The maintenance of electrical grids is crucial for improving their reliability, performance, and
cost-effectiveness. It involves employing various strategies to ensure smooth operation and …

The penetration rates of renewable sources and energy storage systems in the energy
market have risen considerably due to environmental and economic concerns. In addition …

Renewable energies, such as solar and wind power, have become promising sources of
energy to address the increase in greenhouse gases caused by the use of fossil fuels and to …

Abstract In this paper, Machine Learning (ML) based techniques known as Support Vector
Regression (SVR) and Gradient Boosting Regression Trees (GBRT) are utilized for …

As global warming is increasing due to conventional sources the government and the
private sectors introduce policies to minimize it, renewable energy has been developed and …

In an era of big data, organizations increasingly aim to adopt data-driven decision-making
processes to enhance their performance. This paper investigates the data-driven decision …

The study aims to predict solar energy generation to ensure the successful operation of solar
power plants. This objective is crucial in light of the increasing energy demand, global …

A significant amount of electricity in numerous regions worldwide is used for lighting roads,
squares, and other public spaces. Renewable energy can contribute notably to electricity …

In this paper, we perform a short-run Electricity Price Forecast (EPF) with a Recurrent Neural
Network (RNN), namely Long Short-Term Memory (LSTM), using an algorithm that selects …

The present article develops time series machine learning models to forecast the Adama II
wind farm's long-term power production using SCADA data. The study applied data from the …