Browsing by Author "Falana, A."

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Energy and exergy analyses of malt drink production in Nigeria
(Elsevier Limited, 2010-12) Fadare, D. A.; Nkpubre, D. O.|.; Oni, A. O; Falana, A.; Waheed, M. A.; Bamiro, O. A
Energy requirements and exergy inefficiencies for processing of malt drink were estimated for a Nigerian brewery. The process was divided into twenty-one basic unit operations and grouped into four main group operations: silo house, brew house, filter room and packaging house. The energy intensity for processing a batch of 9.8 tonnes brew grains to 562 hl of malt drink was estimated as 261.63 MJ/hl consisting of electrical (41.01%), thermal (58.81%) and manual (0.19%) of the total energy. The most energy intensive group operation was the Packaging House operation, followed by the Brew House operation with energy intensities of 223.19 and 35.94 MJ/hl respectively. The exergy analysis revealed that the packaging house operation was responsible for most of the inefficiency (92.16%) followed by brew house operation (7.17%) and the silo house and filter room operations with less than 1%of the total exergy lost. The most exergy loss took place in the pasteurizer which accounted for 59.75% of the overall system inefficiency. Modification in the pasteurizer and use of spent grains as alternate source of energy in the steam boiler were recommended to improve the energy efficiency of the system.
In this work, three models are used to analyze the electric load capacity of a fast growing urban city and to estimate its future consumption. Ikorodu, the case-study location is a highly populated city whose energy demand is continuously increasing. The ultimate focus of this study is to establish a basis for the comparison of different electric load consumption for the existing populace and to provide estimates for the future planning of the city. In this work, three different models have been used to present more accurate load predictions and to enhance proper comparison of results. Among numerous mathematical and scientific models that are applicable to this kind of task, the compound-growth method, the linear model approach and the cubic model have been chosen to enhance diversity in load analysis. The futuristic scheme to be harnessed will fall within the ranges of values obtained from the three different models used in forecasting. This paper concludes with issues pertaining to economics of load utilization as it affects substantive planning.
(International Association of African Researchers and Reviewers, 2012-01) Eneje, I. S; Fadare, D. A.; Simolowo, O. E.; Falana, A.
In this work, three models are used to analyze the electric load capacity of a fast growing urban city and to estimate its future consumption. Ikorodu, the case-study location is a highly populated city whose energy demand is continuously increasing. The ultimate focus of this study is to establish a basis for the comparison of different electric load consumption for the existing populace and to provide estimates for the future planning of the city. In this work, three different models have been used to present more accurate load predictions and to enhance proper comparison of results. Among numerous mathematical and scientific models that are applicable to this kind of task, the compound-growth method, the linear model approach and the cubic model have been chosen to enhance diversity in load analysis. The futuristic scheme to be harnessed will fall within the ranges of values obtained from the three different models used in forecasting. This paper concludes with issues pertaining to economics of load utilization as it affects substantive planning.
Modeling of solar energy potential in Africa using an artificial neural network
(Science Hub Publishing, 2010) Fadare, D. A.; Irimisose, I.; Oni, A. O.|; Falana, A.
In this study, the feasibility of an artificial neural network (ANN) based model for the prediction of solar energy potential in Africa was investigated. Standard multilayered, feed-forward, back-propagation neural networks with different architecture were designed using NeuroSolutions®. Geographical and meteorological data of 172 locations in Africa for the period of 22 years (1983-2005) were obtained from NASA geo-satellite database. The input data (geographical and meteorological parameters) to the network includes: latitude, longitude, altitude, month, mean sunshine duration, mean temperature, and relative humidity while the solar radiation intensity was used as the output of the network. The results showed that after sufficient training sessions, the predicted and the actual values of solar energy potential had Mean Square Errors (MSE) that ranged between 0.002 - 0.004, thus suggesting a high reliability of the model for evaluation of solar radiation in locations where solar radiation data are not available in Africa. The predicted and actual values of solar energy potential were given in form of monthly maps. The solar radiation potential (actual and ANN predicted) in northern Africa (region above the equator) and the southern Africa (region below the equator) for the period of April – September ranged respectively from 5.0 - 7.5 and 3.5 - 5.5 kW h/m2/day while for the period of October – March ranged respectively from 2.5 – 5.5 and 5.5 - 7.5 kW h/m2/day. This study has shown that ANN based model can accurately predict solar radiation potential in Africa.
Modelling and forecasting periodic electric load for a metropolitan city in Nigeria
(2012-01) Eneje, I. S.; Fadare, D. A.; Simolowo, O. E.; Falana, A.
"In this work, three models are used to analyze the electric load capacity of a fast growing urban city and to estimate its future consumption. Ikorodu, the case-study location is a highly populated city whose energy demand is continuously increasing. The ultimate focus of this study is to establish a basis for the comparison of different electric load consumption for the existing populace and to provide estimates for the future planning of the city. In this work, three different models have been used to present more accurate load predictions and to enhance proper comparison of results. Among numerous mathematical and scientific models that are applicable to this kind of task, the compound-growth method, the linear model approach and the cubic model have been chosen to enhance diversity in load analysis. The futuristic scheme to be harnessed will fall within the ranges of values obtained from the three different models used in forecasting. This paper concludes with issues pertaining to economics of load utilization as it affects substantive planning. "