考虑投资成本的配电网预安排停电管理水平评价指标量化方法
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摘要
随着配电网投资和建设规模的不断扩大,相应的预安排停电工作逐年上升。如何根据配电网投资量化预安排停电工作的管理水平,进而降低预安排停电量,进一步提升配电网的可靠性,已成为当前配电网预安排停电管理工作的一项新课题和新难题。首先采用支持向量数据描述加权算法在停电原因短文本中挖掘出造成每条停电事件的工程施工类型;其次,依据投运设备异动信息与停电事件原因、停电时间之间的关系,建立了配电网各类工程投资与预安排停电数据之间的融合关联模型;在此基础上,依据融合关联的历史数据与可行域概念的思想,设计了一种考虑投资成本的配电网预安排停电管理水平评价指标量化方法;最后,以沿海某省几个实际的配电网系统运行数据为算例,验证所提模型与方法的准确性与有效性。
With continuous expansion of distribution network investment and construction scale, corresponding planned outages increase year by year. How to quantify the management level of planned outages according to the investment of distribution network, reduce the total amount of planned outages and further improve the reliability of distribution network becomes a new difficult problem in the management of planned outages of distribution network. Firstly, support vector data description weighting algorithm is utilized to mine the construction types of each outage event in short text of outage reasons. Secondly, a fusion association model is established between the types of various project investments and the planned power outage data based on the relationship between operation information and the cause of blackout and power outage. On this basis, a quantitative evaluation method of pre-scheduled outage management level considering investment is proposed according to the idea of fusing related historical data and feasible zone concept. Finally, accuracy and validity of the proposed method is verified with operation data of several practical distribution networks in a coastal province.
With continuous expansion of distribution network investment and construction scale, corresponding planned outages increase year by year. How to quantify the management level of planned outages according to the investment of distribution network, reduce the total amount of planned outages and further improve the reliability of distribution network becomes a new difficult problem in the management of planned outages of distribution network. Firstly, support vector data description weighting algorithm is utilized to mine the construction types of each outage event in short text of outage reasons. Secondly, a fusion association model is established between the types of various project investments and the planned power outage data based on the relationship between operation information and the cause of blackout and power outage. On this basis, a quantitative evaluation method of pre-scheduled outage management level considering investment is proposed according to the idea of fusing related historical data and feasible zone concept. Finally, accuracy and validity of the proposed method is verified with operation data of several practical distribution networks in a coastal province.
引文
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[16]唐炬,林俊亦,卓然,等.基于支持向量数据描述的局部放电类型识别[J].高电压技术,2013,39(5):1046-1053.Tang Ju,Lin Junyi,Zhuo Ran,et al Partial discharge type recognition based on support vector data description[J].High Voltage Engineering,2013,39(5):1046-1053(in Chinese).
[17]电力工程造价与定额管理总站.20kV及以下配电网工程建设预算编制与计算标准使用指南[M].北京:中国电力出版社,2009.
[18]孔祥玉,胡启安,董旭柱,等.引入改进模糊C均值聚类的负荷数据辨识及修复方法[J].电力系统自动化,2017,41(9):90-95.Kong Xiangyu,Hu Qi’an,Dong Xuzhu,et al.Load data identification and correction method with improved fuzzy C-means clustering algorithm[J].Automation of Electric Power Systems,2017,41(9):90-95(in Chinese).
[19]肖根胜.改进TFIDF和谱分割的关键词自动抽取方法研究[D].武汉:华中师范大学,2012.
[2]孙健.我国供电可靠性管理的现状分析与展望[J].供用电,2015,32(11):1-5.Sun Jian.Analysis and prospect of power supply reliability management in China[J].Distribution&Utilization,2015,32(11):1-5(in Chinese).
[3]Dias F M,Canizes B,Khodr H,et al.Distribution networks planning using decomposition optimization technique[J].IET Generation Transmission&Distribution,2015,9(12):1409-1420.
[4]王磊.Q/GZW 2 1002-2010供电局配电网综合停电计划管理标准[S].贵州:贵州电网公司,2010.
