基于设备状态评价和电网损失风险的配电网检修计划优化模型
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摘要
为解决配网检修计划制定重视网架结构和负荷而忽视设备差异及实时状态的问题,提出了一种基于设备状态评价和电网损失风险计算的配电网检修计划优化模型。建立了设备健康指数与未来所分析时间内失效率矩阵的计算方法,并给出了关键参数。基于动态变化失效率和配电网网架拓扑,采用最小路法计算获得了正常运行及检修情况下整个配电网负荷点失效率和负荷点故障时间。建立了考虑正常及检修情况下配网缺供电量、负荷点重要性、设备价值及故障维修成本的故障电网、故障设备损失风险模型、检修电网损失风险模型和检修设备损失风险模型。结果表明:论文所提出的优化模型综合考虑上述风险模型的计算风险决策值,实现了检修计划的优化;同时,利用动态变化失效率代替传统检修计划制定过程中的历史平均失效率,克服了传统状态评价检修方案制定过程中未计及配电设备检修而导致网架结构薄弱所引发的配网缺供电损失风险。利用该模型对南京某配电网实际案例开展的计算获得了配网风险决策值,计算结果表明:设备多、负荷大、检修时间晚等单一风险因素不一定决定了配电网的风险值,该模型确定的检修方案整体费用低于其他方案,满足实际工程的需要。研究结果证明了基于设备状态评价的配电网检修计划优化的可行性,所提方法同样适用于更高电压等级网络的检修计划优化。
Traditional maintenance plans of distribution network focus on grid structure and load while ignoring equipment difference and real-time equipment status. In order to solve the problems, we established an optimization model of distribution network maintenance plan based on equipment condition evaluation and grid loss risk calculation, put forward a calculation method of the matrix between an equipment health index and a failure rate in the future analysis time, and presented the key parameters. Based on the dynamic failure rate and the distribution network topology, the minimum road method was adopted to obtain the failure rate and the load point failure time of the whole distribution network under normal conditions and maintenance conditions. Then, the risk model of the loss of a power grid caused by failure, the loss of equipment failure, the loss of the power grid caused by maintenance, and the loss of the equipment caused by maintenance were established based on the risk of the loss of the power supply, the importance of the load point, the equipment value, and the maintenance cost. The results show that the optimization model proposed in the paper comprehensively considers the risk decision value calculated by the above risk model, realizing the optimization of the maintenance plan. Meanwhile, the historical average failure rate in the process of the traditional maintenance plan was replaced by the dynamic change failure rate, overcoming the traditional condition evaluation disadvantages caused by the maintenance without taking the weak power distribution network into account. Finally, the model was used to calculate an actual case of a distribution network in Nanjing, and the decision values of distribution network risk were obtained.The calculation results show that the risk value of the distribution network is not necessarily determined by single risk factor such as multiple equipment, heavy load, and late maintenance time, the overall cost of the maintenance plan determined by the model is lower than other schemes and it meet the needs of actual projects. The research results validate the feasibility of the optimization of the distribution network maintenance plan based on the equipment status evaluation, and the proposed method is also applicable to the maintenance plan optimization of the higher voltage level network.
Traditional maintenance plans of distribution network focus on grid structure and load while ignoring equipment difference and real-time equipment status. In order to solve the problems, we established an optimization model of distribution network maintenance plan based on equipment condition evaluation and grid loss risk calculation, put forward a calculation method of the matrix between an equipment health index and a failure rate in the future analysis time, and presented the key parameters. Based on the dynamic failure rate and the distribution network topology, the minimum road method was adopted to obtain the failure rate and the load point failure time of the whole distribution network under normal conditions and maintenance conditions. Then, the risk model of the loss of a power grid caused by failure, the loss of equipment failure, the loss of the power grid caused by maintenance, and the loss of the equipment caused by maintenance were established based on the risk of the loss of the power supply, the importance of the load point, the equipment value, and the maintenance cost. The results show that the optimization model proposed in the paper comprehensively considers the risk decision value calculated by the above risk model, realizing the optimization of the maintenance plan. Meanwhile, the historical average failure rate in the process of the traditional maintenance plan was replaced by the dynamic change failure rate, overcoming the traditional condition evaluation disadvantages caused by the maintenance without taking the weak power distribution network into account. Finally, the model was used to calculate an actual case of a distribution network in Nanjing, and the decision values of distribution network risk were obtained.The calculation results show that the risk value of the distribution network is not necessarily determined by single risk factor such as multiple equipment, heavy load, and late maintenance time, the overall cost of the maintenance plan determined by the model is lower than other schemes and it meet the needs of actual projects. The research results validate the feasibility of the optimization of the distribution network maintenance plan based on the equipment status evaluation, and the proposed method is also applicable to the maintenance plan optimization of the higher voltage level network.
