Malaysia residential load profile management based on time of use tariff using ant colony optimization algorithm

In Malaysia, electricity generation has been rapidly increasing, in line with consumers’ electricity demand. For those reasons, the government has introduced Demand Side Management (DSM) as a programme to promote balanced energy use between energy generation and demand. However, such an energy manag...

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Bibliographic Details
Main Authors: Dahlan, Nofri Yenita, Sulaima, Mohamad Fani, Wan Hanapi, Wan Noor Azzyati, Noor Din, Muhamad Muhtazam
Format: Article
Language:English
Published: Universiti Malaysia Terengganu 2022
Online Access:http://eprints.utem.edu.my/id/eprint/26585/2/18-JSSM-VOLUME-17-NUMBER-3-MARCH-2022.PDF
http://eprints.utem.edu.my/id/eprint/26585/
https://jssm.umt.edu.my/wp-content/uploads/sites/51/2022/05/Article-18-JSSM-Volume-17-Number-3-March-2022.pdf
http://doi.org/10.46754/jssm.2022.03.018
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Summary:In Malaysia, electricity generation has been rapidly increasing, in line with consumers’ electricity demand. For those reasons, the government has introduced Demand Side Management (DSM) as a programme to promote balanced energy use between energy generation and demand. However, such an energy management policy is usually geared towards industrial and commercial consumers’ but rarely towards residential consumers. The significant incentive demand response programme under the DSM, such as Time of Use tariff (TOU), was not implemented for residential consumers due to many reasons. These include the insufficient TOU tariff designs for residential use and the lack of awareness among consumers on how to manage their load profiles so that they couldn’t enjoy concurrent reductions on their electricity bill. Thus, this study, aims to investigate what the best model of TOU time segmentation was for the residential consumers in Peninsular Malaysia. It also engaged in significant analysis to determine the optimal Load Profile Management (LPM) strategies for consumers that best reflected the residential TOU tariff. To determine the LPM this study made use of optimisation algorithms such as Ant Colony Optimisation (ACO); and an analysis comparing the performance of different load shift weightages that reduce the total cost of electricity are also considered and presented. A command average residential load profile has been tested as a real case study. The results of this study would help electricity providers to design a good TOU tariff policy and consumers would be able to benefit from the practice of LPM.