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...

Energy systems based on renewable energy sources require increasing demand side flexibility. Also, changes in the underlying cost structure, i. e., decreasing variable costs and increasing infrastructure investments, and varying customer needs should be reflected in the setup of future markets,...

Growing numbers of plug-in electric vehicles in Europe will have an increasing impact on the electricity system. Using the agent-based simulation model PowerACE for ten electricity markets in Central Europe, we analyze how different charging strategies impact price levels and production- as well...

Potential environmental benefits of green tariffs may be mitigated if households increase electricity consumption after they subscribe to green tariffs. Using metered data of household electricity consumption from a large provider of green electricity in Germany, our quasi-experimental analysis...