引文
[1]栗然,王飞飞,李增辉.基于风险评估的配电网检修决策优化[J].电力自动化设备,2013,33(11):1-8.LI Ran,WANG Feifei,LI Zenghui.Maintenance decision making optimization based on risk assessment for distribution system[J].Electric Power Automation Equipment,2013,33(11):1-8.
[2]黄弦超,舒隽,张粒子,等.免疫禁忌混合智能优化算法在配电网检修优化中的应用[J].中国电机工程学报,2004,24(11):98-102.HUANG Xianchao,SHU Juan,ZHANG Lizi,et al.Distribution maintenance scheduling using an intelligent optimal approach mixed with immune algorithm and tabu search[J].Proceedings of the CSEE,2004,24(11):98-102.
[3]黄嘉健,王昌照,郑文杰,等.基于状态监测的配电网可靠性检修选择模型[J].电网技术,2015,39(1):164-168.HUANG Jiajian,WANG Changzhao,ZHENG Wenjie,et al.Reliability-centered maintenance selection model for distribution network based on condition monitoring[J].Power System Technology,2015,39(1):164-168.
[4]张高潮,徐洋,刘卫东,等.GIS内置局部放电UHF耦合器的灵敏度[J].高电压技术,2016,42(11):3683-3688.ZHANG Gaochao,XU Yang,LIU Weidong,et al.Sensitivity of the internal UHF coupler used for partial discharge detection in GIS[J].High Voltage Engineering,2016,42(11):3683-3688.
[5]常文治,葛振东,时翔,等.振荡电压下电缆典型缺陷局部放电的统计特征及定位研究[J].电网技术,2013,37(3):746-752.CHANG Wenzhi,GE Zhendong,SHI Xiang,et al.Statistical characteristic and location of partial discharge caused by typical defects in power cable under damped oscillation voltage[J].Power System Technology,2013,37(3):746-752.
[6]张新伯,唐炬,潘成,等.用于局部放电模式识别的深度置信网络方法[J].电网技术,2016,40(10):3272-3278.ZHANG Xinbo,TANG Ju,PAN Cheng,et al.Research of partial discharge recognition based on deep belief nets[J].Power System Technology,2016,40(10):3272-3278.
[7]徐晓刚,张晓星,李鑫,等.内置于高压开关柜的雪花型微带天线设计[J].高电压技术,2016,42(10):3207-3213.XU Xiaogang,ZHANG Xiaoxing,LI Xing,et al.Design of built-in snowflake microstrip antenna built in high-voltage switchgear[J].High Voltage Engineering,2016,42(10):3207-3213.
[8]谢静,束洪春,王科,等.基于FCM算法的高压开关柜局部放电状态评价方法研究[J].高压电器,2015,51(10):82-90,96.XIE Jing,SHU Hongchun,WANG Ke,et al.Study on state evaluation of partial discharge in high voltage switchgear based on fuzzy clustering algorithm[J].High Voltage Apparatus,2015,51(10):82-90,96.
[9]廖瑞金,郑含博,杨丽君,等.基于集对分析方法的电力变压器绝缘状态评估策略[J].电力系统自动化,2010,34(21):55-60.LIAO Ruijin,ZHENG Hanbo,YANG Lijun,et al.A power transformer insulation condition assessment method based on set pair analysis[J].Automation of Electric Power Systems,2010,34(21):55-60.
[10]阮羚,谢齐家,高胜友,等.人工神经网络和信息融合技术在变压器状态评估中的应用[J].高电压技术,2014,40(3):822-828.RUAN Ling,XIE Qijia,GAO Shengyou,et al.Application of artificial neural network and information fusion technology in power transformer condition assessment[J].High Voltage Engineering,2014,40(3):822-828.
