A Simple Approach for Building Cooling Load Estimation

Ansari, Firoz Ahmad; Mokhtar, A. S.; Abbas, K. A.; Adam, Nor Maria

doi:10.3844/ajessp.2005.209.212

Cited by 41 publications

(12 citation statements)

References 2 publications

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“…2 [21]. Overview, the thickness is a function of the following: the building type, function, shape, orientation, construction materials, climatic conditions, insulation material and cost, energy type and cost, and the type and efficiency of air-conditioning system [22][23][24][25]. Hasan [26] used the life-cycle cost analysis to determine optimum insulation thicknesses.…”

Section: Optimization Of Insulation Thickness: a Reviewmentioning

confidence: 99%

Study of the economical and optimum thermal insulation thickness for buildings in a wet and hot tropical climate: Case of Cameroon

Nematchoua

Raminosoa

Mamiharijaona

et al. 2015

Renewable and Sustainable Energy Reviews

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a b s t r a c tIn Cameroon, these last centuries, an increase in energy demand for cooling and heating in buildings has been witnessed all over the world. Solutions must be proposed by researchers and specialists of buildings to remedy this situation. In this study, a literature review on the thermal insulation applications to external walls of buildings was presented, and a case was investigated in a tropical wet and hot climate. The economic model including the cost of insulation material and the present value of energy consumption and the cost over a lifetime of 22 years of the building, were used to find the optimum insulation thickness, energy saving, and payback period, for buildings in Cameroon. Materials that extruded polystyrene were chosen and used for two typical wall structures (Concrete block (HCB) and compressed stabilized earth block wall (CSEB)). The yearly cooling transmission loads, according to wall orientations and percentage of radiation blocked were calculated using the explicit finite-difference method under steady periodic conditions. As a result, it was found that the lowest value of optimum insulation thickness (0.09 m) and energy savings (79.80%) were obtained for the south-oriented wall, while the payback period (4.73years) was the highest on the same face compared to all wall orientations. Insulation optimum thickness was higher in the HCB wall (0.0983 m) than in CSEB wall (0.0958 m), however, the payback period was the weakest for the HCB wall compared to the other wall type.

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Section: Optimization Of Insulation Thickness: a Reviewmentioning

confidence: 99%

Study of the economical and optimum thermal insulation thickness for buildings in a wet and hot tropical climate: Case of Cameroon

Nematchoua

Raminosoa

Mamiharijaona

et al. 2015

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

show abstract

“…For applications in the field of HVAC systems, quantitative predictions are often used and mathematical methods and statistics along with probability theory are applied to collect and deal with large amount of historical data [7] . In the HVAC field, how to predict the building cooling load accurately attracts researchers' attention all the way [8][9][10][11][12][13][14][15] . Several prediction methods have ever been adopted, such as the Admittance and Fourier methods [16] , the correlation method [17,18] , the transfer function method [19] , the Monte Carlo simulation method [20] , and so on.…”

Section: Related Workmentioning

confidence: 99%

Prediction on Hourly Cooling Load of Buildings Based on Neural Networks

Chaowen¹,

Dong²

2015

IJSH

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Energy conservation and indoor environment concerns have motivated extensive research on various aspects of control of Heating, Ventilating and AirConditioning (HVAC) and building systems. The study on optimal operation as well as modeling of HVAC and building systems is one of the fastest growing fields that contribute to saving energy and improving indoor environment of buildings. The reasonable operation adjustment is one of the main methods to improve the energy efficiency. Cooling load prediction is the foundation of the optimization operation. This paper is devoted to the development of a comprehensive modeling of cooling load for a large building with ice-storage systems in Beijing, China. The models describe the dynamics of cooling load, outdoor climate parameters and indoor parameters as one multi-variable nonlinear system in a way that is useful for prediction analysis. The cooling load data collected is from June to September, and then the method of similarity for both longitudinal and transverse waveforms is used to judge whether there is abnormal data. The optimal parameter setting in the proposed model is studied. Principle Component Analysis (PCA) method was applied to select input parameters. A load prediction model has been constructed based on BP neural networks. Taking account of the generalization ability of neural networks, this paper has chosen the bayesian regularization algorithm, which can get better fitting effect than other training algorithms, to train the neural networks. Then, the BP neural network model is used for the summer hourly cooling load prediction of the business building. Evaluation of the prediction accuracy of the proposed models is based on the root mean square error (RMSE). The results show that the prediction model can accurately predict the future hourly load of 1 week and 1 day, with the prediction error at 1.60% and 1.18% respectively. The analysis shows that this model is suitable for the practical engineering application and can provide a basis for optimal operation of air conditioning control systems of large public buildings.

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“…Even though in Ethiopia the properly recorded solar radiation data is available only for Addis Ababa (NASA, 2010), the data used in sizing and simulation is based on data recorded for more than 10 years by the NASA Surface meteorology and Solar Energy: RETScreen Data (Ansari and Mokhtar, 2005).…”

Section: Solar Energy Potentialmentioning

confidence: 99%

Optimal Design of a Standalone Photovoltaic Power Supply System for Air Conditioning Application at Samara University as an Alternative to Diesel Generator Source

Bogale¹,

Alemayehu²

2013

Sci. Technol. Arts Res. J.

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Article InformationThe aim of this paper is to optimally design a stand alone photovoltaic power supply system for air conditioning application at Samara University to be used as an alternative to diesel generator supply. Samara University is established in samara town, Afar region and has an average daily radiation of 6.10kwh/m 2 , sun shine duration of about 10 hours. This condition invites the use of photovoltaic system as an alternative primary energy source to replace the existing diesel generator supply system. Therefore in order to use this energy source for air conditioning application, the cooling load of the building, 628 tons, is estimated using Newton's thumb rule. The evaporative air conditioning system which is sometimes called desert cooler is selected to condition the estimated cooling load of the dwelling room. The sizing method (numerical method and HOMER software tools) is complementarily used to design a standalone photovoltaic power supply system. Finally, the metric value of the present worth is US $ 3,302,066 and its simple payback is 6.6 years, and this foreseen that the attractiveness of photovoltaic power system as one of renewable energy to be used as an alternative to diesel generator in the near future.

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A Simple Approach for Building Cooling Load Estimation

Cited by 41 publications

References 2 publications

Study of the economical and optimum thermal insulation thickness for buildings in a wet and hot tropical climate: Case of Cameroon

Study of the economical and optimum thermal insulation thickness for buildings in a wet and hot tropical climate: Case of Cameroon

Prediction on Hourly Cooling Load of Buildings Based on Neural Networks

Optimal Design of a Standalone Photovoltaic Power Supply System for Air Conditioning Application at Samara University as an Alternative to Diesel Generator Source

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