Balancing the production and consumption of electricity is an urgent task. Its implementation
largely depends on the means and methods of planning electricity production. Forecasting is …

Load forecasting in Smart Grids (SG) is a major module of current energy management
systems, that play a vital role in optimizing resource allocation, improving grid stability, and …

Electricity consumption is increasing rapidly, and the limited availability of natural resources
necessitates efficient energy usage. Predicting and managing electricity costs is …

In today's smart grid and building infrastructure, it is strongly suggested to implement short-
term demand forecasting for future power generation. There is a growing demand for …

Short-term load forecasting (STLF) plays a crucial role in the planning, management, and
stability of a country's power system operation. In this study, we have developed a novel …

Accurate load forecasting is of utmost importance for modern power generation facilities to
effectively meet the ever-changing electricity demand. Predicting electricity consumption is a …

Building energy planning is a challenging task in the current mounting climate change
scenario because the sector accounts for a reasonable percentage of global end-use …

The rationale for using enhanced Deep Neural Networks (DNNs) in the power distribution
system for short-term load forecasting (STLF) originates from a thorough analysis of current …

The use of information technology and the automation of control systems in the energy
sector enables a more efficient transmission and distribution of electricity. However, in …

Accurate forecasts of renewable and nonrenewable energy output are essential for meeting
global energy needs and resolving environmental issues. Energy sources like the sun and …