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Journals / Balkan Journal of Electrical and Computer Engineering / 2026 / Cilt: 14

Optimal Location Placement of EVFCS in Distribution Network Using Genetic Algorithm

Genetik Algoritma Kullanılarak Dağıtım Ağında EAHŞİ'nin Optimum Konum Yerleşimi

Endris Muhammed Hassen(MARMARA UNIVERSITY)0009-0002-5338-9892
Fikret Kaya(MARMARA UNIVERSITY)0009-0003-5832-2766
Onur Akar(MARMARA UNIVERSITY)0000-0001-9695-886X
Ümit Terzi(MARMARA UNIVERSITY)0000-0001-6739-7717
Pages
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Publication Date
2026-08-26
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results the proposed optimal controller outperforms best performance and efficient energy used.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent times, as the number of electrical vehicle (EV) became increased, many researches has been done on finding the optimal placement of Electrical Vehicle Charging Stations (EVCS).
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Key Findings & Data:EV research has become one of the most fascinating, interesting, intriguing and exciting field areas in transportation system due to its low CO2 emission, lower energy consumption and high efficiency.
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Conclusion & Impact:According to the results the proposed optimal controller outperforms best performance and efficient energy used.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Optimum lokasyon · dağıtım ağı · hızlı şarj istasyonu

Abstract

In recent times, as the number of electrical vehicle (EV) became increased, many researches has been done on finding the optimal placement of Electrical Vehicle Charging Stations (EVCS). EV research has become one of the most fascinating, interesting, intriguing and exciting field areas in transportation system due to its low CO2 emission, lower energy consumption and high efficiency. It also has lower maintenance costs compared to normal internal combustion engine vehicles. Inappropriate placement of EVCS lead to under-utilization, grid strain, traffic and safety concerns, limited accessibility, environmental and zoning issues. In this study, Genetic Algorithm (GA) based approach model for electrical distribution network are developed to find best placement of Electrical Vehicle Fast Charging Station (EVFCS). Model has been developed to optimize the location of EVFCS in the power distribution network. The distance from each proximity area to EVFCS is considered as objective function of problem formulation and constructed for the acquired model. In this research, the power loss cost of distribution network, fixed installation cost and the line cost of EVFCS are analyzed. The duration time for EVCS is determined and the optimal time is identified. The GA use crossover, mutation, and selection to distribute EVFCS in a way that would best place them in various proximity areas. According to the results the proposed optimal controller outperforms best performance and efficient energy used.

Özet

Son zamanlarda, elektrikli araç (EV) sayısı arttıkça, Elektrikli Araç Şarj İstasyonları'nın (EVCS) optimum yerleşimini bulmak için birçok araştırma yapılmıştır. EV araştırmaları, düşük CO2 emisyonu, daha düşük enerji tüketimi ve yüksek verimliliği nedeniyle ulaşım sistemindeki en büyüleyici, ilginç, merak uyandırıcı ve heyecan verici alan alanlarından biri haline gelmiştir. Ayrıca, normal içten yanmalı motorlu araçlara kıyasla daha düşük bakım maliyetlerine sahiptir. EVCS'nin uygunsuz yerleşimi, yetersiz kullanıma, şebeke zorlanmasına, trafik ve güvenlik endişelerine, sınırlı erişilebilirliğe, çevresel ve imar sorunlarına yol açar. Bu çalışmada, Elektrikli Araç Hızlı Şarj İstasyonu'nun (EVFCS) en iyi yerleşimini bulmak için elektrik dağıtım şebekesi için Genetik Algoritma (GA) tabanlı yaklaşım modeli geliştirilmiştir. Model, güç dağıtım şebekesinde EVFCS'nin yerini optimize etmek için geliştirilmiştir. Her yakınlık alanının EVFCS'ye olan uzaklığı, problem formülasyonunun nesnel fonksiyonu olarak kabul edilmiş ve edinilen model için oluşturulmuştur. Bu araştırmada, dağıtım şebekesinin güç kaybı maliyeti, sabit kurulum maliyeti ve EVFCS'nin hat maliyeti analiz edilmiştir. EVCS için süre belirlenir ve en uygun zaman tanımlanır. GA, EVFCS'yi çeşitli yakınlık alanlarına en iyi şekilde yerleştirecek şekilde dağıtmak için çaprazlama, mutasyon ve seçilim kullanır. Sonuçlara göre önerilen en uygun denetleyici en iyi performansı ve kullanılan verimli enerjiyi geride bırakmaktadır.

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Cite This Article

Hassen, E. M., Kaya, F., Akar, O., Terzi, Ü. (2026). Optimal Location Placement of EVFCS in Distribution Network Using Genetic Algorithm. Balkan Journal of Electrical and Computer Engineering, Cilt: 14. https://doi.org/10.17694/bajece.1706396

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