Design and Control Strategy of Diffused Air Aeration System
During the past decade, pond aeration systems have
been developed which will sustain large quantities of fish and
invertebrate biomass. Dissolved Oxygen (DO) is considered to be
among the most important water quality parameters in fish culture.
Fishponds in aquaculture farms are usually located in remote areas
where grid lines are at far distance. Aeration of ponds is required to
prevent mortality and to intensify production, especially when
feeding is practical, and in warm regions. To increase pond
production it is necessary to control dissolved oxygen. Artificial
intelligence (AI) techniques are becoming useful as alternate
approaches to conventional techniques or as components of
integrated systems. They have been used to solve complicated
practical problems in various areas and are becoming more and more
popular nowadays. This paper presents a new design of diffused
aeration system using fuel cell as a power source. Also fuzzy logic
control Technique (FLC) is used for controlling the speed of air flow
rate from the blower to air piping connected to the pond by adjusting
blower speed. MATLAB SIMULINK results show high performance
of fuzzy logic control (FLC).
[1] Lopa Ghosh and G.N. Tiwari, "computer modeling of dissolved oxygen
performance in greenhouse fishpond: an experimental validation",
international journal of agricultural research, Vol. 3, PP. 83-97, 2008.
[2] Connie D. DeMoyera, Erica L. Schierholza, John S. Gullivera, Steven C.
Wilhelms," Impact of bubble and free surface oxygen transfer on
diffused aeration systems", Water Research , Vol.37, PP. 1890-1904,
2003.
[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] Claude E. Boyd ,"Pond water aeration systems" Aquacultural
Engineering Vol.,18 PP., 9-40, 1998.
[7] Marcos E. C. Oliveira and Adriana S. Franca, "Analysis of Oxygen
Transfer Performance on Sub-surface Aeration Systems", International
Communications Heat and Mass Transfer, Vol., 25, PP., 853-862, 1998.
[8] M.T. Iqbal, "Modeling and control of a wind fuel cell hybrid energy
system", Renewable Energy Vol., 28, PP., 223-237, 2003.
[9] John e. Huguenin, John colt, "design and operating guide for aquaculture
seawater systems", second ed., library of congress cataloging in
publication data, 2002.
[10] James A. Mueller, William C. Boyle, H. Johannes Pöpel," aeration:
principles and practice", CRC press, 2002.
[11] 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), Cairo Univ., Egypt,
December 19-21, 2010.
[12] 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.
[13] 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.
[1] Lopa Ghosh and G.N. Tiwari, "computer modeling of dissolved oxygen
performance in greenhouse fishpond: an experimental validation",
international journal of agricultural research, Vol. 3, PP. 83-97, 2008.
[2] Connie D. DeMoyera, Erica L. Schierholza, John S. Gullivera, Steven C.
Wilhelms," Impact of bubble and free surface oxygen transfer on
diffused aeration systems", Water Research , Vol.37, PP. 1890-1904,
2003.
[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] Claude E. Boyd ,"Pond water aeration systems" Aquacultural
Engineering Vol.,18 PP., 9-40, 1998.
[7] Marcos E. C. Oliveira and Adriana S. Franca, "Analysis of Oxygen
Transfer Performance on Sub-surface Aeration Systems", International
Communications Heat and Mass Transfer, Vol., 25, PP., 853-862, 1998.
[8] M.T. Iqbal, "Modeling and control of a wind fuel cell hybrid energy
system", Renewable Energy Vol., 28, PP., 223-237, 2003.
[9] John e. Huguenin, John colt, "design and operating guide for aquaculture
seawater systems", second ed., library of congress cataloging in
publication data, 2002.
[10] James A. Mueller, William C. Boyle, H. Johannes Pöpel," aeration:
principles and practice", CRC press, 2002.
[11] 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), Cairo Univ., Egypt,
December 19-21, 2010.
[12] 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.
[13] 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.
@article{"International Journal of Information, Control and Computer Sciences:51031", author = "Doaa M. Atia and Faten H. Fahmy and Ninet M. Ahmed and Hassen T. Dorrah", title = "Design and Control Strategy of Diffused Air Aeration System", abstract = "During the past decade, pond aeration systems have
been developed which will sustain large quantities of fish and
invertebrate biomass. Dissolved Oxygen (DO) is considered to be
among the most important water quality parameters in fish culture.
Fishponds in aquaculture farms are usually located in remote areas
where grid lines are at far distance. Aeration of ponds is required to
prevent mortality and to intensify production, especially when
feeding is practical, and in warm regions. To increase pond
production it is necessary to control dissolved oxygen. Artificial
intelligence (AI) techniques are becoming useful as alternate
approaches to conventional techniques or as components of
integrated systems. They have been used to solve complicated
practical problems in various areas and are becoming more and more
popular nowadays. This paper presents a new design of diffused
aeration system using fuel cell as a power source. Also fuzzy logic
control Technique (FLC) is used for controlling the speed of air flow
rate from the blower to air piping connected to the pond by adjusting
blower speed. MATLAB SIMULINK results show high performance
of fuzzy logic control (FLC).", keywords = "aeration system, Fuel cell, Artificial intelligence (AI)
techniques, fuzzy logic control", volume = "6", number = "3", pages = "281-5", }