一种垂直一体化电网静态参数修正方法
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摘要
模型管理系统中时常存在新投入设备的参数输入错误和临近退役设备的参数漂移或突变的现象,这使得依赖于基础数据的各项高级应用计算的可信度降低,针对这一问题,提出了一种基于智能调度平台的垂直一体化参数辨识修正方法。利用局部参数错误导致状态估计的量测残差会出现局部偏大的现象,定义可疑量测评价函数,建立基于可疑量测评价函数的参数综合可疑度指标,将可疑度较大的参数作为可疑参数的初始集。进而针对设备的全生命周期标志,将可能存在参数错误的新投入设备和临退役设备的参数并入可疑参数集中。排除部分影响很小的可疑参数后得到最终的候选可疑参数集,调度中心模型管理系统对候选可疑参数进行维护之后通告所辖各级用户(子调度)对模型参数数据库进行更新。采用IEEE 14节点系统验证了方法的有效性。
The computing credibility of the advanced applications of energy management system that relies on the basic data may deteriorate due to the error in the input parameter of devices that are newly added into the system and the drift or mutation of parameters of facilities that are near the end of life cycle. This paper presents a vertically-integrated method for parameter identification based on the intelligent scheduling platform. The dispatching center supervisor defines the suspicious measurement evaluation function and the comprehensive judgment indexes using the phenomenon that measuring residuals in the state estimation increase when there are partial parameter errors. The set of parameters with relatively larger comprehensive judgment indexes is employed as the initial set of suspicious parameters. Considering the life cycle flags of the devices, there may be parameter errors in the newly-operated and nearly-retired devices whose parameters are also added to the suspicious parameter set. The suspicious parameters with limited impact are excluded from the suspicious parameter set, and the final set of candidate parameters is finally obtained. The model management system of dispatching centers maintains the candidate parameters, and inform the sub dispatching centers to update the model parameters base. Simulation results on the IEEE 14-node system have verified the validity of the proposed method.
The computing credibility of the advanced applications of energy management system that relies on the basic data may deteriorate due to the error in the input parameter of devices that are newly added into the system and the drift or mutation of parameters of facilities that are near the end of life cycle. This paper presents a vertically-integrated method for parameter identification based on the intelligent scheduling platform. The dispatching center supervisor defines the suspicious measurement evaluation function and the comprehensive judgment indexes using the phenomenon that measuring residuals in the state estimation increase when there are partial parameter errors. The set of parameters with relatively larger comprehensive judgment indexes is employed as the initial set of suspicious parameters. Considering the life cycle flags of the devices, there may be parameter errors in the newly-operated and nearly-retired devices whose parameters are also added to the suspicious parameter set. The suspicious parameters with limited impact are excluded from the suspicious parameter set, and the final set of candidate parameters is finally obtained. The model management system of dispatching centers maintains the candidate parameters, and inform the sub dispatching centers to update the model parameters base. Simulation results on the IEEE 14-node system have verified the validity of the proposed method.
引文
[1]LIU W H E, LIM S L. Parameter error identification and estimation in power system state estimation[J]. IEEE Transactions on power systems, 1995, 10(1):200–209.
[2]杨滢.拓扑错误辨识与参数估计的理论分析和算法研究[D].北京:清华大学, 2005.
[3]李碧君,薛禹胜,顾锦汶,等.电力系统状态估计问题的研究现状和展望[J].电力系统自动化, 1998, 22(11):53–60.LI Bijun, XUE Yusheng, GU Jinwen,et al. Research status and prospect of power system state estimation[J]. Automation of Electric Power Systems, 1998, 22(11):53–60.
[4]李大路,李蕊,孙元章,等.计及广域测量信息的状态估计错误参数识别与修正[J].电力系统自动化, 2008, 32(14):11–15.LI Dalu, LI Rui, SUN Yuanzhang, et al. Recognizing and correcting the wrong parameters in state estimation considering the WAMS measurements[J]. Automation of Electric Power Systems, 2008,32(14):11–15.
[5]郭烨,吴文传,张伯明,等.拉格朗日乘子法电力系统网络参数辨识的应用[J].中国电机工程学报, 2013, 33(10):43–49.GUO Ye, WU Wenchuan, ZHANG Boming, et al. Application of the power system network parameter error identification based on lagrange multiplier method[J]. Proceedings of the CSEE, 2013,33(10):43–49.
[6]谷海彤,郭烨,刘育权,等.智能调度电网参数在线辨识与估计及其在广州电网的应用[J].电网技术, 2013, 37(1):162–166.GU Haitong, GUO Ye, LIU Yuquan, et al. An on-line identification and estimation system for intelligent dispatching power grid parameters and its application in Guangzhou power grid[J]. Power System Technology, 2013, 37(1):162–166.
