基于模型预测控制的多时间尺度无功电压优化控制方法
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摘要
针对高比例风电接入下电网电压快速、频繁波动的问题,提出了基于模型预测控制(MPC)的多时间尺度电网无功电压优化控制方法。在日前优化安排离散无功补偿设备的基础上,日内采用基于MPC的滚动优化及校正控制思路,利用连续无功补偿装置对电压进行控制。首先,建立基于灵敏度的电网电压预测模型,预测得到未来多个时刻的电网电压运行状态;然后,以未来多个时刻的电网电压预计控制偏差最小为优化目标,建立日内滚动优化控制模型,求解得到连续无功补偿装置的无功控制计划,并通过电压控制偏差校正,完成日内无功电压模型预测控制;最后,以我国"三北"地区某风电场集群为例进行仿真计算,通过与传统电压控制方法进行对比,验证所提方法在提高电压控制水平方面的可行性和有效性。
Aiming at the problem of rapid and frequent fluctuation of grid voltage under high proportion wind power interconnection,a multi-time scale optimal control method of reactive power and voltage based on MPC(Model Predictive Control) is proposed. Based on the day-ahead optimal arrangement of discrete reactive power compensation equipment,the voltage is controlled by continuous reactive power compensation equipment within the intra-day time scale,which adopts the idea of rolling optimization and correcting control based on MPC. Firstly,the grid voltage foresting model based on sensitivity is established to forecast the voltage states at multiple future moments. Then,the intra-day rolling optimization model is built with the minimum expected voltage control deviation at multiple future moments as its optimization objective,based on which,the reactive power control planning of continuous reactive power compensation equipment is obtained. The intra-day MPC of reactive power and voltage is realized by correcting the voltage control deviation. Finally,a wind power cluster system in "three northern"regions of China is taken as the example,whose simulative results verify the feasibility and effectiveness of the proposed method in improving the voltage control level by comparing with the traditional voltage control method.
Aiming at the problem of rapid and frequent fluctuation of grid voltage under high proportion wind power interconnection,a multi-time scale optimal control method of reactive power and voltage based on MPC(Model Predictive Control) is proposed. Based on the day-ahead optimal arrangement of discrete reactive power compensation equipment,the voltage is controlled by continuous reactive power compensation equipment within the intra-day time scale,which adopts the idea of rolling optimization and correcting control based on MPC. Firstly,the grid voltage foresting model based on sensitivity is established to forecast the voltage states at multiple future moments. Then,the intra-day rolling optimization model is built with the minimum expected voltage control deviation at multiple future moments as its optimization objective,based on which,the reactive power control planning of continuous reactive power compensation equipment is obtained. The intra-day MPC of reactive power and voltage is realized by correcting the voltage control deviation. Finally,a wind power cluster system in "three northern"regions of China is taken as the example,whose simulative results verify the feasibility and effectiveness of the proposed method in improving the voltage control level by comparing with the traditional voltage control method.
引文
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[13]张忠,王建学.采用模型预测控制的微电网有功无功联合实时调度方法[J].中国电机工程学报,2016,36(24):6743-6750,6928.ZHANG Zhong,WANG Jianxue. An active and reactive power joint real-time dispatch approach for microgrid using model predictive control[J]. Proceedings of the CSEE,2016,36(24):6743-6750,6928.
[14]明杰,向红吉,戴朝华,等.多风电场接入的灵敏度场景静态无功/电压评估[J].电力自动化设备,2017,37(12):102-108,115.MING Jie,XIANG Hongji,DAI Chaohua,et al. Static reactive power/voltage assessment of sensitivity scenarios with multiple wind farms[J]. Electric Power Automation Equipment,2017,37(12):102-108,115.
[15]徐岩,郅静,樊世通.基于功率灵敏度和经济补偿最小化的线路过负荷紧急控制方法[J].电力自动化设备,2017,37(1):118-123.XU Yan,ZHI Jing,FAN Shitong. Line overload emergency control based on power sensitivity and minimized economic compensation[J]. Electric Power Automation Equipment,2017,37(1):118-123.
[16]方润生,任云霞,王世英.用对偶单纯形算法解装卸工问题[J].山西大学学报(自然科学版),2010,33(4):519-524.FANG Runsheng,REN Yunxia,WANG Shiying. Solving the loader problem by dual simplex[J]. Journal of Shanxi University(Natural Science Edition),2010,33(4):519-524.
