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Computational Analysis for Estimating Electricity Wastage in Buildings

by P. A. Ozoh, A. A. Adigun, L. O. Omotosho
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 50
Year of Publication: 2019
Authors: P. A. Ozoh, A. A. Adigun, L. O. Omotosho
10.5120/ijca2019919423

P. A. Ozoh, A. A. Adigun, L. O. Omotosho . Computational Analysis for Estimating Electricity Wastage in Buildings. International Journal of Computer Applications. 178, 50 ( Sep 2019), 36-42. DOI=10.5120/ijca2019919423

@article{ 10.5120/ijca2019919423,
author = { P. A. Ozoh, A. A. Adigun, L. O. Omotosho },
title = { Computational Analysis for Estimating Electricity Wastage in Buildings },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2019 },
volume = { 178 },
number = { 50 },
month = { Sep },
year = { 2019 },
issn = { 0975-8887 },
pages = { 36-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number50/30894-2019919423/ },
doi = { 10.5120/ijca2019919423 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:53:40.850254+05:30
%A P. A. Ozoh
%A A. A. Adigun
%A L. O. Omotosho
%T Computational Analysis for Estimating Electricity Wastage in Buildings
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 50
%P 36-42
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Computational analysis is a collection of procedures that is used to process large amounts of data with a view of obtaining results based on processed data and as a result, getting their behavioral pattern. The main goal of this research is to determine the amount of electricity wastage and to study occupant’s attitude towards energy conservation. In this research, computational techniques are applied to analysis of data collected collected from the Faculty of Computer Science and Information Technology (FCSIT) building, Universiti Malaysia Sarawak (UNIMAS), Malaysia which is considered as the case study. Data collection is carried out by questionnaire analysis of electricity consumers. The questionnaires consists of information on building occupants turning off lights in rooms with no presence, and occupants limiting electricity consumption in the building. This was achieved by administering questionnaires on the FCSIT staffs and students. The information collected provides real-time data on electricity consumption for the building over different periods of time. To effectively model electric wastage in the building, a simulation must be carried out to accurately model the actual amount of electricity consumed in the building and at what period of time. The simulation is based on the real system is built to estimate the amount of electricity wastage at the FCSIT building. Electricity consumption in the building is based on real electricity consumption using statistical analysis. A goodness-tests which consist of the Chi-Squaregoodness-test is computed to ensure that the resulting model is reliable and adequate.

References
  1. Aswani, A., Master, N., Taneja, J., Culler, D. & Tomlin, C. (2012). Reducing Transient and Steady State Electricity Consumption in HVAC Using Learning-Based Model-Predictive Control. Proceedings of the IEEE, Vol. 100, No. 1, pp 240–253.
  2. Banks, J., Carson, J., Nelson, B., Nicol, D. (2000). Discrete-Event System Simulation, Prentice Hall (3rd ed.).
  3. Farhanieh, B. & Sattari, S. (2006). Simulation of Energy Saving in Iranian Buildings using Integrative Modelling for Insulation. Renewable Energy, Vol. 31, No. 4, pp 417–425.
  4. Hartungi, R. & Jiang, L. (2011). Achieving Energy Efficiency in Office Building. Smart Innovation, Systems and Technologies, Vol. 7, pp 1-13.
  5. Iqbal, I. & Al-Homoud, M. (2007). Parametric Analysis of Alternative Energy Conservation Measures in an Office Building in Hot and Humid Climates. Building and Environment, Vol. 42, No. 5, pp. 2166-2177.
  6. Lei, J. & Ning, H. (2009). A New Method of Load-Shedding Control on Centrifugal Water Chiller Sequencing. 2009 4th IEEE Conference on Industrial Electronics and Applications, pp 3204–3209.
  7. Office of Energy Efficiency. (2010). Retrieved from http://Bench marking energy performance.
  8. Oldewurtela, F., Parisiob, A., Jonesc, C. N., Gyalistrasa, D., Gwerderd, M., Stauche, V. & Morari, M. (2012). Use of Model Predictive Control and Weather Forecasts for Energy Efficient Building Climate Control. Energy and Buildings, Vol. 45, pp 15–27.
  9. Ozoh, P., Abd-Rahman, S., Olayiwola, M. (2018). Developing Predictive Models using Typical Machine Learning and Computational Techniques, Analele Universităţii “Tibiscus”, Timişoara, Vol. 16, No. 2, pp. 82-85.
  10. Ozoh, P; Olayiwola, M., Adigun, A. (2018). An In- Depth Study of Typical Machine Learning Methods via Computational Techniques, Analele Universităţii “Tibiscus”, Timişoara, Vol. 16, No. 2, pp 77-81.
  11. World Energy Outlook (2019, May 31). Retrieved from. doi:10.1787/weo-2013-en/
  12. Yao, S., Song, Y., Zhang, L. & Cheng, X. (2000). Wavelet Transform and Neural Networks for Short-Term Electrical Load Forecasting. Energy Conversion and Management, Vol. 41, No. 18, pp 1975–1988.
  13. Zamri, N., Mohammad, Z. &Yusof, M. (2011). Study of Energy Efficiency Opportunities in UTHM. International Journal of Environmental and Ecological Engineering, Vol. 5, No. 5, pp 313-319.
Index Terms

Computer Science
Information Sciences

Keywords

Computational analysis behavioral pattern simulation energy savings goodness-tests.

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