Advanced Anaerobic Digestion With Optimization Techniques Using Genetic Algorithm and Fuzzy Logic

Prashant Mathur; Sudhanshu Singh

doi:10.17485/IJST/v16i22.2195

Article

Advanced Anaerobic Digestion With Optimization Techniques Using Genetic Algorithm and Fuzzy Logic

VIEWS 709
PDF 164

Indian Journal of Science and Technology

DOI: 10.17485/IJST/v16i22.2195

Year: 2023, Volume: 16, Issue: 22, Pages: 1624-1634

Original Article

Advanced Anaerobic Digestion With Optimization Techniques Using Genetic Algorithm and Fuzzy Logic

Prashant Mathur^1*, Sudhanshu Singh²

¹Research Scholar, Amity University, Jaipur, Rajasthan, India
²Associate Professor, Chandigarh University, Gharuan, Mohali, India

*Corresponding Author
Email: [email protected]

Received Date:23 November 2022, Accepted Date:26 April 2023, Published Date:03 June 2023

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objectives: The primary aim of this study is to enhance the anaerobic digestion process’s efficacy by utilizing advanced optimization techniques, specifically genetic algorithms and fuzzy logic. The overarching objective is to employ these methods to optimize the model’s performance, resulting in improved anaerobic digestion outcomes. Methods: The Anaerobic Digestion process is a widely adopted technique for treating organic waste, which involves decomposing organic material by microorganisms without oxygen. However, the effectiveness of this process can be significantly influenced by various factors, such as pH, temperature, and nutrient levels. Given this process’s uncertain and imprecise nature, we propose the integration of fuzzy logic to simulate the associated uncertainties. Furthermore, we also employ genetic algorithm techniques to optimize the model’s parameters and improve its overall performance. The proposed methodology could enhance the efficiency and reliability of the Anaerobic Digestion process while minimizing its environmental impact. Findings: The study introduces an advanced anaerobic digestion model for efficiently treating organic waste. The biological methane potential was significantly improved by employing optimization techniques such as genetic algorithms and fuzzy logic. The findings demonstrate a 23.5% increase in methane production, indicating the potential for this approach to enhance the performance and efficiency of anaerobic digestion processes. Overall, the results suggest that the proposed model can contribute to developing sustainable waste management practices. Novelty: This study presents a pioneering approach by integrating genetic algorithms and fuzzy logic to optimize the anaerobic digestion process in advanced anaerobic digestion systems. To the best of our knowledge, this is the first research work that employs a hybrid control technique to consider multiple optimization methods. The proposed methodology could improve the efficiency of anaerobic digestion processes and reduce operational costs. This research advances sustainable waste management practices by applying advanced optimization techniques.

Keywords: Anaerobic Digestion; Fuzzy Logic; Optimization; Renewable Energy; Genetic Algorithm

