While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …

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

As an important segment in the multi-energy systems, energy hub plays a significant role in
improving the efficiency, flexibility and reliability of the multi-energy systems. In addition …

Reservoir level control in hydroelectric power plants has importance for the stability of the
electric power supply over time and can be used for flood control. In this sense, this paper …

Wavelet transform (WT), as a data preprocessing algorithm, has been widely applied in
electricity price forecasting. However, this deterministic-based algorithm does not present …

Developing an accurate forecasting model for long-term gold price fluctuations plays a vital
role in future investments and decisions for mining projects and related companies. Viewed …

Electricity price forecasting (EPF) has been challenged by the widespread grid integration of
renewable energy (RE), so it is critical to develop a highly accurate and reliable EPF model …

With the large-scale renewable energy integration into the power grid, the features of
electricity price has become more complex, which makes the existing models hard to obtain …

Electricity price is an important indicator of the market operation. Accurate prediction of
electricity price will facilitate the maximization of economic benefits and reduction of risks to …

This paper introduces a proposed model for mid-term to short-term load forecasting (MTLF;
STLF) that can be used to forecast loads at different hours and on different days of each …