In recent years, artificial intelligence methods have been widely applied to solve issues
related to renewable energy because of their ability to solve nonlinear and complex data …

Accurate forecasting results are crucial for increasing energy efficiency and lowering energy
consumption in wind energy. Big data and artificial intelligence (AI) have great potential in …

Nowadays, learning-based modeling methods are utilized to build a precise forecast model
for renewable power sources. Computational Intelligence (CI) techniques have been …

The energy sector plays a vital role in achieving a sustainable net-zero future, and the
adoption of advanced technologies such as AI, blockchain, quantum computing, digital twin …

The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …

Due to population growth and industrial development, Iran is facing the challenge of energy
supply in various industrial, power plant, agricultural, and residential sectors. While most of …

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 …

This paper provides an extensive review of learning-based short-term forecasting models for
smart grid applications. In addition to this, the paper also explores forecasting models …

As Photovoltaic (PV) energy is impacted by various weather variables such as solar
radiation and temperature, one of the key challenges facing solar energy forecasting is …

In recent years, hybrid Solar-Wind energy system has emerged as a viable solution to
achieve sustainable energy generation and alleviate the burden on the power grid …