Analysis of grid performance with diversified distributed resources and storage integration: A bilevel approach with network-oriented PSO

Name: Analysis of grid performance with diversified distributed resources and storage integration: A bilevel approach with network-oriented PSO
Author: Poyrazoglu, Gokturk, El Sayed, Ahmad

İsim	Analysis of grid performance with diversified distributed resources and storage integration: A bilevel approach with network-oriented PSO
Yazar	Poyrazoglu, Gokturk, El Sayed, Ahmad
Basım Tarihi:	2024-05-08
Basım Yeri	- MDPI
Konu	Sitting, Sizing, Resistivity, Pso, Distribution system, Der, Connectivity
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1996-1073
Kayıt Numarası	ea39200c-da81-4508-a5bb-c4bc1685c306
Lokasyon	Electrical & Electronics Engineering
Tarih	2024-05-08
Örnek Metin	The growing deployment of distributed resources significantly affects the distribution grid performance in most countries. The optimal sizing and placement of these resources have become increasingly crucial to mitigating grid issues and reducing costs. Particle Swarm Optimization (PSO) is widely used to address such problems but faces computational inefficiency due to its numerical convergence behavior. This limits its effectiveness, especially for power system problems, because the numerical distance between two nodes in power systems might be different from the actual electrical distance. In this paper, a scalable bilevel optimization problem with two novel algorithms enhances PSO's computational efficiency. While the resistivity-driven algorithm strategically targets low-resistivity regions and guides PSO toward areas with lower losses, the connectivity-driven algorithm aligns solution spaces with the grid's physical topology. It prioritizes actual physical neighbors during the search to prevent local optima traps. The tests of the algorithms on the IEEE 33-bus and the 69-bus and Norwegian networks show significant reductions in power losses (up to 74% for PV, wind, and storage) and improved voltage stability (a 21% reduction in mean voltage deviation index) with respect to the results of classical PSO. The proposed network-oriented PSO outperforms classical PSO by achieving a 2.84% reduction in the average fitness value for the IEEE 69-bus case with PV, wind, and storage deployment. The Norwegian case study affirms the effectiveness of the proposed approach in real-world applications through significant improvements in loss reduction and voltage stability.
DOI	10.3390/en17102270
Cilt	17

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Analysis of grid performance with diversified distributed resources and storage integration: A bilevel approach with network-oriented PSO

Yazar Poyrazoglu, Gokturk, El Sayed, Ahmad

Basım Tarihi 2024-05-08

Basım Yeri - MDPI

Konu Sitting, Sizing, Resistivity, Pso, Distribution system, Der, Connectivity

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1996-1073

Kayıt Numarası ea39200c-da81-4508-a5bb-c4bc1685c306

Lokasyon Electrical & Electronics Engineering

Tarih 2024-05-08

Örnek Metin The growing deployment of distributed resources significantly affects the distribution grid performance in most countries. The optimal sizing and placement of these resources have become increasingly crucial to mitigating grid issues and reducing costs. Particle Swarm Optimization (PSO) is widely used to address such problems but faces computational inefficiency due to its numerical convergence behavior. This limits its effectiveness, especially for power system problems, because the numerical distance between two nodes in power systems might be different from the actual electrical distance. In this paper, a scalable bilevel optimization problem with two novel algorithms enhances PSO's computational efficiency. While the resistivity-driven algorithm strategically targets low-resistivity regions and guides PSO toward areas with lower losses, the connectivity-driven algorithm aligns solution spaces with the grid's physical topology. It prioritizes actual physical neighbors during the search to prevent local optima traps. The tests of the algorithms on the IEEE 33-bus and the 69-bus and Norwegian networks show significant reductions in power losses (up to 74% for PV, wind, and storage) and improved voltage stability (a 21% reduction in mean voltage deviation index) with respect to the results of classical PSO. The proposed network-oriented PSO outperforms classical PSO by achieving a 2.84% reduction in the average fitness value for the IEEE 69-bus case with PV, wind, and storage deployment. The Norwegian case study affirms the effectiveness of the proposed approach in real-world applications through significant improvements in loss reduction and voltage stability.

DOI 10.3390/en17102270

Cilt 17