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.
Author: | Daniel Gaida, Christian Wolf, Thomas Bäck, Michael Bongards |
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URN: | urn:nbn:de:hbz:832-epub4-6622 |
Parent Title (German): | Kompendium der Forschungsgemeinschaft :metabolon 2012-2014 |
Descirption of the primary publication: | Kompendium der Forschungsgemeinschaft :metabolon 2012-2014, 2014, S. 47-51 |
Place of publication: | Gummersbach |
Document Type: | Part of a Book |
Language: | English |
Date of Publication (online): | 2015/05/06 |
GND-Keyword: | Biogas |
Tag: | Algorithm; Biogas; Control; Multi-objective optimization; Optimization; Plant Simulation |
Institutes: | Informatik und Ingenieurwissenschaften (F10) / Fakultät 10 / :metabolon Institut |
Dewey Decimal Classification: | 600 Technik, Medizin, angewandte Wissenschaften |
JEL-Classification: | Q Agricultural and Natural Resource Economics; Environmental and Ecological Economics |
Open Access: | Open Access |
Licence (German): | ![]() |