An integrated prediction and optimization model of biogas production system at a wastewater treatment facility. (November 2015)

• Record Type: Journal Article
• Authors: Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih
• Is Part Of: Bioresource technology. Volume 196(2015)
• Page Start: 566
• Page End: 576
• Publication Date: 2015-11
• Subjects: Biogas quality -- Biogas production -- Neural networks -- Particle swarm optimization -- Wastewater treatment facility; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2015.08.017
• Languages: English
• ISSNs: 0960-8524

Abstract

Highlights: Consistency and optimal control of biogas production system are provided. Biogas quality criterion is described and used as a PSO model output. Neural network simulation provides the integration of MLP neural network and PSO. The best particle positions in PSO model are used to determine maximized outputs. Abstract: This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility.