Abstract In this paper, Artificial Neural Network (ANN) is integrated with data processing,
input variable selection, and external optimization techniques to forecast the day ahead …

With the continuous increase of grid-connected photovoltaic (PV), high-precision PV power
prediction is increasingly important. Extant deterministic forecasting methods do not facilitate …

The relevance of forecasting in renewable energy sources (RES) applications is increasing,
due to their intrinsic variability. In recent years, several machine learning and hybrid …

Estimation of combustion phasing and power production is essential to ensuring proper
combustion and load control. However, archetypal control-oriented physics-based …

Microgrid Protection and Control is the result of numerous research works and publications
by R&D engineers and scientists of the Microgrid and Energy Internet Research Centre …

Solar energy is one of the renewable energy sources that has been in high demand in the
last decades. With the increasing penetration of photovoltaic (PV) systems in around the …

The prediction of a photovoltaic (PV) energy production over time is considered the major
challenge to integrate it with the utilized grid. This is because it is affected by many factors …

Application of Machine Learning in forecasting renewable energy sources (RES) is
increasing: in particular, several neural networks have been employed to perform the day …

Renewable energy resources prove to be a favorable alternative due to its environment
friendly characteristics, and its dependency on different types of natural phenomenon such …

With serious energy poverty, especially concerning power shortages, the economic
development of India has been severely restricted. To some extent, power exploitation can …