Smart grids are electricity networks that deliver electricity in a controlled way, offering
multiple benefits such as growth and effective management of renewable energy sources …

Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

Solar energy forecasting represents a key element in increasing the competitiveness of solar
power plants in the energy market and reducing the dependence on fossil fuels in economic …

Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy
sources into the grid as it provides accurate and timely information on the expected output of …

The rapid variation of clouds is the main factor that causes the fluctuation of photovoltaic
power. 1 The satellite images contain plenty of information about clouds, applicable for …

In this paper, a forecasting algorithm is proposed to predict photovoltaic (PV) power
generation using a long short term memory (LSTM) neural network (NN). A synthetic …

Energy supply of megacities is considered as an active research topic in the new aspects of
urban management, especially in developing countries like Iran. With an introduction to the …

Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …

To mitigate the impact of climate change and global warming, the use of renewable energies
is increasing day by day significantly. A considerable amount of electricity is generated from …

Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure
operation and economic integration of PV in smart grids, accurate forecasting of PV power is …