Utilization of the Internet of Things for Real-time Data Collection and Storage of Big Data as it Relates to Improved Demand Response

Shawyun Sariri, Reza Ghorbani, Volker Schwarzer

2016

Abstract

Demand response programs are viewed as a solution to counter the increasing demand in energy consumption, as well as a way to combat the stochastic nature of renewable sources within the current grid infrastructure. In order to apply an efficient demand response program, it is first necessary to understand the power consumption behaviours within a power grid system. Obtaining large quantities of consumer power consumption data will al-low the ability to tailor a demand response program to efficiently implement control decisions in real-time. The programs are a cost effective alternative to high priced spinning reserves and energy storage. The focus of data collection will be on dense urban environments, which provide a number of factors that can be evaluated as they relate to an efficient demand response program. The island of Oahu was the location of a pilot program to test the feasibility of large data collection and storage. A smart metering device collected high resolution data, which was transmitted to a server where load forecasting and peak shaving decisions could be calculated. The design of the pilot system and initial results of the large data collection are discussed.

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Paper Citation


in Harvard Style

Sariri S., Ghorbani R. and Schwarzer V. (2016). Utilization of the Internet of Things for Real-time Data Collection and Storage of Big Data as it Relates to Improved Demand Response . In Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD, ISBN 978-989-758-183-0, pages 232-242. DOI: 10.5220/0005878002320242


in Bibtex Style

@conference{iotbd16,
author={Shawyun Sariri and Reza Ghorbani and Volker Schwarzer},
title={Utilization of the Internet of Things for Real-time Data Collection and Storage of Big Data as it Relates to Improved Demand Response},
booktitle={Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD,},
year={2016},
pages={232-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005878002320242},
isbn={978-989-758-183-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD,
TI - Utilization of the Internet of Things for Real-time Data Collection and Storage of Big Data as it Relates to Improved Demand Response
SN - 978-989-758-183-0
AU - Sariri S.
AU - Ghorbani R.
AU - Schwarzer V.
PY - 2016
SP - 232
EP - 242
DO - 10.5220/0005878002320242