Electricity demand-side management for an energy efficient future in China : technology options and policy priorities

The main objective of this research is to identify robust technology and policy options which achieve substantial reductions in electricity demand in China's Shandong Province. This research utilizes a scenario-based approach to identify sensible and feasible energy efficiency and load reduction strategies. The research consists of technical analyses through the development of an hourly load simulation model to study the time and temperature sensitive impacts on electricity demand growth by different demand-side management (DSM) scenarios and a policy analysis to formulate policy priorities based on the socio-economic and environmental realities in China. This bottom-up comprehensive study helps inform decision-making given the technological, consumption and socio-economic conditions in large-scale electricity grid systems of Shandong and China, thus preferred DSM strategies are identified, and sensible policy recommendations are made with respect to Shandong province and China as a whole. This study developed a computer-based modeling tool for peak-load based electric demand analysis and long-term projections.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2005

Author dc:creator

• Cheng, Chia-Chin

Advisor dc:contributor.advisor

• Stephen R. Connors.

• Engineering Systems Division.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/33679

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/33679