Improving Electric Power Industry Competitiveness Through the Application of Artificial Intelligence
人工智能应用提升电力行业竞争力
基本信息
- 批准号:9872500
- 负责人:
- 金额:$ 50万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:1998
- 资助国家:美国
- 起止时间:1998-09-01 至 2002-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Deregulation of the electric industry is forcing most utilites to be more competitive. To be competitive, utilities need people at all levels that are trained to deliver a better product, at a lower cost, with more reliability. The goal of this CRCD project entitled, "Improving Electric Power Industry Competitiveness Through the Application of Artificial Intelligence," is to help improve electric power utility competitiveness by incorporating, into the upper division undergraduate and graduate curriculum, instructional modules that can be used to train people in these critical areas. The instructional modules to be developed will focus in the area of the application of artificial intelligence to operation, control and simulation of electric power systems. These modules are based on already completed research at the University of Washington and Arizona State University. These modules will be completed with a team of technical researchers, instructional methodology experts and computer-based media specialists. All modules will be computer based and disseminated in multiple ways including via the Internet. Formative assessment will be ongoing throughout the life of the project. Instructional design will center around active learning strategies such as cooperative learning with emphasis on team methods; however, instructional design will also include components to appeal to the reflective learner as well as students with other learning styles.The results of this work is expected to enhance the ability of new graduates as well as electric power engineers perform in the rapidly changing, highly competitive world brought on by deregulation of the electric power industry.
电力行业的放松管制迫使大多数公用事业公司更具竞争力。为了具有竞争力,公用事业公司需要接受过培训的各级人员,以更低的成本和更高的可靠性提供更好的产品。CRCD项目名为“通过应用人工智能提高电力行业竞争力”,其目标是通过将可用于培训这些关键领域人员的教学模块纳入高年级本科生和研究生课程,帮助提高电力行业的竞争力。将开发的教学模块将重点放在将人工智能应用于电力系统的操作、控制和仿真领域。这些模块基于华盛顿大学和亚利桑那州立大学已经完成的研究。这些单元将由一个由技术研究人员、教学方法专家和计算机媒体专家组成的小组完成。所有模块都将以计算机为基础,并以多种方式传播,包括通过因特网。形成性评估将贯穿项目的整个生命周期。教学设计将围绕主动学习策略,如合作学习,强调团队方法;然而,教学设计也将包括吸引反思型学习者和其他学习风格的学生的组件。这项工作的结果有望提高应届毕业生的能力,以及电力工程师在电力行业放松管制带来的快速变化和高度竞争的世界中的表现。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Daniel Tylavsky其他文献
A Holomorphic embedding approach for finding the Type-1 power-flow solutions
- DOI:
10.1016/j.ijepes.2018.04.029 - 发表时间:
2018-11-01 - 期刊:
- 影响因子:
- 作者:
Yang Feng;Daniel Tylavsky - 通讯作者:
Daniel Tylavsky
Analytic continuation as the origin of complex distances in impedance approximations
- DOI:
10.1016/j.ijepes.2018.09.022 - 发表时间:
2019-02-01 - 期刊:
- 影响因子:
- 作者:
Songyan Li;Daniel Tylavsky - 通讯作者:
Daniel Tylavsky
Daniel Tylavsky的其他文献
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{{ truncateString('Daniel Tylavsky', 18)}}的其他基金
Expedited Award for Novel Research: A Globally Convergent Power Network Solver
新颖研究加急奖:全球融合电力网络求解器
- 批准号:
8714927 - 财政年份:1987
- 资助金额:
$ 50万 - 项目类别:
Standard Grant
Concurrent Processing of Power System Dynamic Simulations
电力系统动态仿真的并行处理
- 批准号:
8715715 - 财政年份:1987
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
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