M. F. Sulaima
Universiti Teknologi Mara (UiTM)

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ETOU electricity tariff for manufacturing load shifting strategy using ACO algorithm M. F. Sulaima; N. Y. Dahlan; M. H. Isa; M. N. Othman; Z. M. Yasin; H. A. Kasdirin
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (490.139 KB) | DOI: 10.11591/eei.v8i1.1438

Abstract

This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program
ETOU electricity tariff for manufacturing load shifting strategy using ACO algorithm M. F. Sulaima; N. Y. Dahlan; M. H. Isa; M. N. Othman; Z. M. Yasin; H. A. Kasdirin
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (489.895 KB) | DOI: 10.11591/eei.v8i1.1438

Abstract

This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program.
ETOU electricity tariff for manufacturing load shifting strategy using ACO algorithm M. F. Sulaima; N. Y. Dahlan; M. H. Isa; M. N. Othman; Z. M. Yasin; H. A. Kasdirin
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (489.895 KB) | DOI: 10.11591/eei.v8i1.1438

Abstract

This paper presents load shifting strategy for cost reduction on manufacturing electricity demand side, by which a real test load profile had been used to prove the concept. Superior bio-inspired algorithm, Ant Colony Optimization (ACO) had been implemented to optimize the upright load profile of load shifting strategy in the Malaysia Enhance Time of Use (ETOU) tariff condition. Subsequently, significant simulation results of operation profit gain through 24 hours electricity consumption had been analyzed properly. The proposed method had shown reduction of approximately 6% of the electricity cost at peak and mid peak zones, when 20%, 40%, 60%, 80% and 100% load shifting weightages were applied to the identified 10% controlled loads consequently. It is hoped that the finding of this study can help poise the manufacturers to switch to ETOU tariff as well as support the national Demand Side Management (DSM) program.