Evaluation and Modelling of Energy Consumption in a Selected Residential Building
[1]
Ogunoh Chika C., Building Services Engineering, South Bank University, London.
[2]
Ogunoh Peter E., Department of Building, Nnamdi Azikiwe University Awka, Anambra State, Nigeria.
[3]
Ogunoh Arinze Victor, Department of Industrial and Production Engineering, Nnamdi Azikiwe University Awka, Anambra State, Nigeria.
[4]
Ezeliora Chukwuemeka Daniel, Department of Industrial and Production Engineering, Nnamdi Azikiwe University Awka, Anambra State, Nigeria.
The study aimed at making use of regression techniques and autocorrelation to model and to analyze the energy consumption in Building using the data collected from daily meter reading. Energy consumption models developed for the selected building revealed that the independent variables used in the modelling contributed to the overall output of the model. The models show that the independent variables in the building explain 93% of the variations in energy consumption. Residual analysis of both models confirmed the overall reliability of the model using graphical analysis.
Building, Regression, Correlation, Energy Consumption, Autocorrelation, Feed Back and Temperature
[1]
Beggs C (2002), Energy: Management, Supply and Conservation. Oxford: Butterwort – Heinemann, Jordan hill, Oxford.
[2]
Dunster J.E, Michel I and Shorrock L. D (1994), Domestic Energy Factfiles: Owner Occupied Homes ref BR271, Local Authority Homes ref BR272 and Private Rented Homes ref BR273 (1994) Building Research Establishment, Garston, Watford.
[3]
FRPO (2003), Options to Reduce Energy Consumption by Encouraging Sub-Metering and Individual Billing in Multi-Residential Rental Dwellings, Executive summary submitted to the government of Ontario. Fair rental policy organization, Ontario.
[4]
Moss J.K and Moss K (1997), Energy Management and Operating Cost in Buildings. Spon Pr Publishers.
[5]
Darby S (2006), The Effectiveness of Feedback on Energy consumption: a review for Defra of the Literature on Metering, Billing and Direct Displays, Report Environmental change institute, University of Oxford.
[6]
Abdel-Aal R.E & Al-Garni A.Z (1996), Forecasting Monthly Electric Energy Consumption in Saudi Arabia Using Univariate Time-Series Analysis. Research paper, Energy research laboratory and King Fahd University of petroleum and minerals, Saudi Arabia.
[7]
Chambers J.M., Cleveland W.S, Kleiner B and Tukey A.P (1983), Graphical Methods of Data Analysis. The Wadswort Statistics/ Probability Series, Wadsworrth international group, Belmont, California.
