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Turkish Journal of Electrical Engineering and Computer Sciences

Author ORCID Identifier

ASAD ALI: 0000-0002-8639-1553

HAZLIE MOKHLIS: 0000-0002-1166-1934

NURULAFIQAH MANSOR: 0000-0003-2148-5775

HUSSAIN SHAREEF: 0000-0001-7708-6904

HASMAINI MOHAMAD: 0000-0003-2633-0350

MUNIR MUHAMMAD: 0000-0001-7356-1923

Abstract

Power distribution systems play a crucial role in transmitting electrical power from generation sources to end users. During transmission, significant power losses occur in the form of heat as the current flowing along the lines/cables has resistance. To minimize power losses, distribution network reconfiguration (DNR) has been widely adopted. This paper proposes optimal DNR based on metaheuristic techniques with discrete mutation feature targeting active power loss reduction, which subsequently lowers carbon emissions and operational costs. Through the discrete mutation feature, computational time to find optimal solution has been reduced significantly with fewer iterations compared to conventional mutation techniques. The proposed DNR is tested using IEEE 33-Bus, 69-Bus Test System, and the Real Iran 59-Bus Distribution Network. Test results show a significant reduction of computational time of 77.78% for the 33-bus system, 66.67% for the 69-bus system, and 69.23% for the 59-bus system. Furthermore, power loss reductions of 31.15%, 55.725%, and 26.3% are achieved, respectively, compared to initial configurations. These reductions correspond to annual cost savings of $33,181.13, $65,900.31, and $24,759.45 for the three test systems. Moreover, CO2 emission reductions of 398,173.54 tonnes, 51,248,396.7 tonnes, and 296,753.76 tonnes have been achieved for the respective systems.

DOI

10.55730/1300-0632.4177

Keywords

Carbon emissions, power distribution systems, voltage profile improvement, power loss minimization

First Page

328

Last Page

341

Publisher

The Scientific and Technological Research Council of Türkiye (TÜBİTAK)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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