High consumption and ever-increasing demand for electricity at commercial, residential, and
industrial levels have attracted the research community to look for new technologies for the …

The emerging concept of smart buildings, which requires the incorporation of sensors and
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …

Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …

Balancing electricity generation and consumption is essential for smoothing the power grids.
Any mismatch between energy supply and demand would increase costs to both the service …

Renewable energy from wind and solar resources can contribute significantly to the
decarbonisation of the conventionally fossil-driven electricity grid. However, their seamless …

Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …

Conventional models and artificial intelligence (AI)-based models have been widely applied
for energy consumption forecasting over the past decades. This paper reviews conventional …

With the growth of population, many countries face the challenge of supplying energy
resources. One approach to managing and planning these resources is to predict energy …

Short term electricity load forecasting is one of the most important issue for all market
participants. Short term electricity load is affected by natural and social factors, which makes …

Energy management systems are designed to monitor, optimize, and control the smart grid
energy market. Demand-side management, considered as an essential part of the energy …