基于分层分布式模型预测控制的多时空尺度协调风电集群综合频率控制策略
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摘要
高渗透率风电集群的接入对电力系统频率稳定性带来了不利影响,为了解决这一问题,根据大系统控制论中分层递阶控制理论,该文提出一种基于分层分布式模型预测控制的多时空尺度协调风电集群综合频率控制策略。该控制策略建立了风电集群在三次调频层、二次调频层及一次调频层的变粒度频率控制框架,首先在各层采用时间尺度逐层细化的预测时域、控制时域以及超短期风电功率预测值;其次在各层建立空间尺度逐层细化的滚动优化模型,其中在三次调频层考虑电网拓扑结构及全区经济性最优目标,在二次调频层考虑平均系统频率增广模型及分区安全性最优目标,在一次调频层考虑分区风电集群内单场动态分类来实时平抑系统负荷小幅值随机扰动;最后根据电网及风电集群实时运行状态建立反馈校正环节,实现综合频率控制策略的闭环运行。算例表明,所提控制策略能够有效实现风电集群参与系统调频,并能兼顾考虑系统的经济性及安全性目标。
High penetration wind power cluster integration has an adverse effect on power system frequency stability. In order to solve this problem, according to the hierarchical control theory in large system cybernetics, an integrated frequency control strategy for wind power cluster with multiple temporal and spatial scale coordination based on hierarchicaldistributed model predictive control(H-DMPC) was proposed in this paper. A variable granularity frequency control framework with wind power cluster participating in third frequency control layer, secondary frequency control layer and primary frequency control layer was established in this control strategy. Firstly, prediction horizon, control horizon and the ultra-short-time wind power forecasting data with coordinated temporal scale were used in each layer. Secondly, a rolling optimization model with coordinated temporal and spatial scale was established in each layer. In third frequency control layer, power system topology and economically optimal objective were considered. In secondary frequency control layer, average system frequency augmented model(ASFAM) and areal securely optimal objective were considered. In primary frequency control layer, system load stochastic disturbancewith small magnitude was reduced by means of dynamic classification of wind farms in areal wind power cluster. Finally, according to the real time operation state of power system and wind power cluster, a feedback correction link was established to realize closed-loop control. Case study results demonstrate that the proposed control strategy could effectively realize power system frequency control with wind power cluster participation and give consideration to both economic and secure objectives in power system.
High penetration wind power cluster integration has an adverse effect on power system frequency stability. In order to solve this problem, according to the hierarchical control theory in large system cybernetics, an integrated frequency control strategy for wind power cluster with multiple temporal and spatial scale coordination based on hierarchicaldistributed model predictive control(H-DMPC) was proposed in this paper. A variable granularity frequency control framework with wind power cluster participating in third frequency control layer, secondary frequency control layer and primary frequency control layer was established in this control strategy. Firstly, prediction horizon, control horizon and the ultra-short-time wind power forecasting data with coordinated temporal scale were used in each layer. Secondly, a rolling optimization model with coordinated temporal and spatial scale was established in each layer. In third frequency control layer, power system topology and economically optimal objective were considered. In secondary frequency control layer, average system frequency augmented model(ASFAM) and areal securely optimal objective were considered. In primary frequency control layer, system load stochastic disturbancewith small magnitude was reduced by means of dynamic classification of wind farms in areal wind power cluster. Finally, according to the real time operation state of power system and wind power cluster, a feedback correction link was established to realize closed-loop control. Case study results demonstrate that the proposed control strategy could effectively realize power system frequency control with wind power cluster participation and give consideration to both economic and secure objectives in power system.
引文
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[14]赵晶晶,吕雪,符杨,等.基于双馈感应风力发电机虚拟惯量和桨距角联合控制的风光柴微电网动态频率控制[J].中国电机工程学报,2015,35(15):3815-3822.Zhao Jingjing,LüXue,Fu Yang,et al.Dynamic frequency control strategy of wind/photovoltaic/diesel microgrid based on DFIG virtual inertia control and pitch angle control[J].Proceedings of the CSEE,2015,35(15):3815-3822(in Chinese).