[11]周承科,李明贞,王航,等.电力电缆资产的状态评估与运维决策综述[J].高电压技术,2016,42(8):2353-2362.ZHOU Chengke,LI Mingzhen,WANG Hang,et al.Review of condition assessment and maintenance strategy of power cable assets[J].High Voltage Engineering,2016,42(8):2353-2362.
[12]AZIS N,ZHOU D,WANG Z D,et al.Operational condition assessment of in-service distribution transformers[C]∥International Conference on Condition Monitoring and Diagnosis.Bali,Indonesia:IEEE,2012:1156-1159.
[13]张友强,寇凌峰,盛万兴,等.配电变压器运行状态评估的大数据分析方法[J].电网技术,2016,40(3):768-773.ZHANG Youqiang,KOU Lingfeng,SHENG Wanxing,et al.Big data analytical method for operating state assessment of distribution transformer[J].Power System Technology,2016,40(3):768-773.
[14]余杰,周浩,黄春光.以可靠性为中心的检修策略[J].高电压技术,2005,31(6):27-28,58.YU Jie,ZHOU Hao,HUANG Chunguang,et al.Maintenance strategies based on RCM[J].High Voltage Engineering,2005,31(6):27-28,58.
[15]胡文堂,高胜友,鲁宗相,等.利用设备风险评估的检修策略优化[J].高电压技术,2010,36(11):2699-2704.HU Wentang,GAO Shengyou,LU Zongxiang,et al.Maintenance strategies optimization of equipment using risk assessment[J].High Voltage Engineering,2010,36(11):2699-2704.
[16]HUGHES D,DENNIS G,WALKER J.Condition based risk management(CBRM)-enabling asset condition information to be central to corporate decision making[C]∥2005 18th International Conference and Exhibition on Electricity Distribution.[S.l.]:[s.n.],2005:1212-1217.
[17]ALLAN R N,BILLINTON R,SJARIEF I,et al.A reliability test system for educational purposes-basic distribution system data and results[J].IEEE Transactions on Power systems,1991,6(2):813-820.
[18]王旭东.配电系统可靠性评估与网络重构的研究[D].天津:天津大学,2008.WANG Xudong,Research on reliability evaluation and network reconfiguration of distribution system[D].Tianjin,China:Tianjin University,2008.
[19]周丹.统计数据对变压器寿命模型的影响[D].北京:华北电力大学,2013.ZHOU Dan.Effect of statistical data on transformer lifetime modelling[D].Beijing,China:North China Electric Power University,2013.
[2]黄弦超,舒隽,张粒子,等.免疫禁忌混合智能优化算法在配电网检修优化中的应用[J].中国电机工程学报,2004,24(11):98-102.HUANG Xianchao,SHU Juan,ZHANG Lizi,et al.Distribution maintenance scheduling using an intelligent optimal approach mixed with immune algorithm and tabu search[J].Proceedings of the CSEE,2004,24(11):98-102.
[3]黄嘉健,王昌照,郑文杰,等.基于状态监测的配电网可靠性检修选择模型[J].电网技术,2015,39(1):164-168.HUANG Jiajian,WANG Changzhao,ZHENG Wenjie,et al.Reliability-centered maintenance selection model for distribution network based on condition monitoring[J].Power System Technology,2015,39(1):164-168.
[4]张高潮,徐洋,刘卫东,等.GIS内置局部放电UHF耦合器的灵敏度[J].高电压技术,2016,42(11):3683-3688.ZHANG Gaochao,XU Yang,LIU Weidong,et al.Sensitivity of the internal UHF coupler used for partial discharge detection in GIS[J].High Voltage Engineering,2016,42(11):3683-3688.
[5]常文治,葛振东,时翔,等.振荡电压下电缆典型缺陷局部放电的统计特征及定位研究[J].电网技术,2013,37(3):746-752.CHANG Wenzhi,GE Zhendong,SHI Xiang,et al.Statistical characteristic and location of partial discharge caused by typical defects in power cable under damped oscillation voltage[J].Power System Technology,2013,37(3):746-752.
