
[2] 赵儆，康重庆，夏清，等. 电力市场中可靠性问题的研究现状与发展前景[J]. 电力系统自动化，2004，28（5）：6－10．
ZHAO Jing, KANG Chongqing, XIA Qing, et al. Power system reliability in electricity market current status and future prospects[J]. Automation of Electric Power Systems, 2004, 28(5): 6-10.
[3] 李文沅．电力系统风险评估[M]．北京科学出版社，2006.
[4] CUNHA S H F, PEREIRA M V F, PINTO L, et al. Composite generation and transmission reliability evaluation in large hydroelectric systems[J]. Power Apparatus and Systems, IEEE Transactions on, 1985(10): 2657-2663
[5] 谢绍宇，王秀丽，王锡凡，等. 自适应重要抽样技术在发输电系统可靠性评估中的应用[J]. 电力系统自动化，2010，34（5）： 13－17．
XIE Shaoyu, WANG Xiuli, WANG Xifan, et al. A dynamic aggregation method for induction motors based on their coherent characteristics [J]. Automation of Electric Power Systems, 2010, 34(5): 13-17.
[6] 宋晓通，谭震宇. 改进的重要抽样法在电力系统可靠性评估中的应用[J]. 电网技术，2005，29（13）：56－59．
SONG Xiaotong, TAN Zhenyu. Application of improved importance sampling method in power system reliability evaluation [J]. Power System Technology, 2005, 29(13): 56-59.
[7] 王斌，赵渊，刘威，等. 基于分裂最优乘子重要抽样的电网可靠性评估[J]. 电力系统自动化，2008，32（19）：30－34.
WANG Bin, ZHAO Yuan, LIU Wei, et al. Power system reliability assessment using importance sampling method with splitting optimal multiplier[J]. Automation of Electric Power Systems, 2008, 32(19): 30-34.
[8] 陈宁，沙倩，汤奕，等. 基于交叉熵理论的风电功率组合预测方法[J]. 中国电机工程学报，2012，32（4）：29－34．
CHEN Ning, SHA Qian, TANG Yi, et al. A combination method for wind power predication based on cross entropy theory[J]. Proceedings of the CSEE, 2012, 32(4): 29-34.
[9] 唐静远，师奕兵，周龙甫，等. 基于交叉熵方法和支持向量机的模拟电路故障诊断[J]. 控制与决策，2009，24（9）：1416－1420．
TANG Jingyuan, SHI Yibing, ZHOU Longpu, et al. Analog circuit fault diagnosis based on cross-entropy method and support vector machine [J]. Control and Decision, 2009, 24(9): 1416-1420.
[10] LEITE da SILVA A M, FERNANDEZ R A G, SINGH C. Generating capacity reliability evaluation based on Monte Carlo simulation and cross-entropy methods[J]. Power Systems, IEEE Transactions on, 2010, 25(1): 129-137.
[11] GONZLEZ-FERNNDEZ R A, LEITE da SILVA A M, Resende L C, et al. Composite systems reliability evaluation based on Monte Carlo simulation and cross-entropy methods [J]. 2013.
[12] WANG Y, GUO C, WU Q H. A cross-entropy-based three-stage sequential importance sampling for composite power system short-term reliability evaluation [J]. IEEE Trans on Power Systems, 2013, 28(4): 4254-4263.
[13] 别朝红，王锡凡. 蒙特卡洛法在评估电力系统可靠性中的应用[J]. 电力系统自动化，1997，21（6）：68－75．
BIE Zhaohong, WANG Xifan. The application of monte carlo method to reliability evaluation of power systems[J]. Automation of Electric Power Systems, 1997, 21(6): 68-75.
[14] 朱丽萍，张圣坤. 船体总纵极限强度的可靠性计算[J]. 上海交通大学学报，1999，33（3）：365－367．
ZHU Liping, ZHANG Shengkun. Reliability analysis for ultimate strength of ship hull girder[J]. Journal of Shanghai Jiaotong University, 1999, 33(3): 365-367.
[15] 唐笑慧，富立，范耀祖. 基于蒙特卡洛方法的惯性元件误差模型分析[J]. 东南大学学报：自然科学版，2006，35（Ｓ2）：30－33．
TANG Xiaohui, FU Li, FAN Yaozu. Error model analysis of inertial sensors using Monte Carlo method [J]. Journal of Southeast University: Natural Science Edition, 2006, 35(S2): 30-33.
[16] COSTA A, JONES O D, KROESE D. Convergence properties of the cross-entropy method for discrete optimization[J]. Operations Research Letters, 2007, 35(5): 573-580.
[17] SUBCOMMITTEE P M. IEEE reliability test system[J]. Power Apparatus and Systems, IEEE Transactions on, 1979(6): 2047-2054.

