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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Heuristic Techniques for Reducing Energy Consumption of Household

Authors:

Sarah Daragemh, Anniken T. Karlsen, Ibrahim Hameed

Published in:

 

 

(2022). ECMS 2022, 36th Proceedings
Edited by: Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat, European Council for Modelling and Simulation.

 

DOI: http://doi.org/10.7148/2022

ISSN: 2522-2422 (ONLINE)

ISSN: 2522-2414 (PRINT)

ISSN: 2522-2430 (CD-ROM)

 

ISBN: 978-3-937436-77-7
ISBN: 978-3-937436-76-0(CD)

 

Communications of the ECMS , Volume 36, Issue 1, June 2022,

Ålesund, Norway May 30th - June 3rd, 2022

 

Citation format:

Sarah Daragemh, Anniken T. Karlsen, Ibrahim Hameed (2022). Heuristic Techniques for Reducing Energy Consumption of Household, ECMS 2022 Proceedings Edited By: Ibrahim A. Hameed, Agus Hasan, Saleh Abdel-Afou Alaliyat, European Council for Modeling and Simulation.

doi:10.7148/2022-0254

DOI:

https://doi.org/10.7148/2022-0254

Abstract:

Efficient energy demand management plays an essential role in smart grid, sustainable and smart cities applications and efforts to reduce CO2 emissions.  In this paper, we propose a framework for describing the household daily energy consumption and how it can be used to help residential households to perform appliance rescheduling to reduce energy consumption and hence reducing their energy bills while keeping resident’s comfort. In this paper, heuristic optimization techniques such as genetic algorithm (GA) and particle swarm optimization (PSO) are used for solving the load scheduling problem. Due to its ability to deal with computational complex scenarios in less computational time using less and less computational resources, Heuristic optimization techniques are used. In the proposed model, dynamic pricing is adopted where the objective is to minimize the overall cost of electricity consumption and payments by scheduling different devices in a way that fulfil each individual’s constraints and preferences. Here, MATLAB was used as the simulation platform. Simulation results showed that GA and PSO can optimize energy consumption and bills and at the same time fulfils needs and preferences of each individual customer. @font-face {font-family:SimSun; panose-1:2 1 6 0 3 1 1 1 1 1; mso-font-alt:宋体; mso-font-charset:134; mso-generic-font-family:auto; mso-font-pitch:variable; mso-font-signature:3 680460288 22 0 262145 0;}@font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face {font-family:"\@SimSun"; panose-1:2 1 6 0 3 1 1 1 1 1; mso-font-charset:134; mso-generic-font-family:auto; mso-font-pitch:variable; mso-font-signature:3 680460288 22 0 262145 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-unhide:no; mso-style-qformat:yes; mso-style-parent:""; margin:0cm; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman",serif; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:EN-US;}.MsoChpDefault {mso-style-type:export-only; mso-default-props:yes; font-size:10.0pt; mso-ansi-font-size:10.0pt; mso-bidi-font-size:10.0pt; mso-fareast-font-family:SimSun; mso-ansi-language:EN-US; mso-fareast-language:EN-US;}div.WordSection1 {page:WordSection1;}.

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