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

We reviewed the literature focusing on nineteen integrated Energy System Models (ESMs)
to:(i) identify the capabilities and shortcomings of current ESMs to analyze adequately the …

A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the
last 15 years, with varying degrees of success. This review article aims to explain the …

As power systems around the world are rapidly evolving to achieve decarbonization
objectives, it is crucial that power system planners and operators use appropriate models …

Agent-based simulation has become increasingly popular as a modeling approach in the
social sciences because it enables researchers to build models where individual entities …

The realisation of the smart grids and markets vision constitutes a substantial transition of
electricity systems affecting multiple stakeholders and creating various technical, social …

Climate change is one of the most daunting challenges human kind has ever faced. In the
paper, we provide a survey of the micro and macro economics of climate change from a …

In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing
on the role of generative theories, aiming at explaining phenomena by growing them. After a …

An analytical method for placement and sizing of distributed generation on power
distribution systems for loss reduction is introduced. The proposed analytical method is …

Abstract Machine learning and agent-based modeling are two popular tools in energy
research. In this article, we propose an innovative methodology that combines these …