.png){kind=icon}
返回
A decision support system for the electrical power districting problem
.png){kind=icon}
OA
AI
DOI：10.1016/S1344-6223(02)00033-0.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Many national electricity industries around the globe are being restructured from regulated monopolies to deregulated marketplaces with competitive business units. The business units responsible for transmission and distribution must be given physical property rights to certain parts of the power grid in order to provide reliable service and make effective business decisions. However, partitioning a physical power grid into economically viable districts (distribution companies) involves many considerations. We refer to this complex problem as the electrical power districting problem (EPDP). This research identifies the fundamental characteristics required to appropriately model and solve an EPDP. The proposed solution methodology is implemented as a decision support system (DSS) featuring a visualization tool that allows decision makers (DMs) to explore what we refer to as a soft efficient frontier. This DSS was found to effectively support DMs at The World Bank in solving an EPDP in the context of a case study for the Republic of Ghana. (C) 2002 Elsevier Science B.V. All rights reserved.
Keyword:
decision support systems
electric utility deregulation
multi-criteria decision making
districting
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.8
论文数:
3.8K
被引数:
1.5W
机构
暂无机构信息
引用论文
.png){kind=icon}
A sampling-based method for generating nondominated solutions in stochastic MOMP problems一种基于采样的方法，用于生成随机MOMP问题中的非支配解
PREAI
分享收藏
Volume and complexity bounded simplification of solid model represented by binary space partition
PREAI
分享收藏
查看更多内容