Design and Control Strategy of Diffused Air Aeration System

Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1056056

References:

[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.