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Biogas Plant Control and Optimization Using Computational Intelligence MethodsBiogasanlagenregelung und -optimierung mit Computational Intelligence Methoden by Christian Wolf; Seàn McLoone; Michael Bongards is a Engineering article available to read on EtoBox.

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## Abstract The optimization of agricultural and industrial biogas plants with respect to external influences and various process disturbances is essential for efficient plant operation. The fact that most biogas plants are manually operated because of a lack of online-measurements and limited knowledge about the anaerobic digestion process makes it necessary to develop new optimization and control strategies. However, the optimization and control of such plants is a challenging problem due to the underlying highly nonlinear and complex digestion processes. One approach to address this challenge is to exploit the flexibility and power of computational intelligence (CI) methods such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). The use of CI methods in conjunction with a validated plant simulation model, based on the Anaerobic Digestion Model No. 1, allows optimization of the substrate feed mix, a key factor in stable and efficient biogas production. Results show that an improvement of up to 20% in biogas production and substrate reduction can be achieved when compared to conventional manual operation.

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Author

Christian Wolf; Seàn McLoone; Michael Bongards

Publisher

Walter de Gruyter GmbH

Published

2009

Language

EN

Field

Engineering (Physical Sciences)