In electricity markets around the world, the substantial increase of intermittent renewable electricity generation has intensified concerns about generation adequacy, ultimately driving the implementation of capacity remuneration mechanisms. Although formally technology-neutral, substantial...

In Europe, the ongoing renewable expansion and delays in the planned grid extension have intensified the discussion about an adequate electricity market design. Against this background, we jointly apply an agent-based electricity market model and an optimal power flow model to investigate the...

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...

The optimization of decentralized energy systems is an important practical problem that can be modeled using stochastic programs and solved via their large-scale, deterministic equivalent formulations. Unfortunately, using this approach, even when leveraging a high degree of parallelism on large...

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...

Despite the vast literature on the energy-efficiency gap, there is a general dearth of investment models which incorporate the consumer's temporal freedom in the investment decision. Focusing on the building sector, we formulate optimal investment in energy efficiency as a problem of wealth...