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Journals / Black Sea Journal of Engineering and Science / 2026 / Cilt: 9 Sayı: 4

Gliding Snake Algorithm for the Optimal Placement and Sizing of Renewable Energy–Based Distributed Generation and Energy Storage Systems in Distribution Networks

Dağıtım Şebekelerinde Yenilenebilir Enerji Kaynaklı Dağıtık Üretim ve Enerji Depolama Sistemlerinin Optimal Yerleşimi ve Boyutlandırılması İçin Süzülen Yılan Algoritması

Cenk Andiç(İSTANBUL TEKNİK ÜNİVERSİTESİ)0000-0003-1123-899X
Pages
2022–2038
Publication Date
2026-07-15
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AI Summary & Key Takeaways

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

The obtained results show that the proposed GSO algorithm is effective and that the coordinated integration of renewable energy sources with energy storage systems provides significant advantages in reducing power losses and improving the voltage profile in distribution networks.

📌 3 Key Takeaways

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Objective & Hypothesis:This study addresses the problem of optimal placement and sizing of renewable energy–based wind turbines (WT) and photovoltaic (PV) systems in a radial distribution network.
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Key Findings & Data:The study consists of three different scenarios, all tested on the IEEE 33-bus radial distribution network.
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Conclusion & Impact:The obtained results show that the proposed GSO algorithm is effective and that the coordinated integration of renewable energy sources with energy storage systems provides significant advantages in reducing power losses and improving the voltage profile in distribution networks.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Dağıtım şebekeleri · Dağıtık üretim · Yenilenebilir enerji kaynakları

Abstract

This study addresses the problem of optimal placement and sizing of renewable energy–based wind turbines (WT) and photovoltaic (PV) systems in a radial distribution network. The integration of renewable energy sources into the distribution network aims to reduce network power losses, improve the voltage profile, and minimize the voltage deviation index. To solve this optimization problem, a novel approach called the Gliding Snake Optimization (GSO) algorithm is proposed in this study. The study consists of three different scenarios, all tested on the IEEE 33-bus radial distribution network. In Scenario 1, the placement of one and two distributed generation units in the distribution network is carried out using the proposed GSO algorithm, considering Type-1 (producing only active power) and Type-3 (producing both active and reactive power) operating modes. In Scenario 2, in order to minimize the annual energy loss of the distribution network, the optimal placement and sizing of PV and WT units are determined using the proposed GSO algorithm by considering seasonal load values as well as seasonal generation profiles of wind turbines and photovoltaic systems. The results obtained in Scenario 1 and Scenario 2 are compared with the genetic algorithm (GA) and particle swarm optimization (PSO), which are widely used in the literature, and the proposed GSO method demonstrates superior performance. In Scenario 3, an energy storage system is integrated into the distribution network together with renewable energy-based distributed generation units, and the improvements in network operating performance are analyzed comparatively. The obtained results show that the proposed GSO algorithm is effective and that the coordinated integration of renewable energy sources with energy storage systems provides significant advantages in reducing power losses and improving the voltage profile in distribution networks.

Özet

Bu çalışma, yenilenebilir enerji kaynaklı rüzgâr türbini (RT) ve fotovoltaik (PV) sistemlerin radyal dağıtım şebekesine optimal yerleşimi ve boyutlandırılması problemini ele almaktadır. Yenilenebilir enerji kaynaklarının dağıtım şebekesine entegrasyonu ile şebeke güç kayıplarının azaltılması, gerilim profilinin iyileştirilmesi ve gerilim değişim indeksinin azaltılması amaçlanmıştır. Bu optimizasyon probleminin çözümü için bu çalışmada yeni bir yaklaşım olan süzülen yılan optimizasyon (SYO) algoritması önerilmiştir. Çalışma üç farklı senaryodan oluşmakta olup tüm senaryolar IEEE 33 baralı radyal dağıtım şebekesi üzerinde test edilmiştir. Senaryo 1’de dağıtım şebekesine bir ve iki adet dağıtık üretim biriminin yerleşimi, Tip-1 (sadece aktif güç üreten) ve Tip-3 (hem aktif hem de reaktif güç üretebilen) çalışma modları dikkate alınarak önerilen SYO algoritması ile gerçekleştirilmiştir. Senaryo 2’de ise dağıtım şebekesinin yıllık enerji kaybını minimize etmek amacıyla mevsimsel yük değerleri ile rüzgâr türbini ve fotovoltaik sistemlerin mevsimsel üretim değerleri dikkate alınarak PV ve RT birimlerinin optimal yerleşimi ve boyutlandırılması önerilen SYO algoritması ile belirlenmiştir. Senaryo 1 ve Senaryo 2’de elde edilen sonuçlar literatürde yaygın olarak kullanılan genetik algoritma (GA) ve parçacık sürü optimizasyonu (PSO) algoritmaları ile karşılaştırılmış ve önerilen SYO yönteminin daha üstün performans gösterdiği ortaya konulmuştur. Senaryo 3’te ise dağıtım şebekesine yenilenebilir enerji kaynaklı dağıtık üretim birimleri ile birlikte enerji depolama sistemi entegre edilerek şebeke işletme performansındaki iyileşmeler karşılaştırmalı olarak analiz edilmiştir. Elde edilen sonuçlar, önerilen SYO algoritmasının etkinliği ile birlikte yenilenebilir enerji kaynaklarının enerji depolama sistemleriyle koordineli entegrasyonunun dağıtım şebekelerinde güç kayıplarını azaltma ve gerilim profilini iyileştirme açısından önemli avantajlar sağladığını göstermektedir.

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Cite This Article

Andiç, C. (2026). Gliding Snake Algorithm for the Optimal Placement and Sizing of Renewable Energy–Based Distributed Generation and Energy Storage Systems in Distribution Networks. Black Sea Journal of Engineering and Science, Cilt: 9 Sayı: 4, 2022–2038. https://doi.org/10.34248/bsengineering.1914505

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