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Elektrikli araç şarj ağı tasarımı için çok amaçlı bir karma tamsayılı doğrusal programlama modeli

A multi objective mixed-integer linear programming model for the electric vehicle charging network design

Meltem Uzuner(BAŞKENT ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ)0000-0002-0497-1934
Orhan Dengiz(ANKARA ÜNİVERSİTESİ)0000-0002-0814-2463
İmdat Kara(BAŞKENT ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ)0000-0002-2730-5993
Esra Karasakal(ORTA DOĞU TEKNİK ÜNİVERSİTESİ)0000-0002-2806-3308
Berna Dengiz(BAŞKENT ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ)0000-0001-7586-5648
Sayfa
1875–1886
Yayın Tarihi
2025-08-21
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AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Problemlerin çözümü için, çok amaçlı eniyileme yöntemlerinden Öncelikli Eniyileme Yöntemi (ÖEY) ve Artırılmış Epsilon Kısıt Yöntemi 2 (AEKY2) kullanılarak elde edilen Pareto Cephesi (PC), karar vericiye amaç fonksiyonlarının farklı düzeyleri için ödünleşim bilgisini sunmaktadır.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Bu çalışmada, elektrikli araçların (EA) taleplerini mümkün olduğunca yakın bölgelerden karşılayacak ve elektrik araç şarj istasyonu kurulum ve işletim maliyetini enküçükleyecek şekilde, şarj istasyonlarının hangi dönemde, nerede ve hangi kapasitede kurulacağının belirlenmesi için yeni bir çok amaçlı karma tamsayılı doğrusal programlama modeli geliştirilmiştir.
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Temel Bulgular & Veri:Farklı araç marka ve modellerinin, EA’nın ve istasyondaki şarj cihazının dönüştürücü ve güç kapasitelerinin, farklı tiplerdeki şarj hizmeti taleplerinin dikkate alındığı bu modelde, talepler gerçekçi bir biçimde ele alınmıştır.
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Sonuç & Katkı:Problemlerin çözümü için, çok amaçlı eniyileme yöntemlerinden Öncelikli Eniyileme Yöntemi (ÖEY) ve Artırılmış Epsilon Kısıt Yöntemi 2 (AEKY2) kullanılarak elde edilen Pareto Cephesi (PC), karar vericiye amaç fonksiyonlarının farklı düzeyleri için ödünleşim bilgisini sunmaktadır.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Elektrikli araç · şarj istasyonu · yer seçim problemi

Özet

Bu çalışmada, elektrikli araçların (EA) taleplerini mümkün olduğunca yakın bölgelerden karşılayacak ve elektrik araç şarj istasyonu kurulum ve işletim maliyetini enküçükleyecek şekilde, şarj istasyonlarının hangi dönemde, nerede ve hangi kapasitede kurulacağının belirlenmesi için yeni bir çok amaçlı karma tamsayılı doğrusal programlama modeli geliştirilmiştir. Model ile mevcut istasyonlardaki şarj altyapısının iyileştirilmesi de göz önüne alınarak EA’ların artan ihtiyaçlarını karşılayacak şekilde şarj ağı tasarımı elde edilmektedir. Farklı araç marka ve modellerinin, EA’nın ve istasyondaki şarj cihazının dönüştürücü ve güç kapasitelerinin, farklı tiplerdeki şarj hizmeti taleplerinin dikkate alındığı bu modelde, talepler gerçekçi bir biçimde ele alınmıştır. Önerilen modelin genel performansı, hesaplamalı deneysel analiz ile rassal olarak üretilen 15 farklı test problemi üzerinde incelenmiştir. Problemlerin çözümü için, çok amaçlı eniyileme yöntemlerinden Öncelikli Eniyileme Yöntemi (ÖEY) ve Artırılmış Epsilon Kısıt Yöntemi 2 (AEKY2) kullanılarak elde edilen Pareto Cephesi (PC), karar vericiye amaç fonksiyonlarının farklı düzeyleri için ödünleşim bilgisini sunmaktadır.

Abstract

In this study, a new mixed integer linear programming model has been developed to determine when, where, and at what capacity the charging stations will be installed, in a way that would satisfy the demand of electric vehicles (EV) from the nearby areas and minimize the cost of electric vehicle charging station installation and operation. Considering the need of charging infrastructure improvement, a methodology for adopting charging network design to satisfy the growing demands of EV drivers has been proposed. Demands are handled realistically in the model, by taking into consideration different vehicle brands and models, battery and power capacities of the EV and the charger in the station, and different types of charging service demands from drivers. The overall performance of the proposed model is examined on 15 test problems randomly generated by computational experiments. For the solution of the problems, Pareto Front (PF) was obtained by using multi-objective optimization methods -Lexicographic Optimization Method and AUGMECON2- providing the decision maker with trade-off information for different levels of objective functions.

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Bu Makaleye Atıf Yap

Uzuner, M., Dengiz, O., Kara, İ., Karasakal, E., Dengiz, B. (2025). Elektrikli araç şarj ağı tasarımı için çok amaçlı bir karma tamsayılı doğrusal programlama modeli. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 40 Sayı: 3, 1875–1886. https://doi.org/10.17341/gazimmfd.1214878

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