基于多层支持向量机的交直流电网频率稳定控制方法
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摘要
该文针对直流互联异步电网的频率稳定问题,考虑数据驱动方法在电力系统紧急控制中的时效性优势,提出一种基于多层支持向量机(support vector machines,SVM)的交直流电网频率稳定紧急控制方法。该方法利用3层SVM模型实现直流紧急功率支援和自动切负荷控制相结合的最优频率稳定协调控制策略。其中,第1层是建立基于v-SVR的扰动后频率稳定预测模型,该模型能够基于扰动后瞬间的WAMS数据快速预测出稳态频率;第2层是建立基于C-SVC的频率稳定控制方式判断模型,该模型根据预测频率判断相应采取的合理控制方式;第3层是建立基于v-SVR的频率稳定控制策略制定模型,该模型根据所选择的控制方式制定出最优控制策略。仿真分析表明,该方法不仅大大提高了控制时效性,而且具有很好的准确性和有效性,适用于交直流电网频率稳定紧急控制的在线应用。
In this paper, aiming at the frequency stability problem of the asynchronous power grid with DC-interconnected, considering the time-effectiveness advantage of the data-driven methods in emergency control, a frequency stability emergency control method based on multi-layer support vector machines(SVM) was proposed. This method mainly implements the frequency stability control coordinated with emergency DC power support and automatic load-shedding according to a three-layer SVM model. The first layer is to establish a prediction model based on v-SVR, which can quickly predict the post-disturbance steady-state frequency according to the WAMS data. The second layer is to establish the judgment model of frequency control mode based on C-SVC, which can judge the reasonable control mode based on the predicted frequency. The last layer is to establish a frequency stability control scheme formulation model based on v-SVR, which can formulate an optimal control scheme for the judged control mode. Simulation analysis shows that the proposed method not only greatly improves the timeliness of the control, but also has good accuracy and effectiveness. It is suitable for on-line frequency stability emergency control.
In this paper, aiming at the frequency stability problem of the asynchronous power grid with DC-interconnected, considering the time-effectiveness advantage of the data-driven methods in emergency control, a frequency stability emergency control method based on multi-layer support vector machines(SVM) was proposed. This method mainly implements the frequency stability control coordinated with emergency DC power support and automatic load-shedding according to a three-layer SVM model. The first layer is to establish a prediction model based on v-SVR, which can quickly predict the post-disturbance steady-state frequency according to the WAMS data. The second layer is to establish the judgment model of frequency control mode based on C-SVC, which can judge the reasonable control mode based on the predicted frequency. The last layer is to establish a frequency stability control scheme formulation model based on v-SVR, which can formulate an optimal control scheme for the judged control mode. Simulation analysis shows that the proposed method not only greatly improves the timeliness of the control, but also has good accuracy and effectiveness. It is suitable for on-line frequency stability emergency control.
引文
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[9]刘克天,王晓茹,薄其滨.基于广域量测的电力系统扰动后最低频率预测[J].中国电机工程学报,2014,34(13):2188-2195.Liu Ketian,Wang Xiaoru,Bo Qibin.Minimum frequency prediction of power system after disturbance based on the WAMS data[J].Proceedings of the CSEE,2014,34(13):2188-2195(in Chinese).
[10]艾鹏,滕予非,王晓茹,等.计及紧急直流功率支援的扰动后稳态频率预测算法[J].电力系统自动化,2017,41(13):92-99.Ai Peng,Teng Yufei,Wang Xiaoru,et al.Prediction algorithm of steady frequency after disturbances considering emergency DC power support[J].Automation of Electric Power Systems,2017,41(13):92-99(in Chinese).
[11]续昕,张恒旭,李常刚,等.基于轨迹灵敏度的紧急切负荷优化算法[J].电力系统自动化,2016,40(18):143-148.Xu Xin,Zhang Hengxu,Li Changgang,et al.Emergency load shedding optimization algorithm based on trajectory sensitivity[J].Automation of Electric Power Systems,2016,40(18):143-148(in Chinese).
[12]王怀远,张保会,杨松浩,等.基于相平面特性的切机切负荷紧急控制方法[J].中国电机工程学报,2016,36(15):4144-4151.Wang Huaiyuan,Zhang Baohui,Yang Songhao,et al.Combined emergency control strategy of generator tripping and load shedding based on the characteristics of state plane[J].Proceedings of the CSEE,2016,36(15):4144-4151(in Chinese).
[13]王路平,谢小荣,刘颖,等.多直流馈入受端电网短期频率稳定性的实时协调控制方法[J].中国电机工程学报,2018,38(8):2205-2212.Wang Luping,Xie Xiaorong,Liu Ying,et al.Real-time coordinated control of short-term frequency stability for the receiving-end systems with multi-infeed HVDCtransmissions[J].Proceedings of the CSEE,2018,38(8):2205-2212(in Chinese).
[14]胡益,滕予非,王晓茹.基于广域量测的多直流馈入/馈出电网稳态频率控制策略研究[J].电网技术,2018,42(1):25-33.Hu Yi,Teng Yufei,Wang Xiaoru.The steady-state frequency control strategy of power grid with multi-send&multi-infeed HVDCs based on wide-area measurement[J].Power System Technology,2018,42(1):25-33(in Chinese).