[6]张新伯,唐炬,潘成,等.用于局部放电模式识别的深度置信网络方法[J].电网技术,2016,40(10):3272-3278.ZHANG Xinbo,TANG Ju,PAN Cheng,et al.Research of partial discharge recognition based on deep belief nets[J].Power System Technology,2016,40(10):3272-3278.
[7]徐晓刚,张晓星,李鑫,等.内置于高压开关柜的雪花型微带天线设计[J].高电压技术,2016,42(10):3207-3213.XU Xiaogang,ZHANG Xiaoxing,LI Xing,et al.Design of built-in snowflake microstrip antenna built in high-voltage switchgear[J].High Voltage Engineering,2016,42(10):3207-3213.
[8]谢静,束洪春,王科,等.基于FCM算法的高压开关柜局部放电状态评价方法研究[J].高压电器,2015,51(10):82-90,96.XIE Jing,SHU Hongchun,WANG Ke,et al.Study on state evaluation of partial discharge in high voltage switchgear based on fuzzy clustering algorithm[J].High Voltage Apparatus,2015,51(10):82-90,96.
[9]廖瑞金,郑含博,杨丽君,等.基于集对分析方法的电力变压器绝缘状态评估策略[J].电力系统自动化,2010,34(21):55-60.LIAO Ruijin,ZHENG Hanbo,YANG Lijun,et al.A power transformer insulation condition assessment method based on set pair analysis[J].Automation of Electric Power Systems,2010,34(21):55-60.
[10]阮羚,谢齐家,高胜友,等.人工神经网络和信息融合技术在变压器状态评估中的应用[J].高电压技术,2014,40(3):822-828.RUAN Ling,XIE Qijia,GAO Shengyou,et al.Application of artificial neural network and information fusion technology in power transformer condition assessment[J].High Voltage Engineering,2014,40(3):822-828.
[11]周承科,李明贞,王航,等.电力电缆资产的状态评估与运维决策综述[J].高电压技术,2016,42(8):2353-2362.ZHOU Chengke,LI Mingzhen,WANG Hang,et al.Review of condition assessment and maintenance strategy of power cable assets[J].High Voltage Engineering,2016,42(8):2353-2362.
[12]AZIS N,ZHOU D,WANG Z D,et al.Operational condition assessment of in-service distribution transformers[C]∥International Conference on Condition Monitoring and Diagnosis.Bali,Indonesia:IEEE,2012:1156-1159.
[13]张友强,寇凌峰,盛万兴,等.配电变压器运行状态评估的大数据分析方法[J].电网技术,2016,40(3):768-773.ZHANG Youqiang,KOU Lingfeng,SHENG Wanxing,et al.Big data analytical method for operating state assessment of distribution transformer[J].Power System Technology,2016,40(3):768-773.
[14]余杰,周浩,黄春光.以可靠性为中心的检修策略[J].高电压技术,2005,31(6):27-28,58.YU Jie,ZHOU Hao,HUANG Chunguang,et al.Maintenance strategies based on RCM[J].High Voltage Engineering,2005,31(6):27-28,58.
[15]胡文堂,高胜友,鲁宗相,等.利用设备风险评估的检修策略优化[J].高电压技术,2010,36(11):2699-2704.HU Wentang,GAO Shengyou,LU Zongxiang,et al.Maintenance strategies optimization of equipment using risk assessment[J].High Voltage Engineering,2010,36(11):2699-2704.
[16]HUGHES D,DENNIS G,WALKER J.Condition based risk management(CBRM)-enabling asset condition information to be central to corporate decision making[C]∥2005 18th International Conference and Exhibition on Electricity Distribution.[S.l.]:[s.n.],2005:1212-1217.
[17]ALLAN R N,BILLINTON R,SJARIEF I,et al.A reliability test system for educational purposes-basic distribution system data and results[J].IEEE Transactions on Power systems,1991,6(2):813-820.
[18]王旭东.配电系统可靠性评估与网络重构的研究[D].天津:天津大学,2008.WANG Xudong,Research on reliability evaluation and network reconfiguration of distribution system[D].Tianjin,China:Tianjin University,2008.
[19]周丹.统计数据对变压器寿命模型的影响[D].北京:华北电力大学,2013.ZHOU Dan.Effect of statistical data on transformer lifetime modelling[D].Beijing,China:North China Electric Power University,2013.