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...

Utilization of electric vehicles provides a solution to several challenges in today’s individual mobility. However, ensuring maximum efficient operation of electric vehicles is required in order to overcome their greatest weakness: the limited range. Even though the overall efficiency is...

Electricity markets are currently going through a phase of agitating transition, which is mainly characterized by an increasing share of fluctuating renewable energies. Among policy makers, this has led to growing concerns about generation adequacy and often to the introduction of different...

Electricity retailers face increasing uncertainty due to the ongoing expansion of unpredictable, distributed generation in the residential sector. We analyze how increasing levels of households' solar PV self-generation affect the short-term decisionmaking and associated risk exposure of...

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...

Renewables introduce new weather-induced patterns and risks for market participants active in the energy commodity sector. We present a flexible framework for power spot prices that is capable of incorporating a weather model for the joint distribution of local weather conditions. This not only...