Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced understanding of the dynamics in interrelated short-term physical power and energy markets is required, which can be supported by market simulations. In this paper, we present an agent-based power market simulation model with rule-based bidding strategies that addresses the above-mentioned challenges, and represents market participants individually with a high level of technical detail. By allowing agents to participate in several interrelated markets, such as the energy-only market, a procurement platform for control reserve and a local heat market representing district heating systems, cross-market opportunity costs are well reflected. With this approach, we were able to reproduce EPEX SPOT market outcomes for the German bidding zone with a high level of accuracy (mean absolute percentage error of 8 €/MWh for the years 2016–2019). We were also able to model negative market prices at the energy-only market realistically, and observed that the occurrence of negative prices differs among data inputs used. The simulation model provides a useful tool for investigating different short-term physical power/energy market structures and designs in the future. The modular structure also enables extension to further related markets, such as fuel, CO${}_2$, or derivative markets.

Modeling power market dynamics is increasingly challenging, as both spatial and temporal imbalances of demand and supply are becoming more pronounced with higher shares of variable renewable energy (VRE). Therefore, a high-resolution spatial and temporal distribution of both VRE and conventional generation, as well as the load, is necessary for modeling the effect of policy measures on the electricity market. Besides, technical constraints must be considered in detail, as they fundamentally influence market outcomes. This contribution presents the results and findings from a power market simulation model for the case of the German market zone under different scenarios phasing out coal-fired power generation. It is shown that the developed spatially resolved model can realistically reproduce market outcomes and is, therefore, suitable for the analysis of future scenarios with increased VRE integration and reduced conventional generation capacity.