ELECTRICA
RESEARCH ARTICLE

Analysis of Electrical Distribution Network Voltage Configuration with Mixed Integer Linear Programming Algorithm and Genetic Algorithm I Terms of Energy Cost

1.

Department of Electrical-Energy, Akseki Vocational School, Alanya Alaaddin Keykubat University, Antalya, Turkey

2.

Department of Electrical - Electronic Engineering, Gazi University, Faculty of Engineering, Ankara, Turkey

3.

Department of Electrical-Energy, Vocational School of Technical Sciences, Akdeniz University, Antalya, Turkey

ELECTRICA 2020; 20: 124-132
DOI: 10.5152/electrica.2020.20014
Read: 52 Downloads: 33 Published: 15 June 2020

Since natural and social resources are not evenly distributed over the earth's surface, socioeconomic developments differ in time and space. Although the most important causes of inequality are natural or geographical reasons, the lack of energy supply-demand balance specific to the region causes inequality to increase. Undoubtedly, eliminating the supply-demand imbalance as a result of the increase in energy demand by costing energy cheaply will play a major role in reducing these differences.  To meet the energy demand, the existing electricity grid may need to be expanded or partially or completely replaced. The aim of the studies to design a new electricity network or to expand an existing network; to meet the needs of consumers by providing energy distribution with minimum cost and maximum quality. In this study; energy costs generated by re-planning in a network that distributes electricity at different voltage levels to meet the increasing energy needs were analysed.  To obtain the optimum network design; a minimization function was established by determining the required transformer powers and their numbers considering the physical and electrical conditions. The generated function was analysed by using a mixed-integer programming algorithm and genetic algorithm in MATLAB.

Cite this article as: Akbulut L, Tezcan SS, Coşgun A. Analysis of Electrical Distribution Network Voltage Configuration with Mixed Integer Linear Programming Algorithm and Genetic Algorithm I Terms of Energy Cost. Electrica 2020; 20(2): 124-132.

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EISSN 2619-9831