The impact of uncertainty and the complexity of renewable heat and hot water production generate the demand for intelligent cost performance analyses to support or provide resilient data and therefore reliable managerial decisions. Especially the risk control and the planning of invest and operating costs of energetic systems are with the help of exact mathematical models only insufficient feasible. One approach provides the monte-carlo-simulation projection with the possibility to handle deterministic and stochastic model approaches. A new approach for the model based investigations of strategic investment decisions for solar heat, geothermal heat or biomass heating systems under consideration of complex uncertainty is the objective of this contribution.