[15]付媛,王毅,张祥宇,等.变速风电机组的惯性与一次调频特性分析及综合控制[J].中国电机工程学报,2014,34(27):4706-4716.Fu Yuan,Wang Yi,Zhang Xiangyu,et al.Analysis and integrated control of inertia and primary frequency regulation for variable speed wind turbines[J].Proceedings of the CSEE,2014,34(27):4706-4716(in Chinese).
[16]刘吉臻,姚琦,柳玉,等.风火联合调度的风电场一次调频控制策略研究[J].中国电机工程学报,2017,37(12):3462-3469.Liu Jizhen,Yao Qi,Liu Yu,et al.Wind farm primary frequency control strategy based on wind&thermal power joint control[J].Proceedings of the CSEE,2017,37(12):3462-3469(in Chinese).
[17]席裕庚.预测控制[M].2版.北京:国防工业出版社,2013.Xi Yugeng.Predictive control[M].2nd ed.Beijing:National Defense Industry Press,2013(in Chinese).
[18]叶林,任成,李智,等.风电场有功功率多目标分层递阶预测控制策略[J].中国电机工程学报,2016,36(23):6327-6336.Ye Lin,Ren Cheng,Li Zhi,et al.Stratified progressive predictive control strategy for multi-objective dispatching active power in wind farm[J].Proceedings of the CSEE,2016,36(23):6327-6336(in Chinese).
[19]叶林,张慈杭,汤涌,等.多时空尺度协调的风电集群有功分层预测控制方法[J].中国电机工程学报,2018,38(13):3767-3780.Ye Lin,Zhang Cihang,Tang Yong,et al.Active power stratification predictive control approach for wind power cluster with multiple temporal and spatial scale coordination[J].Proceedings of the CSEE,2018,38(13):3767-3780(in Chinese).
[20]叶林,李智,汤涌,等.基于随机预测控制理论和功率波动相关性的风电集群优化调度[J].中国电机工程学报,2018,38(11):3172-3183.Ye Lin,Li Zhi,Tang Yong,et al.Optimal dispatch of system integrated wind farm clusters based on stochastic model predictive control considering temporal correlation of wind power[J].Proceedings of the CSEE,2018,38(11):3172-3183(in Chinese).
[21]孙舶皓,汤涌,仲悟之,等.基于分布式模型预测控制的包含大规模风电集群互联系统超前频率控制策略[J].中国电机工程学报,2017,37(21):6291-6302.Sun Bohao,Tang Yong,Zhong Wuzhi,et al.Multi-area interconnected power system advanced frequency control strategy considering large scale wind power cluster integration based on DMPC[J].Proceedings of the CSEE,2017,37(21):6291-6302(in Chinese).
[22]涂序彦,王枞,郭燕慧.大系统控制论[M].北京:北京邮电大学出版社,2005.Tu Xuyan,Wang Zong,Guo Yanhui.Large systems cybernetics[M].Beijing:Beijing University of Posts and Telecommunications Press,2005(in Chinese).
[23]Gautam D,Goel L,Ayyanar R,et al.Control strategy to mitigate the impact of reduced inertia due to doubly fed induction generators on large power systems[J].IEEETransactions on Power Systems,2011,26(1):214-224.
[24]李志刚,吴文传,张伯明.消纳大规模风电的鲁棒区间经济调度:(一)调度模式与数学模型[J].电力系统自动化,2014,38(20):33-39.Li Zhigang,Wu Wenchuan,Zhang Boming.A robust interval economic dispatch method accommodating large-scale wind power generation:part one dispatch scheme and mathematical model[J].Automation of Electric Power Systems,2014,38(20):33-39(in Chinese).
[25]李军军,吴政球.风电参与一次调频的小扰动稳定性分析[J].中国电机工程学报,2011,31(13):1-9.Li Junjun,Wu Zhengqiu.Small signal stability analysis of wind power generation participating in primary frequency regulation[J].Proceedings of the CSEE,2011,31(13):1-9(in Chinese).
[26]Ye Lin,Zhao Yongming,Zeng Cheng,et al.Short-term wind power prediction based on spatial model[J].Renewable Energy,2017,101:1067-1074.
[27]叶林,朱倩雯,赵永宁.超短期风电功率预测的自适应指数动态优选组合模型[J].电力系统自动化,2015,39(20):12-18.Ye Lin,Zhu Qianwen,Zhao Yongning.Dynamic optimal combination model considering adaptive exponential for ultra-short term wind power prediction[J].Automation of Electric Power Systems,2015,39(20):12-18(in Chinese).
[2]Wu Ziping,Gao Wenzhong,Gao Tianqi,et al.State-of-the-art review on frequency response of wind power plants in power systems[J].Journal of Modern Power Systems and Clean Energy,2018,6(1):1-16.
[3]Xue Yingcheng,Tai Nengling.Review of contribution to frequency control through variable speed wind turbine[J].Renewable Energy,2011,36(6):1671-1677.
[4]张丽英,叶廷路,辛耀中,等.大规模风电接入电网的相关问题及措施[J].中国电机工程学报,2010,30(25):1-9.Zhang Liying,Ye Tinglu,Xin Yaozhong,et al.Problems and measures of power grid accommodating large scale wind power[J].Proceedings of the CSEE,2010,30(25):1-9(in Chinese).
[5]Mauricio J M,Marano A,Gomez-Exposito A,et al.Frequency regulation contribution through variable-speed wind energy conversion systems[J].IEEE Transactions on Power Systems,2009,24(1):173-180.
[6]中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会.GB/T 19963-2011风电场接入电力系统技术规定[S].北京:中国标准出版社,2012.General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China,Standardization Administration of the People's Republic of China.GB/T 19963-2011 Technical rule for connecting wind farm to power system[S].Beijing:Standards Press of China,2012(in Chinese).
[7]Ebrahimi F M,Khayatiyan A,Farjah E.A novel optimizing power control strategy for centralized wind farm control system[J].Renewable Energy,2016,86:399-408.
[8]张伯明,吴文传,郑太一,等.消纳大规模风电的多时间尺度协调的有功调度系统设计[J].电力系统自动化,2011,35(1):1-6.Zhang Boming,Wu Wenchuan,Zheng Taiyi,et al.Design of a multi-time scale coordinated active power dispatching system for accommodating large scale wind power penetration[J].Automation of Electric Power Systems,2011,35(1):1-6(in Chinese).
[9]Makarov Y V,Du Pengwei,Kintner-Meyer M C W,et al.Sizing energy storage to accommodate high penetration of variable energy resources[J].IEEE Transactions on Sustainable Energy,2012,3(1):34-40.
[10]何成明,王洪涛,韦仲康,等.风电场与AGC机组分布式协同实时控制[J].中国电机工程学报,2015,35(2):302-309.He Chengming,Wang Hongtao,Wei Zhongkang,et al.Distributed coordinated real-time control of wind farm and AGC units[J].Proceedings of the CSEE,2015,35(2):302-309(in Chinese).
[11]Wang Ye,Delille G,Bayem H,et al.High wind power penetration in isolated power systems-assessment of wind inertial and primary frequency responses[J].IEEETransactions on Power Systems,2013,28(3):2412-2420.
[12]Wu Ziping,Gao Wenzhong,Wang Jianhui,et al.Acoordinated primary frequency regulation from permanent magnet synchronous wind turbine generation[C]//Proceedings of 2012 IEEE Power Electronics and Machines in Wind Applications.Denver,Co,USA:IEEE,2012:1-6.
[13]Chang-Chien L R,Sun C C,Yeh Y J.Modeling of wind farm participation in AGC[J].IEEE Transactions on Power Systems,2014,29(3):1204-1211.
[14]赵晶晶,吕雪,符杨,等.基于双馈感应风力发电机虚拟惯量和桨距角联合控制的风光柴微电网动态频率控制[J].中国电机工程学报,2015,35(15):3815-3822.Zhao Jingjing,LüXue,Fu Yang,et al.Dynamic frequency control strategy of wind/photovoltaic/diesel microgrid based on DFIG virtual inertia control and pitch angle control[J].Proceedings of the CSEE,2015,35(15):3815-3822(in Chinese).
[15]付媛,王毅,张祥宇,等.变速风电机组的惯性与一次调频特性分析及综合控制[J].中国电机工程学报,2014,34(27):4706-4716.Fu Yuan,Wang Yi,Zhang Xiangyu,et al.Analysis and integrated control of inertia and primary frequency regulation for variable speed wind turbines[J].Proceedings of the CSEE,2014,34(27):4706-4716(in Chinese).
