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Optimization of biogas production with computational intelligence a comparative study

Jorg Ziegenhirt, Thomas Bartz-Beielstein, Oliver Flasch, Wolfgang Konen, Martin Zaefferer
2010 IEEE Congress on Evolutionary Computation  
A comparison of several algorithms from computational intelligence to solve this problem is presented in this study.  ...  Compared to previously presented results, our approach required only one tenth of the number of function evaluations.  ...  Acknowledgments This work has been supported by the Bundesministerium für Forschung und Bildung (BMBF) under the grants FIWA (AIF FKZ 17N2309, "Ingenieurnachwuchs") and by the Cologne University of Applied  ... 
doi:10.1109/cec.2010.5586509 dblp:conf/cec/ZiegenhirtBFKZ10 fatcat:zeidmf3ymrh2dacxnfuhldmgsq

Intelligent automation and IT for the optimization of renewable energy and wastewater treatment processes

Michael Bongards, Daniel Gaida, Oliver Trauer, Christian Wolf
2014 Energy, Sustainability and Society  
., biogas plant operation or a pellet-heating process can be optimized.  ...  Methods: Methods from different fields of computational intelligence are investigated.  ...  Furthermore, all students at Cologne University of Applied Sciences who contributed in one of the projects are acknowledged for their contribution.  ... 
doi:10.1186/s13705-014-0019-3 fatcat:w3rq3i27jzbwhnenywgjo2zmte

Biogas Plant Control and Optimization Using Computational Intelligence MethodsBiogasanlagenregelung und -optimierung mit Computational Intelligence Methoden

Christian Wolf, Seàn McLoone, Michael Bongards
2009 at - Automatisierungstechnik  
Results show that an improvement of up to 20% in biogas production and substrate reduction can be achieved when compared to conventional manual operation.  ...  biogas production.  ...  In addition, available measurement data can be used to develop computer based simulation and optimization models which allow a further increase in productivity with minimum effort for the operator.  ... 
doi:10.1524/auto.2009.0809 fatcat:zgqqgt3bzvchnh4ibj2xi6noee

Integration of Artificial Intelligence into Biogas Plant Operation

Samet Cinar, Senem Onen Cinar, Nils Wieczorek, Ihsanullah Sohoo, Kerstin Kuchta
2021 Processes  
As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation.  ...  From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/pr9010085 fatcat:eanhy2z2lbbyzbqzkjfsa2jhaq

Review of Anaerobic Digestion Modeling and Optimization Using Nature-Inspired Techniques

Anjali Ramachandran, Rabee Rustum, Adebayo J. Adeloye
2019 Processes  
Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer  ...  Nature-inspired techniques are a recently developed branch of artificial intelligence wherein knowledge is transferred from natural systems to engineered systems.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/pr7120953 fatcat:kfjmcf75nnfd5pxl2tjqo4zlpu

Optimization of Biogas Electrical Power Generation using Neuro-Fuzzy Controller

Araoye Timothy Oluwaseun, Alor Michael Onyeamaechi, Okika Stephen Sunday
2020 Transactions on Machine Learning and Artificial Intelligence  
This research paper develops a Neuro-fuzzy controller model for generation of Biogas power production.  ...  The technology design and model power system that predict and control the generation of biogas Electrical production.  ...  The study modeled a fuzzy logic controller to improve biogas electrical power output by comparing the biogas electrical power output with fuzzy logic controller and biogas electrical power output without  ... 
doi:10.14738/tmlai.76.7239 fatcat:42os4ucoynhtlprunu6fmhqosu

LSTM networks for anaerobic digester control

V. Yesilevskyi, S. Dyadun, V. Kuznetsov
2019 Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu  
To study the possibility of use of artificial intelligence systems based on neural networks for the improvement of the efficiency of the biogas production in the anaerobic digester by optimization of the  ...  The performed computational experiment showed that the learning convergence could be achieved after 600 episodes in a model with two control channels and four measurement channels.  ...  To test the possibility of building a biogas control system in a digester, computer simulation of the technological process was carried out. An adequate biogas production model had to be chosen.  ... 
doi:10.29202/nvngu/2019-5/21 fatcat:hk5oxnxu3vg33dgkicpks47pja

Applications of Artificial Intelligence‐Based Modeling for Bioenergy Systems: A Review

Mochen Liao, Yuan Yao
2021 GCB Bioenergy  
of traditional computing techniques for bioenergy supply chain design and optimization.  ...  A wide variety of biomass can be converted to bioenergy products, including woody biomass, agricultural residues, aquatic biomass, animal biomass, industrial biomass, and mixtures, as shown in Figure 1  ...  Sloan Foundation through the contract with Environmental Law Institute (Prime Contract No. G-2018-10090, NCSU  ... 
doi:10.1111/gcbb.12816 fatcat:ixyyk6je6rcv3jdde3p36m6hre

Design and Development of Crow Optimization Model for Biogas Powergeneration System

