Renewable Energy, Machine Learning, Satellite Image Processing

Direct Short-Term Forecast of Photovoltaic Power through a Comparative Study between COMS and Himawari-8 Meteorological Satellite Images in a Deep Neural Network

Meteorological satellite images provide crucial information on solar irradiation and weather conditions at spatial and temporal resolutions which are ideal for short-term photovoltaic (PV) power forecasts. Following the introduction of …

Short-Term Forecasting of Photovoltaic Power Integrating Multi-Temporal Meteorological Satellite Imagery in Deep Neural Network

Remotely-sensed satellite imagery offers crucial information on the atmosphere and the local environment, providing a broader perspective for more accurate photovoltaic (PV) power prediction. This study proposes a Deep Neural Network (DNN) framework …

Multimodal Merging of Satellite Imagery with Meteorological and Power Plant Data in Deep Convolutional Neural Network for Short-Term Solar Energy Prediction

Solar energy is a promising renewable energy source, but stable generation of photovoltaic (PV) power is largely impaired by meteorological phenomena. Ground-based weather measurements are limited in their ability to fully capture the unpredictable …