[7]徐艳.基于新息图法的电力系统参数估计的研究[D].哈尔滨:哈尔滨工业大学, 2008.
[8]颜伟,赵雪骞,陈俊,等.电网设备错误参数的支路量测标幺值残差代数和均值辨识法[J].电力自动化设备, 2013, 33(2):99–103.YAN Wei, ZHAO Xueqian, CHEN Jun,et al. Grid equipment parameter error identification based on mean algebraic sum of branch measurement normalized residuals[J]. Electric Power Automation Equipment, 2013, 33(2):99–103.
[9]LIU W H E, WU F F, LUN S M. Estimation of parameter errors from measurement residuals in state estimation(power systems)[J]. IEEE Transactions on Power Systems, 1992, 7(1):81–89.
[10]吴昊,闫文瑾,何桦.基于多方式电网断面的输电网络参数估计[J].电网技术, 2009, 33(18):89–92.WU Hao, YAN Wenjin, HE Hua. Parameter estimation of power transmission network based on multi-cases of power flow operating conditions[J]. Power System Technology, 2009, 33(18):89–92.
[11]WILSON R E, ZEVENBERGEN G A, MAH D L, et al. Calculation of transmission line parameters from synchronized measurements[J].Electric Machines&Power Systems, 1999, 27(12):1269–1278.
[12]NAGAR A K, POWELL R S. LFT/SDP approach to the uncertainty analysis for state estimation of water distribution systems[J]. IEE Proceedings-Control Theory and Applications, 2002, 149(2):137–142.
[13]陈震.基于数据挖掘的电网规划不良数据辨识与修正[D].北京:华北电力大学, 2016.
[14]周寅飞.基于内点法和离散粒子群算法的输电网参数辨识[J].江苏电机工程, 2014, 33(1):22–25.ZHOU Yinfei, A hybrid strategy based on interior point method and DPSO for electricity transmission network parameter estimation[J]. A hybrid strategy based on interior point method and DPSO for electricity transmission network parameter estimation[J]. Jiangsu Electrical Engineering, 2014, 33(1):22–25.
[15]宁剑,王毅,邹德虎,等.状态估计智能分析功能设计与应用[J].中国电力, 2015, 48(2):85–89.NING Jian, WANG Yi, ZOU Dehu, et al. Design and application of state estimation intelligent analysis[J]. Electric Power, 2015, 48(2):85–89.
[16]金学成,邹根华,张浩,等.考虑抗差状态估计大误差点的电网可疑参数辨识及其应用[J].中国电力, 2016, 49(2):114–117, 121.JIN Xuecheng, ZOU Genhua, ZHANG Hao,et al. A network parameter errors identification method considering large error point based on robust state estimation and its real application[J]. Electric Power, 2016, 49(2):114–117, 121.
[17]朱英刚,闫有朋,王良.带等式约束的加权最小二乘法参数估计[J].中国电力, 2008, 41(7):25–27.ZHU Yinggang, YAN Youpeng, WAN Liang. Parameter estimation with equality constraints based on weighted least square[J]. Electric Power, 2008, 41(7):25–27.
[18]曾兵,吴文传,张伯明.基于Karush-Kuhn-Tucker最优条件的电网可疑参数辨识与估计[J].电网技术, 2010, 34(1):56–61.ZENG Bing, WU Wenchuan, ZHANG Boming. A method to identify and estimate network parameter errors based on Karush-Kuhn-Tucker condition[J]. Power System Technology, 2010, 34(1):56–61.
[19]于尔铿.电力系统状态估计[M].北京:水利电力出版社, 1985:105-165.
[20]翟晶晶,张小莲,梁新凡,等.基于可疑度的电网参数错误辨识与估计方法[J].电工电能新技术, 2016, 35(4):43–48.ZHAI Jingjing, ZHANG Xiaolian, LIANG Xinfan,et al. Error identification and estimation method of grid parameters based on suspicious degree[J]. Advanced Technology of Electrical Engineering and Energy, 2016, 35(4):43–48.
[2]杨滢.拓扑错误辨识与参数估计的理论分析和算法研究[D].北京:清华大学, 2005.
[3]李碧君,薛禹胜,顾锦汶,等.电力系统状态估计问题的研究现状和展望[J].电力系统自动化, 1998, 22(11):53–60.LI Bijun, XUE Yusheng, GU Jinwen,et al. Research status and prospect of power system state estimation[J]. Automation of Electric Power Systems, 1998, 22(11):53–60.
[4]李大路,李蕊,孙元章,等.计及广域测量信息的状态估计错误参数识别与修正[J].电力系统自动化, 2008, 32(14):11–15.LI Dalu, LI Rui, SUN Yuanzhang, et al. Recognizing and correcting the wrong parameters in state estimation considering the WAMS measurements[J]. Automation of Electric Power Systems, 2008,32(14):11–15.
