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Design And Control Of Pem Fuel Cell Diffused Aeration System Using Artificial Intelligence Techniques

Domain:

environment and energyagriculture

Record type:

paper
Creator:
DoaFahNinHas
Publisher:
Zenodo
Host:avatar
Fuel cells have become one of the major areas of research in the academia and the industry. The goal of most fish farmers is to maximize production and profits while holding labor and management efforts to the minimum. Risk of fish kills, disease outbreaks, poor water quality in most pond culture operations, aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) techniques control is used to control the fuel cell output power by control input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparison study is applied between the performance of fuzzy logic control (FLC) and neural network control (NNC). The results show the effectiveness of NNC over FLC. {"references": ["Abhishek Sakhare a, Asad Davari, Ali Feliachi,'' Fuzzy logic control of\nfuel cell for stand-alone and grid connection'', Journal of Power Sources\nVol., 135, PP., 165-176, 2004.", "M.J. Khan, M.T. Iqbal, ''Analysis of a small wind-hydrogen stand-alone\nhybrid energy system\", Applied Energy, Vol., 86, PP., 2429-2442, 2009.", "Soteris A. Kalogirou \"Artificial neural networks in renewable energy\nsystems applications: a review\", Renewable and Sustainable Energy\nReviews Vol. 5 pp. 373-401, 2001.", "Abdel Ghani Aissaoui, \"a fuzzy logic controller for synchronous\nmachine'', Journal of Electrical Engineering, Vol. 58, pp. 285-290,\n2007.", "D. Driankov, H. Hellendoorn, and M. Reinfrank, ''an introduction to\nfuzzy control'', Springer-Verlag, Berlin, Heidelberg, 1993.", "Mark C. Williams, ''Fuel Cell Handbook'', fifth ed., EG&G Services\nParsons, Inc., 2000.", "Colleen Spiegel, \"PEM fuel cell modeling and simulation using\nMATLAB\", Academic Press, 2008.", "Energy Efficiency Guide for Industry in Asia -\nwww.energyefficiencyasia.org.", "Austin Hughes, ''Electric motors and drives fundamentals, types and\napplications'', Newnes, 2006.\n[10] P. Thepsatom, A. Numsomran, V. TipsuwanpoM and T. Teanthong,\n''DC motor speed control using fuzzy logic based on Lab VIEW'', SICEICASE\nInternational Joint Conference 2006.\n[11] Kalogirou SA. ''Artificial intelligence for the modeling and control of\ncombustion processes: a review'', Prog Energy Combust Sci; Vol., 29,\n515-66, 2003.\n[12] C.W. Tao, ''Design of fuzzy-learning fuzzy controllers, fuzzy systems\nproceedings'', 1998. IEEE World Congress on Computational\nIntelligence.,.\n[13] Zhan Yuedong, Zhu Jianguo , Guo Youguang , Jin Jianxun, \"Control of\nproton exchange membrane fuel cell based on fuzzy logic\", Proceedings\nof the 26th Chinese Control Conference, 2007, China, IEEE.\n[14] Christina N. Papadimitriou and Nicholas A.Vovos, \"A Fuzzy Control\nScheme for Integration of DGs into a Microgrid \", IEEE, 2010.\n[15] Ahmed M. Ibrahim, \"Fuzzy logic for embedded systems application\",\nNewnes press, 2004.\n[16] M. Azouz, A. Shaltout and M. A. L. Elshafei, \"Fuzzy logic control of\nwind energy systems\", Proceedings of the 14th International Middle East\nPower Systems Conference (MEPCON-10), Egypt, 2010.\n[17] S. Lalouni, D. Rekioua, T. Rekioua and E. Matagne, \"Fuzzy logic\ncontrol of stand-alone photovoltaic system with battery storage\", Journal\nof Power Sources, Vol. 193, PP. 899-907, 2009.\n[18] Ch. Ben Salah, M. Chaaben, M. Ben Ammar, \"Multi-criteria fuzzy\nalgorithm for energy management of a domestic photovoltaic panel\",\nRenewable Energy Vol. 33, PP. 993 -1001, 2008.\n[19] Soteris A Kalogiroua, Soa Pantelioub, Argiris Dentsoras, \"Artificial\nneural networks used for the performance prediction of a thermosiphon\nsolar water heater\", Renewable Energy, Vol., 18, PP., 87-99, 1999.\n[20] James A. Freeman, David M. Skapura, ''Neural networks algorithms,\napplications, and programming techniques'', Addison-Wesley Publishing\nCompany, Inc., Paris, 1991.\n[21] M.N. Cirstea, A. Dinu, J.G. Khor, M. McCormick, \"Neural and fuzzy\nlogic control of drives and power systems\", Replika Press Delhi , India,\n2002.\n[22] Soteris A. Kalogirou, \"Prediction of flat-plate collector performance\nparameters using artificial neural networks\", Solar Energy, Vol., 80, PP.,\n248-259, 2006.\n[23] Adnan Sozen, Tayfun Menlik, Sinan Unvar, \"Determination of\nefficiency of flat-plate solar collectors using neural network approach\",\nExpert Systems with Applications, Vol., 35, PP., 1533-1539, 2008."]}

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doi.orgzenodo.org

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Hamer-Banna

Tags

PEM fuel cellDiffused aeration systemArtificialintelligence (AI) techniquesneural network controlfuzzy logiccontrol

Licenses

Creative Commons Attribution 4.0https://creativecommons.org/licenses/by/4.0Open Accessinfo:eu-repo/semantics/openAccess

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