Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/3014
Title: Analysis of the electricity demand trend in HKSAR in relation to energy efficiency of commercial buildings
Authors: Lee, Sung-kong
Subjects: Hong Kong Polytechnic University -- Dissertations
Commercial buildings -- Energy conservation -- China -- Hong Kong
Electric power consumption -- China -- Hong Kong -- Forecasting
Issue Date: 2003
Publisher: The Hong Kong Polytechnic University
Abstract: Energy required for cooling system in commercial buildings in a sub-tropical climate, as in Hong Kong, is substantial and costly for regular commercial operation. This thesis reports on an investigation of the electricity demand in Hong Kong in the short-run and long-run by studying the energy consumption sectors, the historical energy consumption, the macro economic factors and the energy efficiency measures in commercial buildings. An initial multiple linear regression model is established, which gives a basic relation of the energy and the influencing economic parameters. Estimates of the future energy demand are made in this study using time series analysis. The co-integration approach is then adopted to examine the electricity consumption with macro economical factors and buildings development. Stationarity of the economic variables under time series analysis is achieved by differencing approach and verified via unit root test process. For the prediction of the long-run electricity demand, an error correction model is developed to overwrite the statistics inferences from the time series analysis. Changes of electricity load caused by building envelope designs, lighting intensity, fan and chiller efficiency are investigated by simulation using a reference commercial building and the building energy programme DOE-2.lE. Then the influence of building energy efficiency and growth of commercial building stock on the long-run electricity demand is determined by putting the simulated building energy requirement into the error correction regression model. The results will contribute to the know-how of electricity supply and demand for the local economy and serve as a reference for energy planning and policy.
Description: xiv, 122 leaves : ill. ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577M BSE 2003 Lee
Rights: All rights reserved.
Type: Thesis
URI: http://hdl.handle.net/10397/3014
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