[5]王浩浩,管霖,吴熳红.配电网可靠性评估中预安排停电的实用数学模型[J].电力系统自动化,2011,35(23):59-63+81.Wang Haohao,Guan Lin,Wu Manhong.Mathmatical model of scheduled outage in reliability assessment of distribution network[J].Automation of Electric Power Systems,2011,35(23):59-63+81(in Chinese).
[6]邱生敏,王浩浩,管霖.考虑复杂转供和预安排停电的配电网可靠性评估[J].电网技术,2011,35(5):121-126.Qiu Shengmin,Wang Haohao,Guan Lin.An improved algorithm for reliability assessment of distribution network considering complex load transfer and scheduled outage[J].Power System Technology,2011,35(5):121-126(in Chinese).
[7]Xie K,Zhang H,Singh C.Reliability forecasting models for electrical distribution systems considering component failures and planned outages[J].International Journal of Electrical Power&Energy Systems,2016(79):228-234.
[8]郇嘉嘉,王钢,李海锋,等.多目标决策分析的电网综合停电管理模型[J].电网技术,2013,37(10):2802-2807.Huan Jiajia,Wang Gang,Li Haifeng,et al.A comprehensive outage management model based on multi-objective decision analysis[J].Power System Technology,2013,37(10):2802-2807(in Chinese).
[9]刘科研,盛万兴,张东霞,等.智能配电网大数据应用需求和场景分析研究[J].中国电机工程学报,2015,35(2):287-293.Liu Keyan,Sheng Wanxing,Zhang Dongxia,et al.Big data application requirements and scenario analysis in smart distribution network[J].Proceedings of CSEE,2015,35(2):287-293(in Chinese).
[10]张东霞,苗新,刘丽平,等.智能电网大数据技术发展研究[J].中国电机工程学报,2015,35(1):2-12.Zhang Dongxia,Miao Xin,Liu Liping,et.al.Research on development strategy for smart grid big data network[J].Proceedings of CSEE,2015,35(1):2-12(in Chinese).
[11]胡丽娟,刁赢龙,刘科研,等.基于大数据技术的配电网运行可靠性分析[J].电网技术,2017,41(1):265-271.Hu Lijuan,Diao Yinglong,Liu Keyan,et al.Operational reliability analysis of distribution network based on big data technology[J].Power System Technology,2017,41(1):265-271(in Chinese).
[12]Zhang L,Jiang L,Li C,et al.Two feature weighting approaches for naive Bayes text classifiers[J].Knowledge-Based Systems,2016,100(C):137-144.
[13]Sun A,Lim E P,Liu Y.On strategies for imbalanced text classification using SVM:A comparative study[J].Decision Support Systems,2010,48(1):191-201.
[14]Liu G.An application of ANN in text categorization[J].Computer Engineering&Applications,2003(36):73-74+92.
[15]宋涛,施水才,房祥,等.基于改进的潜在语义分析的文本聚类[J].北京信息科技大学学报(自然科学版),2012,27(3):21-25.Song Tao,Shi Shuicai,Fang Xiang,et al.Text clustering based on improved latent semantic analysis[J].Journal of Beijing Information Science and Technology University.2012,27(3):21-25(in Chinese).
[16]唐炬,林俊亦,卓然,等.基于支持向量数据描述的局部放电类型识别[J].高电压技术,2013,39(5):1046-1053.Tang Ju,Lin Junyi,Zhuo Ran,et al Partial discharge type recognition based on support vector data description[J].High Voltage Engineering,2013,39(5):1046-1053(in Chinese).
[17]电力工程造价与定额管理总站.20kV及以下配电网工程建设预算编制与计算标准使用指南[M].北京:中国电力出版社,2009.
[18]孔祥玉,胡启安,董旭柱,等.引入改进模糊C均值聚类的负荷数据辨识及修复方法[J].电力系统自动化,2017,41(9):90-95.Kong Xiangyu,Hu Qi’an,Dong Xuzhu,et al.Load data identification and correction method with improved fuzzy C-means clustering algorithm[J].Automation of Electric Power Systems,2017,41(9):90-95(in Chinese).
[19]肖根胜.改进TFIDF和谱分割的关键词自动抽取方法研究[D].武汉:华中师范大学,2012.