Real Time Energy Management and Load Forecasting in Smart Grid using CompactRIO

被引：8

作者：

Thiyagarajan, K. ^{[1
]}

SaravanaKumar, R. ^{[1
]}

机构：

[1] VIT Univ, Vellore 632014, Tamil Nadu, India

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELLING AND SECURITY (CMS 2016) | 2016年 / 85卷

关键词：

Load forecasting; Smart Grid; Monitoring; CompactRIO; Artificial neural networks;

D O I：

10.1016/j.procs.2016.05.250

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The energy management is the process of monitoring, controlling, and conserving energy in building or organization. In this paper a real time energy management and load forecasting in smart grid based on the NI CompactRIO platform is done. A console is created to monitor the electrical load connected with the smart grid. The CompactRIO used here is to get the real time data from different electrical loads and the data is transferred and stored through console via Ethernet. Load forecasting is done by past and present data of electrical load connected with the grid using artificial neural networks. (C) 2016 The Authors. Published by Elsevier B.V.

引用

页码：656 / 661

页数：6