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Currrent Issue: Volume 4, Number 2, 2016

Article

Household Electricity Consumption of Middle Class Family in Chiitagong - A Case Study

1Department of Statistics, University of Chittagong, Chittagong, Bangladesh


American Journal of Energy Research. 2016, 4(2), 35-41
doi: 10.12691/ajer-4-2-2
Copyright © 2016 Science and Education Publishing

Cite this paper:
Md Rokonuzzaman, Sharmin Jahan, Md Shahidul Haque. Household Electricity Consumption of Middle Class Family in Chiitagong - A Case Study. American Journal of Energy Research. 2016; 4(2):35-41. doi: 10.12691/ajer-4-2-2.

Correspondence to: Md  Rokonuzzaman, Department of Statistics, University of Chittagong, Chittagong, Bangladesh. Email: rokonuzzaman@cu.ac.bd

Abstract

Introduction: Electricity is a necessity in the modern world. Electricity has attained a very important place in every household on this planet. It is a major contributor towards improvement of the standard of living of any individual, family and society at large. The aims of this study is to find out the monthly average household electricity consumption and fit a suitable time series model to predict the electricity use. Data and Analysis: A time series monthly electricity uses data of a middle class family in Chittagong from January 2001 to November 2015 is considered in this analysis. To check variability the descriptive statistics and different types of graphs are used. The volatility model ARCH family regression with ARIMA disturbances model is used for forecasting. Chow test statistic is used for checking the structural breaking point of the dataset. Results & Conclusion: From the ACF and PACF function we get the cut off point for AR and MA part are 2 and 3 respectively. Further as ARCH effect is significant for this data set we use ARCH family regression with ARMA disturbances model, After comparing the different value of the parameters, ARCH(1) with ARIMA (3,0,2) disturbances is best fit for this data set. There have a structural break point for the month of December in 2010. Before this date data, ARCH (1) regression family with ARIMA (2,0,2) disturbance is the best fitted model for the analysis. And for the post data follows only ARIMA(1,0,1) disturbance is the best fitted model for this analysis. Recommendation: For forecasting of the monthly electricity uses of a middle class family in Chittagong, ARCH(1) with ARIMA (3,0,2) disturbances time series model can be used. For better prediction one can consider to select a representative size of sample families with at least 20 years data. Also some covariates like family size and electronic items used in the family can be considered and can try to fit a GARCH or TGARCH model.

Keywords

References

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Article

Experimental Investigation of Mass Transfer in a Channel of Contacting Conditioner

1Heat-and-Power Engineering Department, NTUU “Kyiv polytechnic institute”, Kyiv, Ukraine


American Journal of Energy Research. 2016, 4(2), 27-34
doi: 10.12691/ajer-4-2-1
Copyright © 2016 Science and Education Publishing

Cite this paper:
I. M. Kuzmenko, O. V. Makarchuk. Experimental Investigation of Mass Transfer in a Channel of Contacting Conditioner. American Journal of Energy Research. 2016; 4(2):27-34. doi: 10.12691/ajer-4-2-1.

Correspondence to: I.  M. Kuzmenko, Heat-and-Power Engineering Department, NTUU “Kyiv polytechnic institute”, Kyiv, Ukraine. Email: ozirno@ukr.net

Abstract

Mass transfer coefficient for contacting conditioning is determined experimentally and theoretically for steady air. Contribution of diffusion and convection component into mass transfer is estimated. The assessment showed that the contribution of the convection component into mass transfer can be neglected. Thickness of diffusional mass transfer layer was experimentally measured and it less than the theoretical values of displacement layer thickness till 10 times. Therefore the experimental value of mass transfer coefficient exceeds by one order the theoretically calculated ones. The criteria equation is recommended for calculation of mass transfer coefficient at steady air flow in a channel.

Keywords

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