JOURNAL ARTICLE

Smart Home Energy Management Using Artificial Intelligence

Chetna RadkeSharvari PakmodeRomit MendheAyushi PunwatkarYash SattabhayyaManoj Maurya

Year: 2023 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Electricity is an essential component of any developing nation. Power generating plants of all kinds are being put in place to meet the rising demand; Even though there is an ever-increasing gap between the supply and demand as a result of the depletion of natural resources, which in turn leads to an increase in the demand for power, the only way to close the gap is to make the most of the energy resources that are available, reduce the amount of electrical energy that is wasted, both technical and non-technical, and keep the demand down during peak times. This project proposes a method for resolving the problem of load management during peak hours for domestic loads, with the goal of narrowing the gap between demand and supply so that both the consumer and the supplier benefit simultaneously. In our proposed project we are going to use AI technology which takes the decision like human brain. We are using the solar power as a renewable energy source to reduce the consumption from grid and to reduce energy bill. From sample of operating conditions AI will be trained and it will be tested for autonomous operation after training. The purpose of using this technology is to optimally utilize solar resource.

Keywords:
Computer science Energy management Energy (signal processing) Mathematics

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Cited By
0.17
FWCI (Field Weighted Citation Impact)
0
Refs
0.41
Citation Normalized Percentile
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Citation History

Topics

IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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