Application of machine learning in solar energy

How can machine learning improve solar and wind energy production?

Machine learning applications for solar and wind energy generation are vital for sustainable energy production. Machine learning can help in design, optimization, cost reduction, and, most importantly, in improving the efficacy of solar and wind energy, including advancing energy storage.

Can machine learning be used in solar energy?

Numerous studies have shown the great potential applications of machine learning in the context of solar energy, as depicted in Table 1. TABLE 1. The various application of machine learning to solar energy. The proposed multistep CNN stacked LSTM model outperformed CNN and -LSTM models in both solar irradiance and POA irradiance prediction.

What is the role of machine learning in photovoltaic energy production?

Photovoltaic (PV) technologies are expected to play an increasingly important role in future energy production. In parallel, machine learning has gained prominence because of a combination of factors such as advances in computational hardware, data collection and storage, and data-driven algorithms.

Can machine learning predict future solar energy generation?

For reliable predictions of solar electricity generation, one must take into consideration changes in weather patterns over time. In this paper, a hybrid model that integrates machine learning and statistical approaches is suggested for predicting future solar energy generation.

Can machine learning predict solar radiation?

Due to the fact that solar radiation is a key source of solar energy, Voyant et al. investigated the application of machine learning algorithms in forecasting solar radiation. Several strategies for forecasting solar radiation have been described.

Can machine learning predict energy production based on weather variables?

This study explores five distinct machine learning (ML) models which are built and compared to predict energy production based on four independent weather variables: wind speed, relative humidity, ambient temperature, and solar irradiation.