Conference article

A Forecast of Effective Energy Efficient Policies for the Building Sector in Shanghai through 2050

Rui Xing
Keio University, Yokohama, Japan

Toshiharu Ikaga
Keio University, Yokohama, Japan

Manfred Strubegger
nternational Institute for Applied Systems Analysis (IIASA), Vienna, Austria

Download articlehttp://dx.doi.org/10.3384/ecp110573436

Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:56, p. 3436-3443

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Published: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

Currently in China; the energy consumption of buildings is increasing rapidly. In this study; we used a macro-model to forecast the energy consumption of buildings in Shanghai through 2050. Total energy consumption from 2000 to 2050 and the potential energy savings were projected for both the residential and commercial sectors. For urban residential buildings; we developed a forecast model for 2050 to estimate the potential energy savings of residential measures. Compared to the business-as-usual (BaU) scenario; implementation of residential measures achieved a 24% reduction in energy consumption. The reduction rate rose to 65% by combining the implementation of residential and electrical measures. For commercial buildings; we first used official statistical data to determine the energy intensities of air conditioning; lighting; computing; and other thermal uses for the base year 2000. Then; estimates of the labor force; GDP; and floor area were predicted through 2050 according to past growth patterns and the literature. Likewise; estimates for energy intensities through 2050 were projected. Energy-saving scenarios also were integrated into the commercial model. Compared to BaU scenario; implementation of commercial measures achieved an 80% reduction in energy consumption. The reduction rate increased to 99% by combining commercial and electrical measures.

Keywords

Shanghai; Energy consumption; Buildings; Forecasting

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