Title: Performance analysis of precise energy consumption algorithm for smart home using hybrid renewable energy
Authors: Dinesh Kumar Anguraj; C. Sathya; C. Vinothini; M. Jayanthi; J. Vakula Rani
Addresses: Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India ' Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India ' Department of Computer Science and Engineering, Dr. N.G.P. Institute of Technology, Coimbatore, Tamil Nadu, India ' Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India ' Department of MCA, CMR Institute of Technology, Bengaluru, Karnataka, India
Abstract: Energy demand is increased day by day, so there is a need for energy management, and it plays a vital part in the 21st century. At present, non-renewable energy is utilised most of the time. The people are not aware of the wastage of energy when their home appliances turned on the whole day. So, hybrid renewable energy is an alternate source for supplying continuous power for their smart home in the future. The collected renewable energy is utilised for the smart home usages. To minimise power consumption and to predict energy consumption precisely is a stimulating task in the future. This work proposes an innovative precise energy consumption algorithm (PECA) that is used to calculate the smart home power consumption accurately. PECA utilises smart plug, smart gateway, and mobile app administration platform to build and deploy a deep learning model. The smart plug and smart gateway combined into the complete distributed sensor network is to analyse, improve, and expand the energy consumption efficiently. Artificial intelligence is used to predict the energy usage data, optimise resource consumption, reduce the cost and maximise renewable energy usage.
Keywords: renewable energy; precise energy consumption algorithm; PECA; smart home; smart plug; smart gateway; deep learning; artificial intelligence.
International Journal of Powertrains, 2023 Vol.12 No.1, pp.1 - 14
Received: 09 Nov 2020
Accepted: 01 Feb 2021
Published online: 20 Mar 2023 *