Speaker
Yong Wang
(Nanjing University of Information Science and Technology)
Description
Post-processing methods are implemented at wind/solar farm for the power forecast. We propose two forecasting frameworks based on EMOS and neural network (NN). Boosting technique is applied for selection of the variables in the EMOS approach. The NN approach uses a multilayer perceptron model, where the training process is specifically tailored to the limited dataset size of one year by utilizing a similarity-based custom validation set. The power forecasts are customer-oriented evaluated, and compared with the commercialized product. The results will be shown at the workshop.
Primary author
Ziqiang Huo
(Nanjing University of Information Science and Technology)
Co-authors
Jieyu Chen
(Nanjing University of Information Science and Technology)
Yong Wang
(Nanjing University of Information Science and Technology)
