Increasing temperatures in urban areas have brought about a series of prevalent
environmental and energy shortage problems. Many studies have focused on the …

Accurately modeling and forecasting electricity consumption remains a challenging task due
to the large number of the statistical properties that characterize this time series such as …

Forecasting energy demand for the industrial sector is both interesting and difficult due to the
difference in energy demand specific to each industrial sub-sector. For an accurate …

Data-driven methods, such as artificial neural networks (ANNs), support vector regression
(SVM), Gaussian process regression (GPR), multiple linear regression (MLR), decision trees …

Cities are the primary carbon emitters in China and play a critical role in achieving national
and regional emission-reduction targets. However, because existing CO 2 emission …

Accurate forecasting of electricity load is essential for electricity companies, primarily for
planning electricity generators. Overestimated or underestimated forecasting value may lead …

Modern energy systems use large amounts of water for electric power production. This has
important impacts on future water management and energy system planning decisions. In …

Electricity demand forecasting stands as a paramount factor in the operation and strategic
planning of energy production and distribution systems. This article aims to present the …

With the grid's evolution, the end‐users demand becomes more vital for demand side
management (DSM). Accurate load forecasting (LF) is critical for power system planning and …

The economy of a country is directly proportional to the power sector of that country. An
unmanaged power sector causes instability in the country. Pakistan is also facing this …