计及控制时间窗内功率波动的风电场群无功电压分层优化控制
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摘要
针对因风电场群的无功电压控制指令周期远大于风电场内有功无功控制周期而造成的场群电压控制指令没有考虑控制周期内有功出力波动带来的节点电压变化的问题,提出一种考虑控制时间窗内电压波动的大规模风电场群无功电压优化控制策略。区域场群控制层采用模型预测控制技术,通过对控制窗内风电出力的动态预测,求取控制窗内从当前至未来多个时刻的中枢点电压偏差和总网损的最优无功控制向量,然后对各风场下达当前无功控制指令。各风场进行自主优化跟踪。通过实时滚动优化,达到总体优化控制效果。在RT-Lab仿真平台上建立由9个大型风电场组成的场群模型,验证了所提出的控制策略比常规优化控制有更好的全局电压优化控制效果,可降低由于风电波动而产生的无功电压事故的风险。
Since the interval of voltage control of wind farm clusters(WFC) is much longer than that of wind farms, the voltage control instruction for wind farms fails to consider the voltage fluctuation caused by wind power in cluster control interval. Therefore, this paper proposes a kind of model predictive control(MPC) for the voltage optical control of a large scale WFC considering voltage fluctuation in a control time window. The MPC is used in the layer of WFC control to predict the wind power fluctuation of wind farms and calculate the optical reactive power control vectors,which optimizes the nodes voltage deviation and overall power losses from the current time to several future time in a control interval. Then the wind farm control instruction is extracted from the vectors.Wind farms in the cluster will track it autonomously. Thus, the overall optimal control will be realized through real time receding horizon optimization. Finally, the proposed control and regular control are compared by simulations with the WFC model including 9 wind farms on the RT-Lab platform. It is shown that the proposed control has better global optimal results for WFC voltage control that can reduce the risk of voltage instability.
Since the interval of voltage control of wind farm clusters(WFC) is much longer than that of wind farms, the voltage control instruction for wind farms fails to consider the voltage fluctuation caused by wind power in cluster control interval. Therefore, this paper proposes a kind of model predictive control(MPC) for the voltage optical control of a large scale WFC considering voltage fluctuation in a control time window. The MPC is used in the layer of WFC control to predict the wind power fluctuation of wind farms and calculate the optical reactive power control vectors,which optimizes the nodes voltage deviation and overall power losses from the current time to several future time in a control interval. Then the wind farm control instruction is extracted from the vectors.Wind farms in the cluster will track it autonomously. Thus, the overall optimal control will be realized through real time receding horizon optimization. Finally, the proposed control and regular control are compared by simulations with the WFC model including 9 wind farms on the RT-Lab platform. It is shown that the proposed control has better global optimal results for WFC voltage control that can reduce the risk of voltage instability.
引文
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[13]孙宏斌,张伯明,吴文传,等.自律协同的智能电网能量管理系统家族概念、体系架构和示例[J].电力系统自动化,2014,38(9):1-5.Sun Hongbin,Zhang Boming,Wu Wenchuan,et al.Autonomous-synergetic energy management system family for smart grids:concept,architecture and cases[J].Automation of Electric Power Systems,2014,38(9):1-5.
[14]郭庆来,王彬,孙宏斌,等.支撑大规模风电集中接入的自律协同电压控制技术[J].电力系统自动化,2015,39(1):88-93.Guo Qinglai,Wang Bin,Sun Hongbin,et al.Autonomous-synergetic voltage control technology supporting large-scale wind power integration[J].Automation of Electric Power Systems,2015,39(1):88-93.
[15]席裕庚.预测控制[M].北京:国防工业出版社,1993.
[16]金涛,沈学宇,苏泰新,等.不平衡电网下并网逆变器的模型预测电流限幅灵活控制[J].电工技术学报,2019,DOI:10.19595/j.cnki.1000-6753.tces.180248.Jin Tao,Shen Xueyu,Su Taixin,et al.Flexible model predictive control with peak current limitation for grid-connected inverter under unbalanced grid voltage[J].Transactions of China Electrotechnical Society,2019,DOI:10.19595/j.cnki.1000-6753.tces.180248.