[5]郭烨,吴文传,张伯明,等.拉格朗日乘子法电力系统网络参数辨识的应用[J].中国电机工程学报, 2013, 33(10):43–49.GUO Ye, WU Wenchuan, ZHANG Boming, et al. Application of the power system network parameter error identification based on lagrange multiplier method[J]. Proceedings of the CSEE, 2013,33(10):43–49.
[6]谷海彤,郭烨,刘育权,等.智能调度电网参数在线辨识与估计及其在广州电网的应用[J].电网技术, 2013, 37(1):162–166.GU Haitong, GUO Ye, LIU Yuquan, et al. An on-line identification and estimation system for intelligent dispatching power grid parameters and its application in Guangzhou power grid[J]. Power System Technology, 2013, 37(1):162–166.
[7]徐艳.基于新息图法的电力系统参数估计的研究[D].哈尔滨:哈尔滨工业大学, 2008.
[8]颜伟,赵雪骞,陈俊,等.电网设备错误参数的支路量测标幺值残差代数和均值辨识法[J].电力自动化设备, 2013, 33(2):99–103.YAN Wei, ZHAO Xueqian, CHEN Jun,et al. Grid equipment parameter error identification based on mean algebraic sum of branch measurement normalized residuals[J]. Electric Power Automation Equipment, 2013, 33(2):99–103.
[9]LIU W H E, WU F F, LUN S M. Estimation of parameter errors from measurement residuals in state estimation(power systems)[J]. IEEE Transactions on Power Systems, 1992, 7(1):81–89.
[10]吴昊,闫文瑾,何桦.基于多方式电网断面的输电网络参数估计[J].电网技术, 2009, 33(18):89–92.WU Hao, YAN Wenjin, HE Hua. Parameter estimation of power transmission network based on multi-cases of power flow operating conditions[J]. Power System Technology, 2009, 33(18):89–92.
[11]WILSON R E, ZEVENBERGEN G A, MAH D L, et al. Calculation of transmission line parameters from synchronized measurements[J].Electric Machines&Power Systems, 1999, 27(12):1269–1278.
[12]NAGAR A K, POWELL R S. LFT/SDP approach to the uncertainty analysis for state estimation of water distribution systems[J]. IEE Proceedings-Control Theory and Applications, 2002, 149(2):137–142.
[13]陈震.基于数据挖掘的电网规划不良数据辨识与修正[D].北京:华北电力大学, 2016.
[14]周寅飞.基于内点法和离散粒子群算法的输电网参数辨识[J].江苏电机工程, 2014, 33(1):22–25.ZHOU Yinfei, A hybrid strategy based on interior point method and DPSO for electricity transmission network parameter estimation[J]. A hybrid strategy based on interior point method and DPSO for electricity transmission network parameter estimation[J]. Jiangsu Electrical Engineering, 2014, 33(1):22–25.
[15]宁剑,王毅,邹德虎,等.状态估计智能分析功能设计与应用[J].中国电力, 2015, 48(2):85–89.NING Jian, WANG Yi, ZOU Dehu, et al. Design and application of state estimation intelligent analysis[J]. Electric Power, 2015, 48(2):85–89.
[16]金学成,邹根华,张浩,等.考虑抗差状态估计大误差点的电网可疑参数辨识及其应用[J].中国电力, 2016, 49(2):114–117, 121.JIN Xuecheng, ZOU Genhua, ZHANG Hao,et al. A network parameter errors identification method considering large error point based on robust state estimation and its real application[J]. Electric Power, 2016, 49(2):114–117, 121.
[17]朱英刚,闫有朋,王良.带等式约束的加权最小二乘法参数估计[J].中国电力, 2008, 41(7):25–27.ZHU Yinggang, YAN Youpeng, WAN Liang. Parameter estimation with equality constraints based on weighted least square[J]. Electric Power, 2008, 41(7):25–27.
[18]曾兵,吴文传,张伯明.基于Karush-Kuhn-Tucker最优条件的电网可疑参数辨识与估计[J].电网技术, 2010, 34(1):56–61.ZENG Bing, WU Wenchuan, ZHANG Boming. A method to identify and estimate network parameter errors based on Karush-Kuhn-Tucker condition[J]. Power System Technology, 2010, 34(1):56–61.
[19]于尔铿.电力系统状态估计[M].北京:水利电力出版社, 1985:105-165.
[20]翟晶晶,张小莲,梁新凡,等.基于可疑度的电网参数错误辨识与估计方法[J].电工电能新技术, 2016, 35(4):43–48.ZHAI Jingjing, ZHANG Xiaolian, LIANG Xinfan,et al. Error identification and estimation method of grid parameters based on suspicious degree[J]. Advanced Technology of Electrical Engineering and Energy, 2016, 35(4):43–48.