Publication Type : Conference Paper
Publisher : Joint International Conference on Communication, Computing and Power Technologies ICCCPT-2015 and Artificial Intelligence and Evolutionary Computations in Engineering Systems
Source : Joint International Conference on Communication, Computing and Power Technologies ICCCPT-2015 and Artificial Intelligence and Evolutionary Computations in Engineering Systems ICAIECES-2015, 2015.
Url : https://link.springer.com/chapter/10.1007/978-81-322-2656-7_97
Campus : Chennai
School : School of Engineering
Center : Amrita Innovation & Research
Department : Electronics and Communication
Verified : Yes
Year : 2015
Abstract : Dynamic demand response (DR) and demand side management (DSM) are the important functions that allow the customer to reduce the peak load demand. This results in the reduced energy consumption cost and better user experience. In DSM, the customers can make informed decisions regarding their energy consumption, and it helps to reshape their load profile. In this chapter, we proposed an integrated solution to predict the electricity demand and made a load shift in a locality at a given day. The system presented in this chapter expands the DR to residential loads by scheduling and controlling the appliance. The electricity demand in the home is forecasted by a decision support system, which helps the user to save energy by recommending optimal run time schedule for appliances, given user constraints and TOU pricing from the utility. The schedule is communicated to the appliance and executed by the appliance control interface
Cite this Research Publication : Ganesh Kumar C, Januja Josephine S, and Premanand V Chandramani, “Mining Based Device Control for Home Automation”, Joint International Conference on Communication, Computing and Power Technologies ICCCPT-2015 and Artificial Intelligence and Evolutionary Computations in Engineering Systems ICAIECES-2015, 2015.