[17]冯凯,应展烽,陈汹,等.计及线路热惯性效应的模型预测控制安全经济调度模型[J].电工技术学报,2018,33(8):1875-1883.Feng Kai,Ying Zhanfeng,Chen Xiong,et al.Model predictive control security economic dispatch model considering transmission line thermal inertia effect[J]Transactions of China Electrotechnical Society,2018,33(8):1875-1883.
[18]黄帅.风电场超短期功率预测方法的研究[D].成都:电子科技大学,2012.
[19]卢芸.超短期风电预测及考虑风速预测的惯性控制研究[D].成都:西南交通大学,2017.
[20]娜仁图雅.风电场功率时间序列分析及预测方法研究[D].天津:天津大学,2017.
[21]陈昊,万秋兰,王玉荣.基于厚尾均值广义自回归条件异方差族模型的短期风电功率预测[J].电工技术学报,2016,31(5):91-98.Chen Hao,Wan Qiulan,Wang Yurong.Short-term wind power forecast based on fat-tailed generalized autoregressive conditional heteroscedasticity-in-mean type models[J].Transactions of China Electrotechnical Society,2016,31(5):91-98.
[22]刘天琪,邱晓燕.电力系统分析理论[M].北京:科学出版社,2005.
[23]夏玥,李征,蔡旭,等.基于直驱式永磁同步发电机组的风电场动态建模[J].电网技术,2014,38(6):1439-1445.Xia Yue,Li Zheng,Cai Xu,et al.Dynamic modeling of wind farm composed of direct-driven permanent magnet synchronous generators[J].Power System Technology,2014,38(6):1439-1445.
[2]邹志翔,周克亮,袁晓冬.风电场接入对周边地区电网电压稳定性的影响分析[J].电网技术,2011,35(11):50-56.Zou Zhixiang,Zhou Keliang,Yuan Xiaodong.Analysis on influences of grid-connected wind farm on voltage stability of local power network neighboring to connection point[J].Power System Technology,2011,35(11):50-56.
[3]杨硕,王伟胜,刘纯,等.双馈风电场无功电压协调控制策略[J].电力系统自动化,2013,37(12):1-6.Yang Shuo,Wang Weisheng,Liu Chun,et al Coordinative control strategy for reactive power and voltage of wind farms with doubly-fed induction generator[J].Automation of Electric Power Systems,2013,37(12):1-6.
[4]柳杰,刘志刚,孙婉璐,等.含风电场电力系统电压稳定性概率评估及其在无功优化中的应用[J].电网技术,2012,36(11):134-139.Liu Jie,Liu Zhigang,Sun Wanlu,et al.Probability assessment on voltage stability of power grid containing wind farms and its application in reactive power optimization[J].Power System Technology,2012,36(11):134-139.
[5]严干贵,孙兆键,穆钢,等.面向集电系统电压调节的风电场无功电压控制策略[J].电工技术学报,2015,30(18):140-146.Yan Gangui,Sun Zhaojian,Mu Gang,et al.Collector system voltage regulation oriented reactive power control strategy for wind farm[J].Transactions of China Electrotechnical Society,2015,30(18):140-146.
[6]Pappala V S,Nakawiro W,Erlich I.Predictive optimal control of wind farm reactive sources[C]//IEEE/PES Transmission and Distribution Conference and Exhibition:Smart Solutions for a Changing World,New Orleans,USA,2010:1-7.
[7]陈惠粉,乔颖,鲁宗相,等.风电场群的无功电压协调控制策略[J].电力系统自动化,2010,34(18):78-83.Chen Huifen,Qiao Ying,Lu Zongxiang,et al.Study on reactive power and voltage coordinated control strategy of wind farm group[J].Automation of Electric Power Systems,2010,34(18):78-83.
[8]陈惠粉,张毅威,闵勇,等.集群双馈风电场的分次调压控制[J].电力系统自动化,2013,37(4):7-13.Chen Huifen,Zhang Yiwei,Min Yong,et al.Granded voltage control strategy for clustering wind farms based on doubly-fed induction generators[J].Automation of Electric Power Systems,2013,37(4):7-13.
[9]杨硕,王伟胜,刘纯,等.改善风电汇集系统静态电压稳定性的无功电压协调控制策略[J].电网技术,2014,38(5):1250-1256.Yang Shuo,Wang Weisheng,Liu Chun,et al Coordinative strategy of reactive power and voltage control for improving static voltage stability of wind power centralized system[J].Power System Technology,2014,38(5):1250-1256.
