Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594754
Title: Malaysia building energy estimation
Author: Rahman, Ismail Abdul
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2005
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Abstract:
This thesis concerns building energy simulation for Malaysian conditions. The simulations were done using IES software. Hourly weather data required by the program were prepared from weather data obtained from the Malaysian Meteorological Office. A Typical Weather Year was developed by statistical selection from 19 years of daily weather data from 1980 to 1998. Four weather variables (dry bulb temperature, global solar radiation, relative humidity and wind speed) were considered in the selection. The selection was done purely using Finkelstein-Schafer statistics. Typical Weather Year hourly data was generated from the daily values because the available hourly data was incomplete. The generation applied models that were created using one year of hourly data (1998). The direct and diffuse solar radiation data required by the simulation program were lacking and therefore estimated by a model from the hourly global radiation. A model was developed from 1992 hourly solar radiation data but was unsatisfactory. The same data was used to select from among established models, and it was found that Lam's model was the most suitable for Malaysian conditions. A parametric study on the annual cooling load of a Malaysia office reference building revealed that the most important parameters of those studied are window-to-wall ratio, inside air set point temperature and occupancy density. This study also developed an annual energy model equation for the building using the multiple regression technique. Simulation of an actual building using a conservative value for air conditioning COP found that the simulated energy index was about 5% lower than the value stated in an energy study report. This supported the report, which stated that the building consumed more energy than it should. Energy regression model was applied to the actual building and it was found that the predicted cooling load was 17% lower than the simulated value. The difference is probably due to the effect of factors not considered in the model. Despite this difference, the energy model can be applied as simple tool for estimating the annual cooling load of an office building in Malaysia.
Supervisor: Dewsbury, Jonathan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.594754  DOI: Not available
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