[15]Djukanovic M B,Popovic D P,Sobajic D J,et al.Prediction of power system frequency response after generator outages using neural nets[J].IEE Proceedings C-Generation,Transmission and Distribution,1993,140(5):389-398.
[16]薄其滨,王晓茹,刘克天.基于v-SVR的电力系统扰动后最低频率预测[J].电力自动化设备,2015,35(7):83-88.Bo Qibin,Wang Xiaoru,Liu Ketian,et al.Minimum frequency prediction based on v-SVR for post-disturbance power system[J].Electric Power Automation Equipment,2015,35(7):83-88(in Chinese).
[17]Agüero E D,ColoméD G,Granda N V.Adjustment of frequency transient response with reserve deficit using artificial neural network[C]//2016 IEEE PES Transmission&Distribution Conference and Exposition-Latin America(PES T&D-LA).Morelia,Mexico:IEEE,2016:1-6.
[18]胡伟,张玮灵,闵勇,等.基于支持向量机的电力系统紧急控制实时决策方法[J].中国电机工程学报,2017,37(16):4567-4576.Hu Wei,Zhang Weiling,Min Yong,et al.Real-time emergency control decision in power system based on support vector machines[J].Proceedings of the CSEE,2017,37(16):4567-4576(in Chinese).
[19]Jiang Huaiguang,Zhang J J,Gao D W,et al.Synchrophasor based auxiliary controller to enhance power system transient voltage stability in a high penetration renewable energy scenario[C]//2014 IEEESymposium Power Electronics and Machines for Wind and Water Applications(PEMWA).Milwaukee,WI,USA:IEEE,2014:1-7.
[20]周艳真,吴俊勇,冀鲁豫,等.基于两阶段支持向量机的电力系统暂态稳定预测及预防控制[J].中国电机工程学报,2018,38(1):137-147.Zhou Yanzhen,Wu Junyong,Ji Luyu,et al.Two-stage support vector machines for transient stability prediction and preventive control of power systems[J].Proceedings of the CSEE,2018,38(1):137-147(in Chinese).
[21]Robnik-?ikonja M,Kononenko I.Theoretical and empirical analysis of ReliefF and RReliefF[J].Machine Learning,2003,53(1-2):23-69.
[22]鞠平,马大强.电力系统负荷建模[M].2版.北京:中国电力出版社,2008:56-65.Ju Ping,Ma Daqiang.Power system load modeling[M].2nd Ed.Beijing:China Electric Power Press,2008:56-65(in Chinese).
[2]孙雁斌,刘恺,陈亦平,等.异步联网的交直流输电网损在线优化方法及其在南方电网的实现[J].电网技术,2016,40(4):1018-1024.Sun Yanbin,Liu Kai,Chen Yiping,et al.Loss minimization method for asynchronous interconnection AC/DC transmission network and its implementation in CSG system[J].Power System Technology,2016,40(4):1018-1024(in Chinese).
[3]潘晓杰,张顺,文汀,等.渝鄂异步互联对华中电网运行特性的影响[J].电力系统保护与控制,2016,44(19):157-162.Pan Xiaojie,Zhang Shun,Wen Ting,et al.Operation characteristic analysis of Central China Power Grid in unsynchronized interconnection of Chongqing and Hubei power grid[J].Power System Protection and Control,2016,44(19):157-162(in Chinese).
[4]Zhou Baorong,Rao Hong,Wu Wei,et al.Principle and application of asynchronous operation of China Southern Power Grid[J].IEEE Journal of Emerging and Selected Topics in Power Electronics,2018,6(3):1032-1040.
[5]刘巨,姚伟,文劲宇,等.大规模风电参与系统频率调整的技术展望[J].电网技术,2014,38(3):638-646.Liu Ju,Yao Wei,Wen Jinyu,et al.Prospect of technology for large-scale wind farm participating into power grid frequency regulation[J].Power System Technology,2014,38(3):638-646(in Chinese).
[6]李兆伟,吴雪莲,庄侃沁,等.“9·19”锦苏直流双极闭锁事故华东电网频率特性分析及思考[J].电力系统自动化,2017,41(7):149-155.Li Zhaowei,Wu Xuelian,Zhuang Kanqin,et al.Analysis and reflection on frequency characteristics of East China Grid after bipolar locking of“9·19”Jinping-Sunan DCtransmission line[J].Automation of Electric Power Systems,2017,41(7):149-155(in Chinese).
[7]张恒旭,李常刚,刘玉田,等.电力系统动态频率分析与应用研究综述[J].电工技术学报,2010,25(11):169-176.Zhang Hengxu,Li Changgang,Liu Yutian,et al.Reviews on power system dynamic frequency analysis and its application[J].Transactions of China Electrotechnical Society,2010,25(11):169-176(in Chinese).
