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Home Energy Management System Based on Genetic Algorithm for Load Scheduling: A Case Study Based on Real Life Consumption Data

  • This paper proposes a home energy management system able to achieve optimized load scheduling for the operation of appliances within a given household. The system, based on the genetic algorithm, provides recommendations for the user to improve the way the energy needs of the home are handled. These recommendations not only take into account the dynamic pricing of electricity, but also the optimization for solar energy usage as well as user comfort. Historical data regarding the times at which the appliances have been used is leveraged through a statistical method to integrate the user’s preference into the algorithm. Based on real life appliance consumption data collected from a household in Morocco, three scenarios are established to assess the performance of the proposed system with each scenario having different parameters. Running the scenarios on the developed MATLAB script shows a cost saving of up to 63.48% as compared to a base scenario for a specific day. These results demonstrate that significant cost saving can be achievedThis paper proposes a home energy management system able to achieve optimized load scheduling for the operation of appliances within a given household. The system, based on the genetic algorithm, provides recommendations for the user to improve the way the energy needs of the home are handled. These recommendations not only take into account the dynamic pricing of electricity, but also the optimization for solar energy usage as well as user comfort. Historical data regarding the times at which the appliances have been used is leveraged through a statistical method to integrate the user’s preference into the algorithm. Based on real life appliance consumption data collected from a household in Morocco, three scenarios are established to assess the performance of the proposed system with each scenario having different parameters. Running the scenarios on the developed MATLAB script shows a cost saving of up to 63.48% as compared to a base scenario for a specific day. These results demonstrate that significant cost saving can be achieved while maintaining user comfort. The addition of supplementary shiftable loads (i.e., an electric vehicle) to the household as well as the limitations of such home energy management systems are discussed. The main contribution of this paper is the real data and including the user comfort as a metric in in the home energy management scheme.show moreshow less

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Metadaten
Author:Reda El Makroum, Ahmed KhallaayounORCiD, Rachid Lghoul, Kedar MehtaORCiD, Wilfried Zörner
Language:English
Document Type:Article
Year of first Publication:2023
published in (English):Energies
Publisher:MDPI
Place of publication:Basel
ISSN:1996-1073
Volume:16
Issue:6
Pages:18
Article Number:2698
Review:peer-review
Open Access:ja
Version:published
Tag:genetic algorithm; home energy management; load scheduling; user comfort
URN:urn:nbn:de:bvb:573-32284
Related Identifier:https://doi.org/10.3390/en16062698
Faculties / Institutes / Organizations:Fakultät Maschinenbau
Institut für neue Energie-Systeme (InES)
Licence (German):License Logo Creative Commons BY 4.0
Release Date:2023/03/15