A coupled modeling of design and investment parameters for optimal operation of methane bioreactors: Attainable region concept approach. (April 2020)

• Record Type: Journal Article
• Authors: Abunde Neba, F.; Asiedu, Nana Y.; Addo, Ahmad; Morken, John; Østerhus, Stein W.; Seidu, Razak
• Is Part Of: Renewable energy. Volume 148(2020)
• Page Start: 1054
• Page End: 1064
• Publication Date: 2020-04
• Subjects: Attainable regions -- Reactor economics -- Modeling -- Biogas plant design -- Optimization; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2019.10.089
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Current practice to design methane bioreactors does not consider all degrees of freedom simultaneously, which raises question of global optimality. This study presents a model-based design framework, which simultaneously integrates process kinetics and business parameters into the design process, a key motivation for investors. Within the study, a methane bioreactor model is presented and kinetic models incorporating different economic feasibility indicators (PBP and BCR) are developed. The methane bioreactor model gives a good prediction of test data for digestion of diary manure and the natural patterns of payback period and benefit cost ratio are predicted. Stochastic stimulation is presented to include robustness in the design process and overall yield coefficients are illustrated for model dimensionality reduction. Two-dimensional attainable region is introduced as a reliable technique for defining limits of achievability as well as obtaining optimal methane bioreactor structures. Finally, a schematic model of the design process is established. Highlights: We introduce a coupled modeling of digester design and investment parameters. Attainable region theory is introduced for obtaining optimal digester structures. Stochastic stimulation is presented to include robustness in the design process. Overall yield coefficients are illustrated for model dimensionality reduction. The study is useful in defining performance targets and associated reactor networks.