References

Palma-Heredia D, Verdaguer M, Puig V, Poch M, Cugueró-Escofet MÀ. Comparison of Optimisation Algorithms for Centralised Anaerobic Co-Digestion in a Real River Basin Case Study in Catalonia. Sensors. 2022;22(5):1857. Available from: https://doi.org/10.3390/s22051857
Asadi M, Mcphedran K. Biogas maximization using data-driven modelling with uncertainty analysis and genetic algorithm for municipal wastewater anaerobic digestion. Journal of Environmental Management. 2021;293:112875. Available from: https://doi.org/10.1016/j.jenvman.2021.112875
Beltramo T, Klocke M, Hitzmann B. Prediction of the biogas production using GA and ACO input features selection method for ANN model. Information Processing in Agriculture. 2019;6(3):349–356. Available from: https://doi.org/10.1016/j.inpa.2019.01.002
Mathur R, Sharma MK. Modeling and optimization of the anaerobic digestion system for domestic waste water treatment with the development of monitoring techniques. IOP Conference Series: Earth and Environmental Science. 2022;1084(1):012046. Available from: https://doi.org/10.1088/1755-1315/1084/1/012046
Sridhar A, Kapoor A, Kumar PS, Ponnuchamy M, Balasubramanian S, Prabhakar S. Conversion of food waste to energy: A focus on sustainability and life cycle assessment. Fuel. 2021;302:121069. Available from: https://doi.org/10.1016/j.fuel.2021.121069
Suganthi L, Iniyan S, Samuel AA. Applications of fuzzy logic in renewable energy systems – A review. Renewable and Sustainable Energy Reviews. 2015;48:585–607. Available from: https://doi.org/10.1016/j.rser.2015.04.037
Enitan AM, Adeyemo J, Swalaha FM, Kumari S, Bux F. Optimization of biogas generation using anaerobic digestion models and computational intelligence approaches. Reviews in Chemical Engineering. 2017;33(3):309–335. Available from: https://doi.org/10.1515/revce-2015-0057
Sulaiman A, Nikbakht M, Tabatabaei A, Meisam, Khatamifar, Hassan M. Modeling anaerobic process for wastewater treatment: New Trends and Methodologies. 2010. Available from: https://www.academia.edu/822420/Modeling_anaerobic_process_for_wastewater_treatment_new_trends_and_methodologies
Cruz IA, Chuenchart W, Long FC, Surendra KC, Andrade LRS, Bilal M, et al. Application of machine learning in anaerobic digestion: Perspectives and challenges. Bioresource Technology. 2022;345:126433. Available from: https://doi.org/10.1016/j.biortech.2021.126433
Longo E, Sahin FA, Redondi AEC, Bolzan P, Bianchini M, Maffei S. A 5G-Enabled Smart Waste Management System for University Campus. Sensors. 2021;21(24):8278. Available from: https://doi.org/10.3390/s21248278
Liu Y, Zong Y, Xie T, Song H, Zhang J. Anaerobic Co-Digestion with Food Waste: A Possible Alternative to Overcome the Energy Deficit of Sludge Thermal Pretreatment. ACS Omega. 2022;7(43):38496–38504. Available from: https://doi.org/10.1021/acsomega.2c03700
Onwosi CO, Eke IE, Igbokwe VC, Odimba JN, Ndukwe JK, Chukwu KO, et al. 2019.
Henriques AA, Fontes M, Camanho A, Silva JG, Amorim P. Leveraging logistics flows to improve the sludge management process of wastewater treatment plants. Journal of Cleaner Production. 2020;276:122720. Available from: https://doi.org/10.1016/j.jclepro.2020.122720
Fang C, Yin J, Ren H. Evaluation Model of Ship Berthing Behavior Based on AIS Data. IEEE Open Journal of Intelligent Transportation Systems. 2022;3:104–110. Available from: https://doi.org/10.1109/OJITS.2021.3138562
Stalley SO, Wang D, Dasarathy G, Lipor J. A Graph-Based Approach to Boundary Estimation With Mobile Sensors. IEEE Robotics and Automation Letters. 2022;7(2):4991–4998. Available from: https://doi.org/10.1109/LRA.2022.3145977
Ye C, Chen L, Ni S, Zhou J. Evaluation model of forest eco economic benefits based on discrete particle swarm optimization. Environmental Technology & Innovation. 2021;22:101426. Available from: https://doi.org/10.1016/j.eti.2021.101426
Cerón-Vivas A, Cáceres KT, Rincón CA, Cajigas ÁA. Influence of pH and the C/N ratio on the biogas production of wastewater. 2019. Available from: https://doi.org/10.17533/udea.redin.20190627
Ankathi S, Watkins D, Sreedhara P, Zuhlke J, Shonnard DR. GIS-Integrated Optimization for Locating Food Waste and Manure Anaerobic Co-digestion Facilities. ACS Sustainable Chemistry & Engineering. 2021;9(11):4024–4032. Available from: https://doi.org/10.1021/acssuschemeng.0c07482
Deng Y, Qiu L, Shao Y, Yao Y. Process Modeling and Optimization of Anaerobic Co-Digestion of Peanut Hulls and Swine Manure Using Response Surface Methodology. Energy & Fuels. 2019;33(11):11021–11033. Available from: https://doi.org/10.1021/acs.energyfuels.9b02381
Hallaji SM, Kuroshkarim M, Moussavi SP. Enhancing methane production using anaerobic co-digestion of waste activated sludge with combined fruit waste and cheese whey. BMC Biotechnology. 2019;19(1). Available from: https://doi.org/10.1186/s12896-019-0513-y
Hanum F, Yuan LC, Kamahara H, Aziz HA, Atsuta Y, Yamada T, et al. Treatment of Sewage Sludge Using Anaerobic Digestion in Malaysia: Current State and Challenges. Frontiers in Energy Research. 2019;7. Available from: https://doi.org/10.3389/fenrg.2019.00019
Do HT, Bach NV, Nguyen LV, Tran HT, Nguyen M. A design of higher-level control-based genetic algorithms for wastewater treatment plants. Engineering Science and Technology, an International Journal. 2021;24(4):872–878. Available from: https://doi.org/10.1016/j.jestch.2021.01.004
Ahmed SF, Mofijur M, Tarannum K, Chowdhury AT, Rafa N, Nuzhat S, et al. Biogas upgrading, economy and utilization: A review. Environmental Chemistry Letters. 2021;19(6):4137–4164. Available from: https://doi.org/10.1007/s10311-021-01292-x
Afrane S, Ampah JD, Agyekum EB, Amoh PO, Yusuf AA, Fattah IMR, et al. Integrated AHP-TOPSIS under a Fuzzy Environment for the Selection of Waste-To-Energy Technologies in Ghana: A Performance Analysis and Socio-Enviro-Economic Feasibility Study. International Journal of Environmental Research and Public Health. 2022;19(14):8428. Available from: https://doi.org/10.3390/ijerph19148428

Copyright

© 2023 Mathur & Singh. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)