摘要
针对电导增量法(incremental conductance,INC)的震荡与误判问题,结合变步长INC算法与功率预测,提出一种改进的基于功率预测的INC算法。根据最大功率跟踪控制的工作点所处区域位置和电导率的变动幅度改变算法步长,当太阳光照强度剧烈变化时,基于功率预测电流值,使工作点维持在一条动态的I-U输出特性曲线上,从而克服误判,提高算法的跟踪速度和精度。仿真结果表明,改进的INC算法相比于传统INC算法在跟踪时间上缩短了40%,跟踪精度提高约20%。基于此最大功率跟踪控制环节,建立基于IEEE 14节点的光伏并网模型,分析发现在同等接入容量条件下,光伏接入系统线路末端对系统电压质量有很大影响。
To solve the problem of the fluctuation and misjudgment of the incremental conductance algorithm(INC),combined with variable step size INC algorithm and power prediction,an improved INC prediction algorithm based on power prediction is proposed.The step size of the algorithm was changed according to the location of the operating point of the maximum power point tracking control and the variation range of the conductivity.When the sunlight intensity changed sharply,the working point was maintained on a dynamic I-U output characteristic curve based on the power prediction current value,so as to overcome misjudgment and improve the tracking speed and accuracy of the algorithm.Simulation results show that compared with the traditional INC algorithm,the improved INC algorithm could shorten the tracking time by 40%and improve the tracking accuracy by about 20%.Based on the maximum power point tracking control link,a photovoltaic grid connected model based on IEEE 14-nodes was established.The analysis shows that the end of the photovoltaic access system has a great impact on the system voltage quality under the same access capacity.
作者
贺兴民
何柏娜
崔荣喜
张婧茹
董彦辰
HE Xingmin;HE Baina;CUI Rongxi;ZHANG Jingru;DONG Yanchen(College of Electric and Electronic Engineering, Shandong University of Technology, Zibo, Shandong 255000, China;Smart Grid Rizhao Power Supply Company, Rizhao, Shandong 276826, China)
出处
《中国科技论文》
CAS
北大核心
2020年第11期1283-1288,1295,共7页
China Sciencepaper
基金
山东省研究生教育质量提升计划项目(SDYKC19103)
国家电网公司科技资助项目(SGSDDY00FCJS2000199)。
关键词
太阳能发电
最大功率跟踪
电导增量法
功率预测
光伏并网
solar power
maximum power point tracking
incremental conductance(INC)
power prediction
photovoltaic grid connection
