Design and Control of PEM Fuel Cell Diffused Aeration System using Artificial Intelligence Techniques
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.
[1] Abhishek Sakhare a, Asad Davari, Ali Feliachi,'' Fuzzy logic control of
fuel cell for stand-alone and grid connection'', Journal of Power Sources
Vol., 135, PP., 165-176, 2004.
[2] M.J. Khan, M.T. Iqbal, ''Analysis of a small wind-hydrogen stand-alone
hybrid energy system", Applied Energy, Vol., 86, PP., 2429-2442, 2009.
[3] Soteris A. Kalogirou "Artificial neural networks in renewable energy
systems applications: a review", Renewable and Sustainable Energy
Reviews Vol. 5 pp. 373-401, 2001.
[4] Abdel Ghani Aissaoui, "a fuzzy logic controller for synchronous
machine'', Journal of Electrical Engineering, Vol. 58, pp. 285-290,
2007.
[5] D. Driankov, H. Hellendoorn, and M. Reinfrank, ''an introduction to
fuzzy control'', Springer-Verlag, Berlin, Heidelberg, 1993.
[6] Mark C. Williams, ''Fuel Cell Handbook'', fifth ed., EG&G Services
Parsons, Inc., 2000.
[7] Colleen Spiegel, "PEM fuel cell modeling and simulation using
MATLAB", Academic Press, 2008.
[8] Energy Efficiency Guide for Industry in Asia -
www.energyefficiencyasia.org.
[9] Austin Hughes, ''Electric motors and drives fundamentals, types and
applications'', Newnes, 2006.
[10] P. Thepsatom, A. Numsomran, V. TipsuwanpoM and T. Teanthong,
''DC motor speed control using fuzzy logic based on Lab VIEW'', SICEICASE
International Joint Conference 2006.
[11] Kalogirou SA. ''Artificial intelligence for the modeling and control of
combustion processes: a review'', Prog Energy Combust Sci; Vol., 29,
515-66, 2003.
[12] C.W. Tao, ''Design of fuzzy-learning fuzzy controllers, fuzzy systems
proceedings'', 1998. IEEE World Congress on Computational
Intelligence.,.
[13] Zhan Yuedong, Zhu Jianguo , Guo Youguang , Jin Jianxun, "Control of
proton exchange membrane fuel cell based on fuzzy logic", Proceedings
of the 26th Chinese Control Conference, 2007, China, IEEE.
[14] Christina N. Papadimitriou and Nicholas A.Vovos, "A Fuzzy Control
Scheme for Integration of DGs into a Microgrid ", IEEE, 2010.
[15] Ahmed M. Ibrahim, "Fuzzy logic for embedded systems application",
Newnes press, 2004.
[16] M. Azouz, A. Shaltout and M. A. L. Elshafei, "Fuzzy logic control of
wind energy systems", Proceedings of the 14th International Middle East
Power Systems Conference (MEPCON-10), Egypt, 2010.
[17] S. Lalouni, D. Rekioua, T. Rekioua and E. Matagne, "Fuzzy logic
control of stand-alone photovoltaic system with battery storage", Journal
of Power Sources, Vol. 193, PP. 899-907, 2009.
[18] Ch. Ben Salah, M. Chaaben, M. Ben Ammar, "Multi-criteria fuzzy
algorithm for energy management of a domestic photovoltaic panel",
Renewable Energy Vol. 33, PP. 993 -1001, 2008.
[19] Soteris A Kalogiroua, Soa Pantelioub, Argiris Dentsoras, "Artificial
neural networks used for the performance prediction of a thermosiphon
solar water heater", Renewable Energy, Vol., 18, PP., 87-99, 1999.
[20] James A. Freeman, David M. Skapura, ''Neural networks algorithms,
applications, and programming techniques'', Addison-Wesley Publishing
Company, Inc., Paris, 1991.
[21] M.N. Cirstea, A. Dinu, J.G. Khor, M. McCormick, "Neural and fuzzy
logic control of drives and power systems", Replika Press Delhi , India,
2002.
[22] Soteris A. Kalogirou, "Prediction of flat-plate collector performance
parameters using artificial neural networks", Solar Energy, Vol., 80, PP.,
248-259, 2006.
[23] Adnan Sozen, Tayfun Menlik, Sinan Unvar, "Determination of
efficiency of flat-plate solar collectors using neural network approach",
Expert Systems with Applications, Vol., 35, PP., 1533-1539, 2008.
[1] Abhishek Sakhare a, Asad Davari, Ali Feliachi,'' Fuzzy logic control of
fuel cell for stand-alone and grid connection'', Journal of Power Sources
Vol., 135, PP., 165-176, 2004.
