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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi
Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi
Electrical and Computer Engineering Faculty Research & Creative Works
Predicting solar irradiance has been an important topic in renewable energy generation. Prediction improves the planning and operation of photovoltaic systems and yields many economic advantages for electric utilities. The irradiance can be predicted using statistical methods such as artificial neural networks (ANN), support vector machines (SVM), or autoregressive moving average (ARMA). However, they either lack accuracy because they cannot capture long-term dependency or cannot be used with big data because of the scalability. This paper presents a method to predict the solar irradiance using deep neural networks. Deep recurrent neural networks (DRNNs) add complexity to the model without specifying …
Predicting Solar Irradiance Using Time Series Neural Networks, Ahmad Alzahrani, Jonathan W. Kimball, Cihan H. Dagli
Predicting Solar Irradiance Using Time Series Neural Networks, Ahmad Alzahrani, Jonathan W. Kimball, Cihan H. Dagli
Electrical and Computer Engineering Faculty Research & Creative Works
Increasing the accuracy of prediction improves the performance of photovoltaic systems and alleviates the effects of intermittence on the systems stability. A Nonlinear Autoregressive Network with Exogenous Inputs (NARX) approach was applied to the Vichy-Rolla National Airport's photovoltaic station. The proposed model uses several inputs (e.g. time, day of the year, sky cover, pressure, and wind speed) to predict hourly solar irradiance. Data obtained from the National Solar Radiation Database (NSRDB) was used to conduct simulation experiments. These simulations validate the use of the proposed model for short-term predictions. Results show that the NARX neural network notably outperformed the other …