Machine learning and agent-based modeling are two popular tools in energy research. In this article, we propose an innovative methodology that combines these methods. For this purpose, we develop an electricity price forecasting technique using artificial neural networks and integrate the novel...

This paper provides a review on modeling electricity markets with System Dynamics (SD) focusing on deregulated electricity market models. First the SD method is classified within the wide field of electricity market modeling. Then all distinctive properties of the SD method in this context are...

Currently, most photovoltaic (PV) modules are aligned in a way that maximizes the overall annual yields, which leads to significant peaks in electricity production and could threaten energy policy objectives such as security of supply as well as environmental sustainability. The exploitation of...