Online-measurement systems for agricultural and industrial AD plants – A review and practice test

Online-measurement systems for AD plants in general are crucial to allow for detailed and comprehensive process monitoring and provide a basis for the development and practical application of process optimisation and control strategies. Nevertheless, the online measurement of key process variables such as Volatile Fatty Acids (VFA) and Total Alkalinity (TA) has proven to be difficult due to extreme process conditions. High Total Solids (TS) concentrations and extraneous material often damage the sensors or have a strong negative impact on measurement quality and long-term behaviour. Consequently, there is a need for new robust and accurate online-measurement systems. The purpose of this paper is to give an overview of existing online-measurement systems, to present the current state of research and to show the results of practice tests at an agricultural and industrial AD plant. It becomes obvious that a broad variety of measurement solutions have been developed over the past few years, but that the main problem is the upscaling from lab-scale to practical application at full-scale AD plants. Results from the practice tests show that an online-measurement of pH, ORP, TS is possible

Multi-objective nonlinear model predictive substrate feed control of a biogas plant

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