Text mining is an emerging topic that advances the review of academic literature. This paper
presents a preliminary study on how to review solar irradiance and photovoltaic (PV) power …

Energy communities will play a central role in the sustainable energy transition by helping
inform and engage end users to become more responsible consumers of energy. However …

Making the Black Box More Transparent: Understanding the Physical Implications of Machine
Learning in: Bulletin of the American Meteorological Society Volume 100 Issue 11 (2019) Jump …

Summary pvlib python is a community-supported open source tool that provides a set of
functions and classes for simulating the performance of photovoltaic energy systems. pvlib …

Given the growing use of Artificial intelligence (AI) and machine learning (ML) methods
across all aspects of environmental sciences, it is imperative that we initiate a discussion …

With the boom in Internet techniques and computer science, a variety of big data have been
introduced into forecasting research, bringing new knowledge and improving prediction …

Over the past decade, significant progress in solar forecasting has been made.
Nevertheless, there are concerns about duplication, long-term value, and reproducibility; this …

Increasing penetration of distributed renewable power means that reliable generation
forecasts are required for grid operation. The present work aims at combining state of the art …

The design of a Building Integrated Photovoltaic (BIPV) system involves considering various
factors such as geophysical, technical, economic, and environmental aspects throughout its …

The exponential growth of solar power has been witnessed in the past decade and is
projected by the ambitious policy targets. Nevertheless, the proliferation of solar energy …