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 …

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 …

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 …

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 …

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 …

In the last decade, the water and electricity industry has experienced significant investments
in smart grid technologies. Within a smart grid framework, information and energy engage in …

The implementation of smart grids has emerged as a promising solution to enhance energy
efficiency and address the challenges posed by the growing energy demands and …

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 …