[16]刘吉臻,姚琦,柳玉,等.风火联合调度的风电场一次调频控制策略研究[J].中国电机工程学报,2017,37(12):3462-3469.Liu Jizhen,Yao Qi,Liu Yu,et al.Wind farm primary frequency control strategy based on wind&thermal power joint control[J].Proceedings of the CSEE,2017,37(12):3462-3469(in Chinese).
[17]席裕庚.预测控制[M].2版.北京:国防工业出版社,2013.Xi Yugeng.Predictive control[M].2nd ed.Beijing:National Defense Industry Press,2013(in Chinese).
[18]叶林,任成,李智,等.风电场有功功率多目标分层递阶预测控制策略[J].中国电机工程学报,2016,36(23):6327-6336.Ye Lin,Ren Cheng,Li Zhi,et al.Stratified progressive predictive control strategy for multi-objective dispatching active power in wind farm[J].Proceedings of the CSEE,2016,36(23):6327-6336(in Chinese).
[19]叶林,张慈杭,汤涌,等.多时空尺度协调的风电集群有功分层预测控制方法[J].中国电机工程学报,2018,38(13):3767-3780.Ye Lin,Zhang Cihang,Tang Yong,et al.Active power stratification predictive control approach for wind power cluster with multiple temporal and spatial scale coordination[J].Proceedings of the CSEE,2018,38(13):3767-3780(in Chinese).
[20]叶林,李智,汤涌,等.基于随机预测控制理论和功率波动相关性的风电集群优化调度[J].中国电机工程学报,2018,38(11):3172-3183.Ye Lin,Li Zhi,Tang Yong,et al.Optimal dispatch of system integrated wind farm clusters based on stochastic model predictive control considering temporal correlation of wind power[J].Proceedings of the CSEE,2018,38(11):3172-3183(in Chinese).
[21]孙舶皓,汤涌,仲悟之,等.基于分布式模型预测控制的包含大规模风电集群互联系统超前频率控制策略[J].中国电机工程学报,2017,37(21):6291-6302.Sun Bohao,Tang Yong,Zhong Wuzhi,et al.Multi-area interconnected power system advanced frequency control strategy considering large scale wind power cluster integration based on DMPC[J].Proceedings of the CSEE,2017,37(21):6291-6302(in Chinese).
[22]涂序彦,王枞,郭燕慧.大系统控制论[M].北京:北京邮电大学出版社,2005.Tu Xuyan,Wang Zong,Guo Yanhui.Large systems cybernetics[M].Beijing:Beijing University of Posts and Telecommunications Press,2005(in Chinese).
[23]Gautam D,Goel L,Ayyanar R,et al.Control strategy to mitigate the impact of reduced inertia due to doubly fed induction generators on large power systems[J].IEEETransactions on Power Systems,2011,26(1):214-224.
[24]李志刚,吴文传,张伯明.消纳大规模风电的鲁棒区间经济调度:(一)调度模式与数学模型[J].电力系统自动化,2014,38(20):33-39.Li Zhigang,Wu Wenchuan,Zhang Boming.A robust interval economic dispatch method accommodating large-scale wind power generation:part one dispatch scheme and mathematical model[J].Automation of Electric Power Systems,2014,38(20):33-39(in Chinese).
[25]李军军,吴政球.风电参与一次调频的小扰动稳定性分析[J].中国电机工程学报,2011,31(13):1-9.Li Junjun,Wu Zhengqiu.Small signal stability analysis of wind power generation participating in primary frequency regulation[J].Proceedings of the CSEE,2011,31(13):1-9(in Chinese).
[26]Ye Lin,Zhao Yongming,Zeng Cheng,et al.Short-term wind power prediction based on spatial model[J].Renewable Energy,2017,101:1067-1074.
[27]叶林,朱倩雯,赵永宁.超短期风电功率预测的自适应指数动态优选组合模型[J].电力系统自动化,2015,39(20):12-18.Ye Lin,Zhu Qianwen,Zhao Yongning.Dynamic optimal combination model considering adaptive exponential for ultra-short term wind power prediction[J].Automation of Electric Power Systems,2015,39(20):12-18(in Chinese).
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