[10]崔杨,彭龙,仲悟之,等.双馈型风电场群无功分层协调控制策略[J].中国电机工程学报,2015,35(17):4300-4307.Cui Yang,Peng Long,Zhong Wuzhi,et al.Coordination strategy of reactive power control on wind farms based doubly fed induction generator[J].Proceedings of the CSEE,2015,35(17):4300-4307.
[11]王琦,袁越,陈宁,等.多风电场接入局部电网的无功协调分配方法[J].电力系统保护与控制,201240(24):76-82.Wang Qi,Yuan Yue,Chen Ning,et al.The cooperating distribution methods of reactive power in multi-wind farms integrated region[J].Power System Protection and Control,2012,40(24):76-82.
[12]杨硕,王伟胜,刘纯,等.计及风电功率波动影响的风电场集群无功电压协调控制策略[J].中国电机工程学报,2014,34(28):4761-4769.Yang Shuo,Wang Weisheng,Liu Chun,et al.Coordinative strategy for reactive power and voltage control of wind farms cluster considering wind power fluctuation[J].Proceedings of the CSEE,2014,34(28):4761-4769.
[13]孙宏斌,张伯明,吴文传,等.自律协同的智能电网能量管理系统家族概念、体系架构和示例[J].电力系统自动化,2014,38(9):1-5.Sun Hongbin,Zhang Boming,Wu Wenchuan,et al.Autonomous-synergetic energy management system family for smart grids:concept,architecture and cases[J].Automation of Electric Power Systems,2014,38(9):1-5.
[14]郭庆来,王彬,孙宏斌,等.支撑大规模风电集中接入的自律协同电压控制技术[J].电力系统自动化,2015,39(1):88-93.Guo Qinglai,Wang Bin,Sun Hongbin,et al.Autonomous-synergetic voltage control technology supporting large-scale wind power integration[J].Automation of Electric Power Systems,2015,39(1):88-93.
[15]席裕庚.预测控制[M].北京:国防工业出版社,1993.
[16]金涛,沈学宇,苏泰新,等.不平衡电网下并网逆变器的模型预测电流限幅灵活控制[J].电工技术学报,2019,DOI:10.19595/j.cnki.1000-6753.tces.180248.Jin Tao,Shen Xueyu,Su Taixin,et al.Flexible model predictive control with peak current limitation for grid-connected inverter under unbalanced grid voltage[J].Transactions of China Electrotechnical Society,2019,DOI:10.19595/j.cnki.1000-6753.tces.180248.
[17]冯凯,应展烽,陈汹,等.计及线路热惯性效应的模型预测控制安全经济调度模型[J].电工技术学报,2018,33(8):1875-1883.Feng Kai,Ying Zhanfeng,Chen Xiong,et al.Model predictive control security economic dispatch model considering transmission line thermal inertia effect[J]Transactions of China Electrotechnical Society,2018,33(8):1875-1883.
[18]黄帅.风电场超短期功率预测方法的研究[D].成都:电子科技大学,2012.
[19]卢芸.超短期风电预测及考虑风速预测的惯性控制研究[D].成都:西南交通大学,2017.
[20]娜仁图雅.风电场功率时间序列分析及预测方法研究[D].天津:天津大学,2017.
[21]陈昊,万秋兰,王玉荣.基于厚尾均值广义自回归条件异方差族模型的短期风电功率预测[J].电工技术学报,2016,31(5):91-98.Chen Hao,Wan Qiulan,Wang Yurong.Short-term wind power forecast based on fat-tailed generalized autoregressive conditional heteroscedasticity-in-mean type models[J].Transactions of China Electrotechnical Society,2016,31(5):91-98.
[22]刘天琪,邱晓燕.电力系统分析理论[M].北京:科学出版社,2005.
[23]夏玥,李征,蔡旭,等.基于直驱式永磁同步发电机组的风电场动态建模[J].电网技术,2014,38(6):1439-1445.Xia Yue,Li Zheng,Cai Xu,et al.Dynamic modeling of wind farm composed of direct-driven permanent magnet synchronous generators[J].Power System Technology,2014,38(6):1439-1445.