Home energy management for home appliances using knapsack model

Md Noh, Nor Aishah and Mohd Ridzuan, Fatin Nur Liyana (2025) Home energy management for home appliances using knapsack model. In: Mathematics and Statistics Undergraduate Research Proceedings 2025. Universiti Teknologi MARA, Negeri Sembilan, pp. 395-408. ISBN 9786299595328

Abstract

In recent months, increasing electricity bills have led to the need for consumers to manage their energy consumption efficiently. This study used the knapsack model for home energy management for home appliances to solve this problem. The aims are to adapt an optimization approach for daily appliance usage using the knapsack model for home energy management of home appliances and to compare the cost of electricity bills per day before and after using the knapsack model. The model was developed using IBM CPLEX software where the knapsack model will prioritize essential appliances for continuous use while nonessential devices are scheduled based on the cost budget limit. The results indicate that the knapsack model reduced daily electricity costs by RM0.22–RM0.66. This corresponds to monthly savings of RM6.60–RM19.80, representing approximately 4–12% compared to the actual daily costs. In conclusion, the model not only ensures optimal energy consumption but also provides consumers with a sustainable and cost-effective solution for managing household electricity usage.

Metadata

Item Type: Book Section
Creators:
Creators
Email / ID Num.
Md Noh, Nor Aishah
UNSPECIFIED
Mohd Ridzuan, Fatin Nur Liyana
UNSPECIFIED
Subjects: H Social Sciences > HD Industries. Land use. Labor > Technological innovations
Q Science > QA Mathematics > Mathematical statistics. Probabilities > Data processing
Q Science > QA Mathematics > Real-time programming
Divisions: Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus
Page Range: pp. 395-408
Keywords: Energy consumption, appliances, knapsack model, IBM CPLEX
Date: 2025
URI: https://ir.uitm.edu.my/id/eprint/138683
Edit Item
Edit Item

Download

[thumbnail of 138683.pdf] Text
138683.pdf

Download (3MB)

ID Number

138683

Indexing

Statistic

Statistic details