Development of Consumer Preference based Demand Response Model for Home Energy Management
M. Krishna Paramathma1, D. Devaraj2
1M. Krishna Paramathma, Department of Electrical and Electronics Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2D. Devaraj, Department of Electrical and Electronics Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 29 November 2019 | Revised Manuscript received on 18 December 2019 | Manuscript Published on 31 December 2019 | PP: 387-390 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D10861284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1086.1284S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Demand response has become an effective method for energy saving and to reduce the energy cost. By adjusting the residential loads, it reacts quickly for the mismatches of supply and demand. In this paper, the Internet of Things (IoT) based Demand Response (Load scheduling method) methodology is proposed to mitigate the energy waste and tariff. Two different alarm provisions are made at the consumer side to indicate the normal and demand modes operated by the supplier. The consumer is provided with a controller that read the market signal and answers with consumer preferences. Whenever demand mode arises, the consumer is completely free to change the load setting; also the developed system will propose the load pattern. The demand mode will be given during peak hour and the tariff will be high at that time and normal mode will consist of the minimum tariff. The consumer may control their load through cloud-MQTT by giving a specific command or from the MQTT dashboard android app. Based on the tariff, the consumption profile could be reduced.
Keywords: Cloud Mqtt, IoT, Demand Response.
Scope of the Article: Recent Trends & Developments in Computer Networks