In this study a novel model-based process control strategy is presented that enhances the fuel flexibility of existing biomass power plants. In a first step, major changes in the fuel composition are detected with an online monitoring. Therefore, power plant-specific mass and energy balances as well as statistical data about the biomass composition are used. As a result, the plant operator receives continuous information about the heating value, the water content, the elemental (C, H, O, N, S) and structural composition (cellulose, hemicellulose, lignin and extractives). In a second step, these data are used as input values for a simplified process model that predicts the fuel burn out and emissions depending on the plant and process data. For validation, experimental investigations were carried out in a laboratory fluidized bed reactor and a 300 kW(th) circulating fluidized bed combustion pilot plant. Taking into account uncertainties regarding biomass composition and the strong model simplifications, good agreement between measurement and calculation results is achieved.