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In this paper a closed-loop substrate feed control for agricultural biogas plants is proposed. In this case, multi-objective nonlinear model predictive control is used to control composition and amount of substrate feed to optimise the economic feasibility of a biogas plant whilst assuring process stability. The control algorithm relies on a detailed biogas plant simulation model using the Anaerobic
Digestion Model No. 1. The optimal control problem is solved using the state-of-the-art multi-objective optimization method SMS-EGO. Control performance is evaluated by means of a set point tracking problem in a noisy environment.
Results show, that the proposed control scheme is able to keep the produced electrical energy close to a set point with an RMSE of 0.9 %, thus maintaining optimal biogas plant operation.
Modern industrial biomass combustion plants are regulated by the power and/or combustion control. In this process, the implemented sensors collect the relevant measured data. The aim is to achieve ideal combustion with optimum efficiency and to minimize gas emissions. For this purpose, a group within the research project Metabolon developed new regulatory procedures in order to record the combustion process of a biomass combustion plant using a webcam. The recordings were evaluated automatically and were used for a better monitoring of the process. In addition, the webcam-based method aims, among other things, to provide private homes with a cost-effective variant as an alternative to industrial system solutions.