于改进抽样法的电力系统可靠性评估

Power System Reliability Evaluation Based on Improved Sampling Method

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	李健, 张钧, 韩新阳, 靳晓凌. 新型电力系统形态量化推演方法的总体框架与功能设计[J]. 中国电力, 2025, 58(3): 1-7, 97.
[2]	张磊, 马晓伟, 王满亮, 陈力, 高丙团. 互联新能源电力系统区内AGC机组分布式协同控制策略[J]. 中国电力, 2025, 58(3): 8-19.
[3]	张沛, 杨马婧, 张放, 谢桦, 刘广一, 李文云, 路学刚, 王珍意, 翟苏巍. 图数据库与图计算在电力系统调度运行应用综述[J]. 中国电力, 2025, 58(3): 119-131.
[4]	高志远, 庄卫金, 李峰, 于芳, 张鸿, 王艳, 夏旻. 调控领域人工智能应用的高复用性验证平台[J]. 中国电力, 2025, 58(3): 142-150.
[5]	汤明润, 李若旸, 刘慕然, 程晓钰, 刘铫, 杨淑霞. 电力系统稳态下可再生能源大规模接入量预测[J]. 中国电力, 2025, 58(2): 126-132.
[6]	赵晨浩, 焦在滨, 李程昊, 张迪, 张鹏辉. 基于主动迁移学习的电力系统暂态稳定自适应评估[J]. 中国电力, 2025, 58(1): 70-77.
[7]	董武, 张健, 周勤勇, 张立波, 龚浩岳. 中国电力系统安全稳定性演化综述[J]. 中国电力, 2025, 58(1): 115-127.
[8]	朱瑞, 娄奇鹤, 靳晓凌, 刘畅. 适应新型电力系统的电网基建功能化投资结构演化研究[J]. 中国电力, 2024, 57(9): 194-204.
[9]	傅观君, 张富强, 夏鹏, 冯君淑, 张晋芳. 天然气发电在新型电力系统中的功能定位及发展前景研判[J]. 中国电力, 2024, 57(8): 67-74.
[10]	翟苏巍, 李银银, 杜凡, 李文云, 潘凯岩, 梁峻恺. 考虑海量分布式能源接入的配电网分布式无功控制策略[J]. 中国电力, 2024, 57(8): 138-144.
[11]	李碧君, 李威, 董希建. 新型电力系统中主控型安全稳定服务质量的在线评估[J]. 中国电力, 2024, 57(8): 168-181.
[12]	叶小宁, 王彩霞, 李琼慧, 杨超. 国外新能源高占比电力系统电力供应保障措施及启示[J]. 中国电力, 2024, 57(4): 61-67.
[13]	王雪, 刘林, 卓庆东, 张海鹏, 杨苓, 许方园, 曹雨晨. 基于虚拟惯量控制的新型电力系统功率差前馈振荡抑制方法[J]. 中国电力, 2024, 57(4): 68-76.
[14]	周勤勇, 李根兆, 秦晓辉, 施浩波, 陈文静, 龚浩岳. 能源革命下的电力系统范式转换分析[J]. 中国电力, 2024, 57(3): 1-11.
[15]	李卓, 王胤喆, 叶林, 罗雅迪, 宋旭日, 张振宇. 从感知-预测-优化综述图神经网络在电力系统中的应用[J]. 中国电力, 2024, 57(12): 2-16.

模态框（Modal）标题

于改进抽样法的电力系统可靠性评估

Power System Reliability Evaluation Based on Improved Sampling Method

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics