The rapidly growing supply-based renewable energy (EE) in the electricity market increased the complexity of the electricity system and the requirements of the electricity market modeling. This work describes on the basis of empirical examples from Germany and Texas, that increasing EE share strongly influenced the operation of the market. The resulting price signals lead in the long term system adjustments. To obtain an estimate of the effects of adjustment, the current market model was 'the high temporal resolution of electricity market analysis model' (THEA) developed. In a first application, the ERCOT market area in Texas is modeled to the specific properties of the model to test and compare with complexity-reducing methods with regard to the temporal resolution and the operational detail sharpness. In both cases, the results show significant differences compared to the results of the full use of the model. The ERCOT application also shows that the EE-induced adaptation effects in an isolated, mainly thermal power market are very clear. In summary, it can be seen that restricting the flexibility of a system component increases the value of the flexibility of other system components, resulting in a careful and long term-oriented, integrated energy policy recommendation can be derived.
