DocumentCode
3695723
Title
Grid planning: Agent based approach for early notification of air conditioning loads to smart grid
Author
Saqib Rehan Ayyubi;Taha Selim Ustun;Yuan Miao
Author_Institution
College of Engineering and Science, Victoria University, Melbourne, Australia
fYear
2015
fDate
6/1/2015 12:00:00 AM
Firstpage
1772
Lastpage
1777
Abstract
Electricity needs are increasing with more ownership of air conditioning systems in houses. Air conditioning loads are a significant portion of the overall peak load on grids. In order to match generation and load in a more optimal way and reduce the strain on the grids, we need load information of houses in advance. The main problem is that the majority of houses are still not smart enough to notify the grids about future loads. Even the smart houses with such capability, the users need to keep track of it, which is a cumbersome manual task. Furthermore, the houses do not have the ability to sense the occupant and air conditioning requirements if the occupant is on the road. In this paper we have proposed a system to tackle these problems. The proposed system is a smart agent developed by combining existing technologies such as smart phones, GPS sensors, Internet over GSM networks, cloud services, and a novel application of image processing to combine interfaces of different components and technologies. Development of this smart agent requires low cost, less resources, and no modification to the existing systems. Lab results show that the prototype agent can easily sense and notify the upcoming air conditioning loads to the grid operator. A conservative estimate of the proposed systems´ effect on the grid shows that in peak hours by just keeping 1000 ACs away from the grid for a single minute may result in a significant reduction of grid load by 1 MW.
Keywords
"Air conditioning","Smart homes","Home appliances","Smart grids","Intelligent sensors","Temperature sensors"
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on
Type
conf
DOI
10.1109/ICIEA.2015.7334398
Filename
7334398
Link To Document