Study Of The Energy Performance Differences And Impact Factors Of Residential Buildings In The Cities Of Guangdong-Hong Kong-Macao Greater Bay Area

In recent years,Guangdong-Hong Kong-Macao Greater Bay Area(GBA),established according to one of the national development strategies of China,has attracted extensive attention.Its sustainable development is characterized as Low-carbon,energy-saving,and efficient.To reveal the residential energy consumption(REC)characteristics and trends of 11 GBA cities,the statistics for the nearly past two decades has been collected and the macro quantitative models has been developed.The main research contents and findings of this thesis are as follows:Firstly,according to the Lorentz curve theory,an allocation method of energy consumption statistics is proposed.Next,a city-level REC calculation model(CRECM)is developed based on this method.Since the CRECM is based on the Lorentz curve that can reflect the uneven energy consumption,it is able to estimate the unavailable city-level data according to the province-level statistics,which can effectively solve the problem of city's missing energy statistics.The REC of 11 GBA cities from 2000 to 2017 are calculated through CRECM.And then the energy consumption intensity(REC per household and REC per square meter)are obtained to compare the energy efficiency of different cities.The results show that the REC of 11 GBA cities except Hong Kong have grown significantly over the past 18 years.The total growth of GBA cities ranges from 15% to 324%,with the average annual growth rate of 0.8%-8.9%.Meanwhile,there is a significant difference between the REC intensities of GBA cities.The coefficient of variance(CV)is 31-48%,but it has decreased year by year.Additionally,the decomposition result of Theil index reveals that 82.7-96.4% of the difference in electricity consumption of residential buildings in GBA comes from the development gap between Hong Kong and Macao SARs and the Pearl River Delta cities.Secondly,based on the STIRPAT theory,this study selects 6 impact factors,i.e.,per household population,per capita residential building area,per capita GDP,cooling degree days,city longitude,and latitude,to perform regression analysis of the per household electricity consumption of the residential buildings in GBA.It is found that both household size and GDP per capita have significant positive effect on the residential electricity consumption per household in GBA cities,with regression coefficients of 0.919 and 0.600.Meanwhile,the residential building floor area per capita do not influence residential electricity consumption intensity,since the per capita residential building area of some GBA cities did not increase much over the past 18 years.Moreover,regarding climate,only the latitudes of cities have significant negative impact on residential electricity consumption per household,which decreased by 0.269% for every 1 ° increase of latitude.Thirdly,using the classification theory of policy instruments,the current building energy efficient policies in China are divided into mandatory policies and regulations,economically incentive measures and voluntary schema instruments.Based on this classification,this study reviews the building energy conservation policies issued in China from the 1980 s to the present and analyzes the related competent institutions,the system of related policies and regulations,and the effects of the policy implementation.After reviewing the national policy context,this study reviews the energy saving policies of the residential buildings in GBA and analyzes the policy structure and its developing trends.It is found that a large part of the policies are mandatory policies and regulations,and there are few economically incentive measures or voluntary schema instruments.At last,this study proposes advices for the adjustment of the implementation of ‘total building energy consumption control' and the general standards among Guangdong,Hong Kong,and Macao.To sum up,both CRECM and the analysis of influencing factors in this thesis can provide robust data support for developing building energy efficiency policy for GBA cities as well as other cities across the country.