一种改进的光水互补控制策略研究
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摘要
多能源互补发电具有优良的特性,在电网发电体系中的比例逐渐提高,部分地区出现了光水联合发电的情况,但是输出电流波动较大,谐波含量较高,控制精度不足。针对这些情况,提出了一种改进的光水互补控制策略,通过充分利用二者的优势,让光伏以电量支持水电,水电以容量调节光伏,对其进行出力行补偿,并提出了一种改进型的光水互补控制策略。该策略利用神经网络预测光伏第二天的输出功率,提前知晓大致波动情况,采用电压环和电流环构成双环控制,用比例积分环节替换掉原有的比例环节,通过反馈实时跟踪并网输出功率,实现无差调节,并通过AGC对水力发电进行出力的分配。最后通过Matlab建模进行仿真分析,仿真结果表明该控制方法是可行性的、有效性的。
Multi-energy complementary power generation has excellent characteristics,and the proportion in the power generation system of power grid is gradually increasing. In some areas, light-water combined power generation occurs. However, the output current fluctuates greatly,the harmonic content is higher, and the control precision is not sufficient. In view of these circumstances, an improved light-water complementary control strategy is proposed. By making full use of the advantages of both, photovoltaic power is used to support hydropower, and hydropower is used to adjust photovoltaic power by capacity, and it is proposed for compensation.Using neural network to predict the output power of PV the next day,the general fluctuation is known in advance.The voltage loop and the current loop are used to form a double loop control. The original proportional part is replaced by the proportional integral part, and the output of the synchronous motor is fed back by the feedback in real time to realize no-difference adjustment and through the AGC to distribute the hydropower. Finally, through the Matlab modeling simulation analysis, the simulation results show that the proposed control method is feasible and effective.
Multi-energy complementary power generation has excellent characteristics,and the proportion in the power generation system of power grid is gradually increasing. In some areas, light-water combined power generation occurs. However, the output current fluctuates greatly,the harmonic content is higher, and the control precision is not sufficient. In view of these circumstances, an improved light-water complementary control strategy is proposed. By making full use of the advantages of both, photovoltaic power is used to support hydropower, and hydropower is used to adjust photovoltaic power by capacity, and it is proposed for compensation.Using neural network to predict the output power of PV the next day,the general fluctuation is known in advance.The voltage loop and the current loop are used to form a double loop control. The original proportional part is replaced by the proportional integral part, and the output of the synchronous motor is fed back by the feedback in real time to realize no-difference adjustment and through the AGC to distribute the hydropower. Finally, through the Matlab modeling simulation analysis, the simulation results show that the proposed control method is feasible and effective.
引文
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[2]陈峦.光伏电站-水电站互补发电系统的仿真研究[J].水力发电,2010,36(08):81-84.CHEN Luan.Simulation on complementary photovoltaichydro power generation system[J].Water Power,2010,36(08):81-84.
[3]WU C S,LIAO H,YANG Z L,et al.Research on control strategies of small-hydro/PV hybrid power system[C]Nanjing:International Conference on Sustainable Power Generation and Supply.UK-China Network of Clean Energy Research,2009:1-5.
[4]姚骏,杜红彪,周特,等.微网逆变器并联运行的改进下垂控制策略[J].电网技术,2015,39(4):932-938.YAO Jun,DU Hongbiao,ZHOU Te,et al.Improved droop control strategy for inverters parallel operation in microgrid[J].Power System Technology,2015,39(4):932-938.
[5]余志强,王淳,胡奕涛,等.并网光伏发电置信容量评估[J].电力系统保护与控制,2016,44(07):122-127.YU Zhiqiang,WANG Chun,HU Yitao,et al.Capacity credit evaluation of grid-connected photovoltaic generation[J].Power System Protection and Control,2016,44(07):122-127.
[6]党克,陆雯雯,严干贵.基于改进滑模控制技术的光伏阵列最大功率跟踪控制研究[J].广东电力,2016,29(10):12-16.DANG Ke,LU Wenwen,YAN Gangui.Maximum power point tracking of photovoltaic array based on improved sliding mode control technology[J].Guangdong Electric Power,2016,29(10):12-16.
[7]朱卫平,汪志成,袁晓冬,等.一种光伏功率预测的RBF神经网络校正模型[J].电子设计工程,2016,24(13):113-115+119.ZHU Weiping,WANG Zhicheng,YUAN Xiaodong,et al.A correction model to forecast output power of photovoltaic system based on RBF neural network[J].Electronic Design Engineering,2016,24(13):113-115+119.
[8]田旭,张祥成,白左霞,等.青海省水电与光伏互补特性分析与效果评价[J].电力建设,2015,36(10):67-72.TIAN Xu,ZHANG Xiangcheng,BAI Zuoxia,et al.Characteristic analysis and effect evaluation of synergy between hydropower and photovoltaic power in Qinghai province[J].Electric Power Construction,2015,36(10):67-72.
[9]韩柳,庄博,吴耀武,等.风光水火联合运行电网的电源出力特性及相关性研究[J].电力系统保护与控制,2016,44(19):91-98.HAN Liu,ZHUANG Bo,WU Yaowu,et al.Power source'soutput characteristics and relevance in wind-solar-hydrothermal power system[J].Power System Protection and Control,2016,44(19):91-98.
[10]马亮,李旭阳,卢远宏,等.釆用非线性控制的光伏并网逆变器低电压穿越[J].电子设计工程,2016,24(13):82-84.MA Liang,LI Xuyang,LU Yuanhong,et al.LVRT of photovoltaic grid-connected inverter adopting non-linear control[J].Electronic Design Engineering,2016,24(13):82-84.
[11]李鲁霞.多源微电网综合控制策略及其仿真研究[D].杭州,浙江工业大学,2013
[12]李春平,杨万清,梁英哲,等.风光储系统接人电网优化控制策略研究[J].中国电力,2013,46(9):138-141.LI Chunping,YANG Wanqing,LIANG Yingzhe,et al.Scenery storage systems connected to the grid optimization control strategy[J].Electric Power,2013,46(9):138-141.
[13]毕晓辉,孙韬,毛瑞,等.光储微电网混合储能系统的控制策略及开关优化[J].重庆大学学报,2016,39(6):11-18.BI Xiaohui,SUN Tao,MAO Rui,et al.Control strategy and protection switch optimization of hybrid energy storagesystem for PV-storage microgrid system[J].Journal of Chongqing University,2016,39(6):11-18.
[14]赵巍.微网综合控制技术研究[D].南京,南京理工大学,2013.
[15]KATIRAEI F,IRAVANI M R.Small-signal dynamic model of a micro-grid includingconventional and electronically interfaced distributed resources[J].Transmission&Distribution,2007,1(3):369-378.
[16]CAI C C,CHEN S C,DAI W L,et al.Optimal operation of microgrid composed of smallhydropower and photovoltaic generation with energy storagebased based on multiple scenarios technique[C].Beijing:2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies(DRPT):2185-2190.
[17]孙鹏.适应多元电源接人的电网AGC控制策略优化研究[D].北京,华北电力大学,2015.