Analysis of weather parameters on electrical energy consumption of a residential building

Siddhartha ., Maya Yeswanth Pai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper aims to collect and encapsulate data regarding the modelling efforts made to predict the energy consumption of residential buildings using a prominent statistical method, to help in prediction the subsequent conservation of energy (electricity) consumed in the residential building sector. Among the various statistical methods available linear regression analysis is considered a good option in case of availability of historic building use data via smart metering techniques as it provides reasonably accurate results with a simple approach. In this study, linear and multiple regression analysis were conducted on data collected from a residential building so as to obtain the best model for prediction purposes. The average temperature parameter emerged as the most important predictor variable and relative humidity as the least having low or negative correlations. Also, the study of the cumulative effect of all the independent parameters on the building use variables proved that it is best to incorporate the effects of all the independent variables to obtain accurate results.

Original languageEnglish
Title of host publication2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679890
DOIs
Publication statusPublished - 02-2019
Event2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019 - Gangtok, Sikkim, India
Duration: 25-02-201828-02-2018

Publication series

Name2019 2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019

Conference

Conference2nd International Conference on Advanced Computational and Communication Paradigms, ICACCP 2019
Country/TerritoryIndia
CityGangtok, Sikkim
Period25-02-1828-02-18

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Artificial Intelligence
  • Computer Networks and Communications
  • Instrumentation

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