In this paper we address the problems faced for automatic configuration of flexible hybrid models. We approach this problem with concepts from the computer science field including object orientated design and dependency injection to create a new Hybrid Model that combines traditional modelling methods with a flexible design. This type of model is able to drastically change its functional behaviour, allowing it to simulate a larger variety of scenarios of varying complexity. We then use AI methods to automatically configure the model to reduce its complexity to the minimum while having minimal impact on the models accuracy. A small example is demonstrated where this method is used to configure the market environment for a hydro-power plant model, allowing us to determine which set of markets are most profitable for any given plant configuration . Furthermore, the use of flexible hybrid models opens up the possibility for further AI methods to be used in conjunction with mathematical models.