[2]钱臻,刘建坤,陈静,等.计及风电不确定性的含UPFC电力系统的两阶段最优潮流[J].电力自动化设备,2017,37(3):80-86.QIAN Zhen,LIU Jiankun,CHEN Jing,et al. Two-stage OPF considering wind-power uncertainty for power system with UPFC[J].Electric Power Automation Equipment,2017,37(3):80-86.
[3]薛禹胜,雷兴,薛峰,等.关于风电不确定性对电力系统影响的评述[J].中国电机工程学报,2014,34(29):5029-5040.XUE Yusheng,LEI Xing,XUE Feng,et al. A review on impacts of wind power uncertainties on power systems[J]. Proceedings of the CSEE,2014,34(29):5029-5040.
[4]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.
[5]刘文颖,郭鹏,但扬清,等.含大规模风电接入电网的双时间尺度无功协调控制[J].可再生能源,2016,34(12):1811-1818.LIU Wenying,GUO Peng,DAN Yangqing,et al. Double-time scale reactive power control with large-scale wind power integrated into grid[J]. Renewable Energy Resources,2016,34(12):1811-1818.
[6]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.
[7]陈惠粉,乔颖,闵勇,等.风电场动静态无功补偿协调控制策略[J].电网技术,2013,37(1):248-254.CHEN Huifen,QIAO Ying,MIN Yong,et al. Study on coordinated control strategy of dynamic and static reactive compensation in wind farm[J]. Power System Technology,2013,37(1):248-254.
[8]PAPPALA V S,NAKAWIRO W,ERLICH I. Predictive optimal control of wind farm reactive sources[C]∥2010 IEEE/PES Transmission and Distribution Conference and Exhibition. New Orleans,LA,USA:IEEE,2010:1-7.
[9]杨兴武,冀红超,甘伟.基于模型预测控制的并网逆变器开关损耗优化方法[J].电力自动化设备,2015,35(8):84-89.YANG Xingwu,JI Hongchao,GAN Wei. Switching loss optimization based on model predictive control for grid-connected inverter[J].Electric Power Automation Equipment,2015,35(8):84-89.
[10]肖浩,裴玮,孔力.基于模型预测控制的微电网多时间尺度协调优化调度[J].电力系统自动化,2016,40(18):7-14,55.XIAO Hao,PEI Wei,KONG Li. Multi-time scale coordinated optimal dispatch of microgrid based on model predictive control[J].Automation of Electric Power Systems,2016,40(18):7-14,55.
[11]董雷,陈卉,蒲天骄,等.基于模型预测控制的主动配电网多时间尺度动态优化调度[J].中国电机工程学报,2016,36(17):4609-4617.DONG Lei,CHEN Hui,PU Tianjiao,et al. Multi-time scale dynamic optimal dispatch in active distribution network based on model predictive control[J]. Proceedings of the CSEE,2016,36(17):4609-4617.
[12]张伯明,陈建华,吴文传.大规模风电接入电网的有功分层模型预测控制方法[J].电力系统自动化,2014,38(9):6-14.ZHANG Boming,CHEN Jianhua,WU Wenchuan. A hierarchical model predictive control method of active power for accommodating largescale wind power integration[J]. Automation of Electric Power Systems,2014,38(9):6-14.
[13]张忠,王建学.采用模型预测控制的微电网有功无功联合实时调度方法[J].中国电机工程学报,2016,36(24):6743-6750,6928.ZHANG Zhong,WANG Jianxue. An active and reactive power joint real-time dispatch approach for microgrid using model predictive control[J]. Proceedings of the CSEE,2016,36(24):6743-6750,6928.
[14]明杰,向红吉,戴朝华,等.多风电场接入的灵敏度场景静态无功/电压评估[J].电力自动化设备,2017,37(12):102-108,115.MING Jie,XIANG Hongji,DAI Chaohua,et al. Static reactive power/voltage assessment of sensitivity scenarios with multiple wind farms[J]. Electric Power Automation Equipment,2017,37(12):102-108,115.
[15]徐岩,郅静,樊世通.基于功率灵敏度和经济补偿最小化的线路过负荷紧急控制方法[J].电力自动化设备,2017,37(1):118-123.XU Yan,ZHI Jing,FAN Shitong. Line overload emergency control based on power sensitivity and minimized economic compensation[J]. Electric Power Automation Equipment,2017,37(1):118-123.
[16]方润生,任云霞,王世英.用对偶单纯形算法解装卸工问题[J].山西大学学报(自然科学版),2010,33(4):519-524.FANG Runsheng,REN Yunxia,WANG Shiying. Solving the loader problem by dual simplex[J]. Journal of Shanxi University(Natural Science Edition),2010,33(4):519-524.