Ashwini Nikose et al., Ashwini Nikose et al.,, TJPRC
2020 International Journal of Mechanical and Production Engineering Research and Development  
Since biogas is a clean and renewable energy that could replace the conventional energy source (fossil fuels), the optimization of this type of energy becomes important.  ...  Biogas from anaerobic digestion of organic matter is a renewable energy source consisting mainly of CH4 and CO2.  ...  [20] developed an experimental setup with a bioreactor of 5 litres to study the biogas production process.  ... 
doi:10.24247/ijmperdaug202022 fatcat:vwnma6tdtrdrxjqgwd3rauyfke

Development of Data-Driven Models to Predict Biogas Production from Spent Mushroom Compost

Reza Salehi, Qiuyan Yuan, Sumate Chaiprapat
2022 Agriculture  
In this study, two types of data-driven models were proposed to predict biogas production from anaerobic digestion of spent mushroom compost supplemented with wheat straw as a nutrient source.  ...  These findings imply that SVM modeling can be considered a robust technique in predicting biogas production from AD processes as they can be implemented without requiring prior knowledge of biogas production  ...  We also thank the support from Biogas and Biorefinery Laboratory at the Faculty of Engineering, and PSU Energy Systems Research Institute, Prince of Songkla University, Thailand.  ... 
doi:10.3390/agriculture12081090 fatcat:cb2pexigbzaftelladada7nlca

Parametric optimization for floating drum anaerobic bio-digester using Response Surface Methodology and Artificial Neural Network

S. Sathish, S. Vivekanandan
2016 Alexandria Engineering Journal  
The main purpose of this study to increase the optimal conditions for biogas yield from anaerobic digestion of agricultural waste (Rice Straw) using Response Surface Methodology (RSM) and Artificial Neural  ...  The ANN model indicates that it is much more accurate and reckons the values of maximum biogas yield when compared to RSM model. Ó 2016 Faculty of Engineering, Alexandria University.  ...  Acknowledgments The authors would like to thank the management of Annamalai University for providing us the laboratory facilities to perform this study.  ... 
doi:10.1016/j.aej.2016.08.010 fatcat:lal7hufskncovahsm6dkbb2ple

Development of Ann-Based Models to Predict Biogas and Methane Productions in Anaerobic Treatment of Molasses Wastewater

Kaan Yetilmezsoy, F. Ilter Turkdogan, Ilknur Temizel, Asli Gunay
2013 International Journal of Green Energy  
ACKNOWLEDGMENTS This work was carried out as a part of the MSc thesis by Ilknur Temizel, completed under the supervision of Dr Kaan Yetilmezsoy.  ...  The optimal neuron numbers in the hidden layer were computed as nine and 12 with the corresponding minimum MSE values of 0.06238 and 0.06488, respectively, for the estimation of biogas and methane production  ...  Compared with aerobic processes, anaerobic digestion has been considered a sustainable option for management of organic wastes and by-products as it produces renewable energy in the form of biogas and  ... 
doi:10.1080/15435075.2012.727116 fatcat:arbrjkhb3ndvbbyaxjjmrtk67u

A systematic methodology to extend the applicability of a bioconversion model for the simulation of various co-digestion scenarios

Adam Kovalovszki, Merlin Alvarado-Morales, Ioannis A. Fotidis, Irini Angelidaki
2017 Bioresource Technology  
(AD) requires complex mathematical models 19 and the optimization of numerous model parameters.  ...  A systematic methodology to extend the applicability of a bioconversion model for the simulation of various co-digestion scenarios.  ...  a rapid increase 259 in biogas productivity is observed.  ... 
doi:10.1016/j.biortech.2017.03.101 pmid:28365343 fatcat:kcehfgccafbh7icysmnudz7vvi

Towards a sustainable capacity expansion of the Danish biogas sector

M. Bojesen, L. Boerboom, H. Skov-Petersen
2015 Land Use Policy  
It is found that a sustainable facility location has the potential of reducing overall production costs by 3% as compared with current biogas plants.  ...  In this paper the authors develop a model for sustainable capacity expansion of the Danish biogas sector allowing for an identification and prioritization of suitable locations for biogas production.  ...  Acknowledgements The authors would like to thank Professor Mark Birkin, University of Leeds for a valuable commenting of the paper.  ... 
doi:10.1016/j.landusepol.2014.07.022 fatcat:dnlmyo4cbfbihpbor4lfhhmhuq

Optimal Scheduling of Biogas-Solar-Wind Renewable Portfolio for Multi-Carrier Energy Supplies

Bin Zhou, Da Xu, Canbing Li, C.Y. Chung, Yijia Cao, Ka Wing Chan, Qiuwei Wu
2018 IEEE Transactions on Power Systems  
This paper proposes a multi-source multi-product framework for coupled multi-carrier energy supplies with a biogas-solar-wind hybrid renewable system.  ...  a coupling matrix is formulated for the modeling of production, conversion, storage, and consumption of different energy carriers.  ...  CASE STUDIES A.  ... 
doi:10.1109/tpwrs.2018.2833496 fatcat:oawl3ytawvbijbk653b5mxuhz4
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