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Publication Type : Journal Article
Publisher : IOS Press
Source : Journal of Intelligent & Fuzzy Systems (IOS Press), vol. 40, no. 1, pp. 403-413, 2021.
Campus : Chennai
School : School of Engineering
Center : Amrita Innovation & Research
Department : Electronics and Communication
Verified : Yes
Year : 2021
Abstract : Under demand response enabled demand-side management, the home energy management (HEM) schemes schedule appliances for balancing both energy and demand within a residence. This scheme enables the user to achieve either a minimum electricity bill (EB) or maximum comfort. There is always the added burden on a HEM scheme to obtain the least possible EB with comfort. However, if a time window that contains comfortable time slots of the day for an appliance operation, is identified, and if the cost-effective schedule-pattern gets generated from these windows autonomously, then the burden can be reduced. Therefore, this paper proposes a two-level method that can assist the HEM scheme by generating a cost-effective schedule-pattern for scheduling home appliances. The first level uses a classifier to identify the comfortable time window from past ON and OFF events. The second level uses pattern generation algorithms to generate a cost-effective schedule-pattern from the identified window. The generated cost-effective schedule-pattern is applied to a HEM scheme as input to demonstrate the proposed two-level approach. The simulation results exhibit that the proposed approach helps the HEM scheme to schedule home appliances cost-effectively with a satisfactory user-comfort between 90% and 100%.
Cite this Research Publication : M. Firdouse Ali Khan, Ganesh Kumar Chellamani, and Premanand Venkatesh Chandramani, “Naïve Bayes Classifier Enabled Home Energy Management Scheme for Cost-effective End-user Comfort”, Journal of Intelligent & Fuzzy Systems (IOS Press), vol. 40, no. 1, pp. 403-413, 2021.