课题基金 / 基金详情

Japan Long-Term Research Visit: Techniques for Evaluating the Impact of Demand Side Management in the Japanese Electric Utility Industry

Japan Long-Term Research Visit: Techniques for Evaluating the Impact of Demand Side Management in the Japanese Electric Utility Industry
日本长期考察访问:评估日本电力行业需求侧管理影响的技术
批准号:
9201904
负责人:
Saifur Rahman
金额:
$11.82万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1992
资助国家:
美国
项目状态:
已结题
起止时间:
1992-09-01 至 1994-05-31

项目摘要

项目成果

Saifur Rahman的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
This award will support a ten month long-term visit by Professor Saifur Rahman, Department of Electrical Engineering, Virginia Polytechnic Institute, to Japan for a cooperative research project with researchers at the Tokyo Electric Power Company, (TEPCO). His co-hosts will be Mr. Toshiaki Ohashi, AI Technology Department, Computer and Communication Research Center and Mr. Akira Maeda, Technology Research Group, Research and Development Planning Department. The research will include a study of the techniques for evaluating the impact of demand side management (DSM) in the Japanese Electric Utility Industry. They will be dealing with the modeling of uncertainty related to demand side management activities. These uncertainties originate from the unknown customer response to the DSM programs, and their willingness or unwillingness to maintain interest in the program under less than ideal conditions. An attempt will be made to model such uncertainty using the "pairwise comparison" technique that Professor Rahman has applied in other fields of electric power engineering. Once such quantitative measures of uncertainty are available, they will be applied to a generation expansion model to examine the impacts of DSM on capacity needs. A new technique to model the load duration curve will be investigated which will facilitate the representation of DSM impacts on peak load, load factor and energy consumption. This will provide an analytical method to study the impact of DSM on capacity requirements. In the past, iterative methods have been applied to study these impacts. An analytical method would result in faster solutions with higher accuracy. The research has a comparative value and should also provide a potential methodology with which to evaluate DSM programs prior to their initiation. The research may also result in useful analytical techniques that are fundamentally different from presently used demand management evaluation methods. Professor Rahman is knowledgeable in a wide- range of topics related to power systems engineering. He is well-published in the area of power systems planning and is familiar with the power industry in Japan. TEPCO is the largest electric utility in Japan, and it is the largest privately owned power company in the world. It serves 22 million customers with a peak demand of approximately 50,000 MW making it an ideal utility in which to carry out direct load control studies. A successful development of the proposed methodology could be used to evaluate the impact of some new DSM programs in the U.S. electric utility industry. It is expected that this collaborative effort between the researchers will continue even after the formal agreement has terminated. It is also expected that a number of publications will result from the project.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
US-China Workshop: Identification of Challenges and Opportunities for Large Scale Deployment of the Smart Grid
US-Egypt Cooperative Research: Managing Grid Integration of Large-Scale Wind Power Parks using Energy Storage Technology and Demand Response
PFI: Role of the Smart Grid in Alleviating Electrical Power System Stress Conditions Through Demand Response
SGER: Intelligent Distributed Autonomous Power Systems (IDAPS): A Framework for a Resilient and Environmentally-Friendly Microgrid with Demand-Side Participation
国内基金
海外基金
基于Relm-β核转位激活EndMT促进肺动脉高压研究肺心汤预防 Long COVID 机制
维生素D调控巨噬细胞极化在改善“Long COVID”中作用和机制的分子流行病学研究
long non-coding RNA(lncRNA)-activatedby TGF-β(lncRNA-ATB)通过成纤维细胞影响糖尿病创面愈合的机制研究
  • 批准号:
    LQ23H150003
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2023
  • 负责人:
    厉怡
  • 依托单位:
Long-TSLP和Short-TSLP佐剂对新冠重组蛋白疫苗免疫应答的影响与作用机制
  • 批准号:
    --
  • 项目类别:
    面上项目
  • 资助金额:
    58万元
  • 批准年份:
    2021
  • 负责人:
    叶亮
  • 依托单位: