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|Title:||Methodology for forecasting residential energy demand in China : an approach to technological impacts||Authors:||Liao, Zaiyi||Keywords:||Energy consumption -- China
Power resources -- China
Hong Kong Polytechnic University -- Dissertations
|Issue Date:||2001||Publisher:||The Hong Kong Polytechnic University||Abstract:||This thesis is concerned with the development of a methodology for forecasting the residential energy demand in China with a focus on the technological impacts. The methodology can be used to study the impacts of the technologies that are utilised to improve the energy efficiency in residential buildings by the current practice in China. It can also be used to forecast the residential energy demand under different scenarios of economic growth and energy price. Through a literature study it has been found that low energy efficiency persists in the majority of the current residential stock and consequently a lot of technologies have been utilised in both retrofit and new projects. However a comprehensive understanding on the impact of the technologies is absent. Furthermore, it is important to understand the trend of the residential energy consumption because both the residential stock and the residential energy intensity exhibit a consistently high growth. The absence of a methodology for achieving these understandings has been evidenced through the literature study and justifies this PH.D project.
A bottom-up approach has been made and accordingly an innovative multiple-level of forecasting model (MLFM) has been developed for forecasting the residential energy consumption at different levels, including the community level, the regional level, and the national level. It has four sub models, including RHEM (Residential Household Energy Model), RCEM (Residential Community Energy Model), RREM (Regional Residential Energy Model), and NREM (National Residential Energy Model). The RHEM represents the energy consuming processes in individual households. The RCEM represents the energy consumption in individual residential communities. It classifies all individual households in a residential community into prototype households that can be represented in RHEM. It also accommodates an economy model that estimates how the concerned technologies will be utilised and how the energy behaviours of occupants will be affected in the future under different scenarios of economy and energy price. The RREM defines the universe of prototype communities and employ the RCEM to forecast their energy consumption. The NREM integrates all the regional consumption to forecast the national residential energy consumption. The frameworks of the MLFM and the method for collecting the relevant supporting data have been developed. However, this project is not aimed to completely develop the whole model. It is focused on the development of RHEM, RCEM and their integration. The model has been used to carry out a number of case studies on some practical problems. It has been found that the technological approaches of the current practice are not adequate enough to achieve their target of energy saving. The results also indicate that the growth of residential energy consumption can be controlled if appropriate economic incentives are introduced. However, it is likely that the residential energy consumption will continue growing at a consistently high rate in the next 10 to 15 years. The model covers the commercial energy sources and urban areas only. Uncommercial energy sources, such as biomass, mainly consumed in the rural areas are not accommodated in the current development. Therefore, it can only be applied to study commercial energy consumption of residential buildings in urban areas.
|Description:||268 leaves : ill. ; 30 cm.
PolyU Library Call No.: [THS] LG51 .H577P BSE 2001 Liao
|URI:||http://hdl.handle.net/10397/3747||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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