[2] M.J. Khan, M.T. Iqbal, ''Analysis of a small wind-hydrogen stand-alone
hybrid energy system", Applied Energy, Vol., 86, PP., 2429-2442, 2009.
[3] Soteris A. Kalogirou "Artificial neural networks in renewable energy
systems applications: a review", Renewable and Sustainable Energy
Reviews Vol. 5 pp. 373-401, 2001.
[4] Abdel Ghani Aissaoui, "a fuzzy logic controller for synchronous
machine'', Journal of Electrical Engineering, Vol. 58, pp. 285-290,
2007.
[5] D. Driankov, H. Hellendoorn, and M. Reinfrank, ''an introduction to
fuzzy control'', Springer-Verlag, Berlin, Heidelberg, 1993.
[6] Mark C. Williams, ''Fuel Cell Handbook'', fifth ed., EG&G Services
Parsons, Inc., 2000.
[7] Colleen Spiegel, "PEM fuel cell modeling and simulation using
MATLAB", Academic Press, 2008.
[8] Energy Efficiency Guide for Industry in Asia -
www.energyefficiencyasia.org.
[9] Austin Hughes, ''Electric motors and drives fundamentals, types and
applications'', Newnes, 2006.
[10] P. Thepsatom, A. Numsomran, V. TipsuwanpoM and T. Teanthong,
''DC motor speed control using fuzzy logic based on Lab VIEW'', SICEICASE
International Joint Conference 2006.
[11] Kalogirou SA. ''Artificial intelligence for the modeling and control of
combustion processes: a review'', Prog Energy Combust Sci; Vol., 29,
515-66, 2003.
[12] C.W. Tao, ''Design of fuzzy-learning fuzzy controllers, fuzzy systems
proceedings'', 1998. IEEE World Congress on Computational
Intelligence.,.
[13] Zhan Yuedong, Zhu Jianguo , Guo Youguang , Jin Jianxun, "Control of
proton exchange membrane fuel cell based on fuzzy logic", Proceedings
of the 26th Chinese Control Conference, 2007, China, IEEE.
[14] Christina N. Papadimitriou and Nicholas A.Vovos, "A Fuzzy Control
Scheme for Integration of DGs into a Microgrid ", IEEE, 2010.
[15] Ahmed M. Ibrahim, "Fuzzy logic for embedded systems application",
Newnes press, 2004.
[16] M. Azouz, A. Shaltout and M. A. L. Elshafei, "Fuzzy logic control of
wind energy systems", Proceedings of the 14th International Middle East
Power Systems Conference (MEPCON-10), Egypt, 2010.
[17] S. Lalouni, D. Rekioua, T. Rekioua and E. Matagne, "Fuzzy logic
control of stand-alone photovoltaic system with battery storage", Journal
of Power Sources, Vol. 193, PP. 899-907, 2009.
[18] Ch. Ben Salah, M. Chaaben, M. Ben Ammar, "Multi-criteria fuzzy
algorithm for energy management of a domestic photovoltaic panel",
Renewable Energy Vol. 33, PP. 993 -1001, 2008.
[19] Soteris A Kalogiroua, Soa Pantelioub, Argiris Dentsoras, "Artificial
neural networks used for the performance prediction of a thermosiphon
solar water heater", Renewable Energy, Vol., 18, PP., 87-99, 1999.
[20] James A. Freeman, David M. Skapura, ''Neural networks algorithms,
applications, and programming techniques'', Addison-Wesley Publishing
Company, Inc., Paris, 1991.
[21] M.N. Cirstea, A. Dinu, J.G. Khor, M. McCormick, "Neural and fuzzy
logic control of drives and power systems", Replika Press Delhi , India,
2002.
[22] Soteris A. Kalogirou, "Prediction of flat-plate collector performance
parameters using artificial neural networks", Solar Energy, Vol., 80, PP.,
248-259, 2006.
[23] Adnan Sozen, Tayfun Menlik, Sinan Unvar, "Determination of
efficiency of flat-plate solar collectors using neural network approach",
Expert Systems with Applications, Vol., 35, PP., 1533-1539, 2008.
@article{"International Journal of Electrical, Electronic and Communication Sciences:59997", author = "Doaa M. Atia and Faten H. Fahmy and Ninet M. Ahmed and Hassen T. Dorrah", title = "Design and Control of PEM Fuel Cell Diffused Aeration System using Artificial Intelligence Techniques", abstract = "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.", keywords = "PEM fuel cell, Diffused aeration system, Artificialintelligence (AI) techniques, neural network control, fuzzy logiccontrol", volume = "5", number = "9", pages = "1230-8", }
