Investment decisions in competitive power markets are based upon thorough profitability assessments. Thereby, investors typically show a high degree of risk aversion, which is the main argument for capacity mechanisms being implemented around the world. In order to investigate the...

Investment decisions in competitive power markets are based upon thorough profitability assessments. Thereby, investors typically show a high degree of risk aversion, which is the main argument for capacity mechanisms being implemented around the world. In order to investigate the...

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...

Introduction -- Fundamentals of Energy and Power Systems -- Energy Demand -- Electricity Generation and Operational Planning -- Electricity Transport and Storage -- Regulation: Grids and Environment -- Simple Electricity Market Equilibrium Models -- Markets: Organisation, Trading and Efficiency...

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...

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...

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...

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...