计算机科学
智能电网
楼宇自动化
能源消耗
负荷管理
楼宇管理系统
网格
信息和通信技术
需求响应
节能
负载平衡(电力)
数据收集
工程类
控制(管理)
万维网
电
人工智能
几何学
热力学
物理
数学
电气工程
统计
作者
Mahmoud A. Alahmad,Yuye Peng,Evans Sordiashie,Lana El Chaar,Nasser Aljuhaishi,Hamid Sharif
出处
期刊:International Conference on Innovations in Information Technology
日期:2013-03-01
卷期号:: 60-65
被引量:5
标识
DOI:10.1109/innovations.2013.6544394
摘要
Through combining Information and Communication Technologies (ICT), advanced instrumentation, system intelligence, and information on the end user, the smart grid will increase building energy efficiency and conservation. Demand Side Management (DSM) programs serve as an aid in energy conservation and management strategies as well as in the collection of real-time consumption information data. Specifically, as proposed in this paper, real-time, fine-grain consumption data at the point of use in buildings can be used by building energy managers, utilities, and the end user for planning, load forecasting, and feedback for providing information that may lead to end user behavior change. This paper focuses on the development of node-level very short time load forecasting (NL-VSTLF), and specifically on a framework for the utilization of real-time data at the point of use for advancing research in the area of building-very short term load forecasting. This proposed framework will be the foundation for variable one minute to hourly and daily load forecasting using an aggregate of all active nodes in real-time.
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