可再生能源2024，Vol.42Issue(4)：471-478,8.
基于TOPSIS-GRNN的机理-数据混合驱动光伏电站功率预测
Power prediction of mechanism-data hybrid drive photovoltaic power plant based on TOPSIS-GRNN
摘要
Abstract
The article addresses the problem of relatively low accuracy of traditional PV power prediction and proposes a hybrid TOPSIS-GRNN based mechanism-data driven PV plant power prediction model.Firstly,the correlation analysis of several meteorological indicators and the output power of PV power plant is carried out,and the meteorological data with high correlation is selected as the input factor of the model.The TOPSIS algorithm was used to select the optimal similar days,and then the theoretical values of their PV plant output power and meteorological data were used to build the GRNN prediction model.Finally,the model was simulated and validated by combining the historical meteorological data and power data on the DKASC website.The final test results yielded an average power prediction accuracy of 0.8269 kW for RMSE,3.45%for MAPE and 0.019 5 kW for MAE.The prediction accuracy of this forecasting method is significantly higher than that of a single forecasting model and has some theoretical and practical value.关键词
光伏功率预测/TOPSIS法/最佳相似日/GRNNKey words
photovoltaic power prediction/TOPSIS/best similar day/GRNN分类
能源科技引用本文复制引用
柳想,陈春玲,王慧,陈浩楠..基于TOPSIS-GRNN的机理-数据混合驱动光伏电站功率预测[J].可再生能源,2024,42(4):471-478,8.基金项目
辽宁省科学研究经费项目(LJKZ0681). （LJKZ0681）
