The short-term load forecasting is crucial in the power system operation and control.
However, due to its nonstationary and complicated random features, an accurate forecast of …

This book offers an in-depth and up-to-date review of different statistical tools that can be
used to analyze and forecast the dynamics of two crucial for every energy company …

Load forecasting has been a conventional and important process in electric utilities since the
early 20 th century. Due to the deregulation of the electric utility industry, the utilities tend to …

Short-term load forecast (STLF) is a key issue for operation of both regulated power systems
and electricity markets. In spite of all performed research in this area, there is still an …

This paper presents short-term load forecasting models, which are developed by using fuzzy
logic and adaptive neuro-fuzzy inference system (ANFIS). Firstly, historical data are …

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF)
models for electric power distribution applications. However, they are not typically used in …

Short-term load forecasting is viewed as one promising technology for demand prediction
under the most critical inputs for the promising arrangement of power plant units. Thus, it is …

A new hybrid model for forecasting the electric power load several months ahead is
proposed. To allow for distinct responses from individual load sectors, this hybrid model …

Affected by the new coronavirus (COVID-19) pandemic, global energy production and
consumption have changed a lot. It is unknown whether conventional short-term load …

The load forecasting problem is a complex nonlinear problem linked with social
considerations, economic factors, and weather variations. In particular, load forecasting for …