Prediction for Day-ahead Power of Distributed Rooftop Photovoltaic Considering Occlusion Factors
In view of the difference of output characteristics of distributed PV users due to the occlusion problem of distributed rooftop photovoltaic(PV)installation,a day-ahead prediction model of distributed rooftop PV power with substation bus level considering the occlusion factor is proposed.Firstly,the start time and cut-off time of daily PV output are calculated according to the latitude and longitude of the substation.Secondly,according to the historical power data of each PV user,the influence of the surrounding buildings on the photovoltaic occlusion is analyzed,and the shape distance is used as the metric to carry out the co-hesive hierarchical clustering.Then,the irradiance data is used to establish a Back Propagation(BP)power prediction model for each type of distributed photovoltaic user,and the power prediction value is corrected by the Long Short-Term Memory(LSTM)neural network to obtain the final predicted value.Finally,the prediction results of each type of distributed roof are added to obtain the day-ahead power prediction of distributed rooftop PV with the substation bus level.Using the actual photo-voltaic power station for case analysis,the results show that high accuracy of the prediction method proposed in this paper rea-ches,and the Root Mean Squared Error(RMSE)is significantly reduced compared with the prediction method without consid-ering the occlusion factor.
day-ahead power forecastocclusion factorcondensation hierarchical clusteringshape distanceBP-LSTM prdeic-tion model
NETL
NSTL
万方数据