[8]张薇,王晓茹,廖国栋.基于广域量测数据的电力系统自动切负荷紧急控制算法[J].电网技术,2009,33(3):69-73.Zhang Wei,Wang Xiaoru,Liao Guodong.Automatic load shedding emergency control algorithm of power system based on wide-area measurement data[J].Power System Technology,2009,33(3):69-73(in Chinese).
[9]刘克天,王晓茹,薄其滨.基于广域量测的电力系统扰动后最低频率预测[J].中国电机工程学报,2014,34(13):2188-2195.Liu Ketian,Wang Xiaoru,Bo Qibin.Minimum frequency prediction of power system after disturbance based on the WAMS data[J].Proceedings of the CSEE,2014,34(13):2188-2195(in Chinese).
[10]艾鹏,滕予非,王晓茹,等.计及紧急直流功率支援的扰动后稳态频率预测算法[J].电力系统自动化,2017,41(13):92-99.Ai Peng,Teng Yufei,Wang Xiaoru,et al.Prediction algorithm of steady frequency after disturbances considering emergency DC power support[J].Automation of Electric Power Systems,2017,41(13):92-99(in Chinese).
[11]续昕,张恒旭,李常刚,等.基于轨迹灵敏度的紧急切负荷优化算法[J].电力系统自动化,2016,40(18):143-148.Xu Xin,Zhang Hengxu,Li Changgang,et al.Emergency load shedding optimization algorithm based on trajectory sensitivity[J].Automation of Electric Power Systems,2016,40(18):143-148(in Chinese).
[12]王怀远,张保会,杨松浩,等.基于相平面特性的切机切负荷紧急控制方法[J].中国电机工程学报,2016,36(15):4144-4151.Wang Huaiyuan,Zhang Baohui,Yang Songhao,et al.Combined emergency control strategy of generator tripping and load shedding based on the characteristics of state plane[J].Proceedings of the CSEE,2016,36(15):4144-4151(in Chinese).
[13]王路平,谢小荣,刘颖,等.多直流馈入受端电网短期频率稳定性的实时协调控制方法[J].中国电机工程学报,2018,38(8):2205-2212.Wang Luping,Xie Xiaorong,Liu Ying,et al.Real-time coordinated control of short-term frequency stability for the receiving-end systems with multi-infeed HVDCtransmissions[J].Proceedings of the CSEE,2018,38(8):2205-2212(in Chinese).
[14]胡益,滕予非,王晓茹.基于广域量测的多直流馈入/馈出电网稳态频率控制策略研究[J].电网技术,2018,42(1):25-33.Hu Yi,Teng Yufei,Wang Xiaoru.The steady-state frequency control strategy of power grid with multi-send&multi-infeed HVDCs based on wide-area measurement[J].Power System Technology,2018,42(1):25-33(in Chinese).
[15]Djukanovic M B,Popovic D P,Sobajic D J,et al.Prediction of power system frequency response after generator outages using neural nets[J].IEE Proceedings C-Generation,Transmission and Distribution,1993,140(5):389-398.
[16]薄其滨,王晓茹,刘克天.基于v-SVR的电力系统扰动后最低频率预测[J].电力自动化设备,2015,35(7):83-88.Bo Qibin,Wang Xiaoru,Liu Ketian,et al.Minimum frequency prediction based on v-SVR for post-disturbance power system[J].Electric Power Automation Equipment,2015,35(7):83-88(in Chinese).
[17]Agüero E D,ColoméD G,Granda N V.Adjustment of frequency transient response with reserve deficit using artificial neural network[C]//2016 IEEE PES Transmission&Distribution Conference and Exposition-Latin America(PES T&D-LA).Morelia,Mexico:IEEE,2016:1-6.
[18]胡伟,张玮灵,闵勇,等.基于支持向量机的电力系统紧急控制实时决策方法[J].中国电机工程学报,2017,37(16):4567-4576.Hu Wei,Zhang Weiling,Min Yong,et al.Real-time emergency control decision in power system based on support vector machines[J].Proceedings of the CSEE,2017,37(16):4567-4576(in Chinese).
[19]Jiang Huaiguang,Zhang J J,Gao D W,et al.Synchrophasor based auxiliary controller to enhance power system transient voltage stability in a high penetration renewable energy scenario[C]//2014 IEEESymposium Power Electronics and Machines for Wind and Water Applications(PEMWA).Milwaukee,WI,USA:IEEE,2014:1-7.
[20]周艳真,吴俊勇,冀鲁豫,等.基于两阶段支持向量机的电力系统暂态稳定预测及预防控制[J].中国电机工程学报,2018,38(1):137-147.Zhou Yanzhen,Wu Junyong,Ji Luyu,et al.Two-stage support vector machines for transient stability prediction and preventive control of power systems[J].Proceedings of the CSEE,2018,38(1):137-147(in Chinese).
[21]Robnik-?ikonja M,Kononenko I.Theoretical and empirical analysis of ReliefF and RReliefF[J].Machine Learning,2003,53(1-2):23-69.
[22]鞠平,马大强.电力系统负荷建模[M].2版.北京:中国电力出版社,2008:56-65.Ju Ping,Ma Daqiang.Power system load modeling[M].2nd Ed.Beijing:China Electric Power Press,2008:56-65(in Chinese).