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ABC algorithm based optimal sizing and placement of DGs in distribution networks considering multiple objectives

تستند خوارزمية ABC إلى الحجم الأمثل ووضع DGS في شبكات التوزيع مع مراعاة أهداف متعددة
Authors: Essam A. Al‐Ammar; Kiran Farzana; Asad Waqar; Muhammad Aamir; Saifullah; Azhar Ul-Haq; Muhammad Zahid; +1 Authors

ABC algorithm based optimal sizing and placement of DGs in distribution networks considering multiple objectives

Abstract

Ces dernières années, en raison de l'augmentation de la demande de charge, les réseaux de distribution ont reçu une attention considérable pour être optimisés. Il est important de placer de manière optimale les générateurs distribués (DG) dans les réseaux de distribution afin de minimiser les pertes de puissance et les chutes de tension. Cependant, les DG encourent certains coûts d'investissement et d'exploitation, et leur placement n'est viable que si ces coûts surmontent les pertes d'énergie. Par conséquent, l'article actuel étudie la taille et le placement optimaux des DG dans les réseaux de distribution avec un nouveau concept pour minimiser simultanément le coût total de l'énergie ainsi que la perte de puissance totale et la chute de tension moyenne. L'algorithme de colonie d'abeilles artificielles (ABC) est proposé pour résoudre le problème multi-objectif considéré. Les performances de l'algorithme ABC proposé sont testées avec des algorithmes standard. L'analyse du flux de charge Newton Raphson (NRLF) est réalisée sur les réseaux radiaux IEEE 33 et 69-bus et sur la grille de référence CIGRE moyenne tension (MT). Deux cas de test ont été formés et étudiés. Les résultats prouvent que l'algorithme ABC proposé surpasse largement les autres algorithmes.

En los últimos años, debido al aumento de la demanda de carga, las redes de distribución han recibido una atención sustancial para ser optimizadas. Es importante colocar de manera óptima los generadores distribuidos (DGS) en las redes de distribución para minimizar las pérdidas de energía y las caídas de voltaje. Sin embargo, las DG incurren en ciertos costos de inversión y operación, y su colocación solo es viable si estos costos superan las pérdidas de energía. Por lo tanto, el documento actual investiga el tamaño y la colocación óptimos de las DG en las redes de distribución con un concepto novedoso para minimizar simultáneamente el costo total de energía junto con la pérdida total de potencia y la caída de voltaje promedio. Se propone el algoritmo de colonia artificial de abejas (ABC) para resolver el problema multiobjetivo considerado. El rendimiento del algoritmo ABC propuesto se prueba con algoritmos estándar. El análisis del flujo de carga de Newton Raphson (NRLF) se realiza en redes radiales IEEE 33 y 69-bus y en la red de referencia de media tensión (MT) CIGRE. Se han formado e investigado dos casos de prueba. Los resultados demuestran que el algoritmo ABC propuesto supera en su mayoría a otros algoritmos.

In recent years, due to increase in load demand, distribution networks have got substantial attention to get optimized. It is significant to optimally place the distributed generators (DGs) in distribution networks to minimize power losses and voltage drops. However, the DGs incur certain investment and operational costs, and their placement is only viable if these costs overcome energy losses. Therefore, current paper investigates the optimal sizing and placement of DGs in distribution networks with a novel concept to simultaneously minimize total energy cost along with total power loss and average voltage drop. Artificial bee colony (ABC) algorithm is proposed to solve the considered multi-objective problem. The performance of the proposed ABC algorithm is tested with standard algorithms. Newton Raphson load flow (NRLF) analysis is conducted on IEEE 33 and 69-bus radial networks and on CIGRE medium voltage (MV) benchmark grid. Two test cases have been formed and investigated. The results prove that proposed ABC algorithm mostly outperforms other algorithms.

في السنوات الأخيرة، وبسبب الزيادة في الطلب على الأحمال، حظيت شبكات التوزيع باهتمام كبير لتحسينها. من المهم وضع المولدات الموزعة (DGS) على النحو الأمثل في شبكات التوزيع لتقليل فقد الطاقة وانخفاض الجهد. ومع ذلك، تتكبد DGS بعض التكاليف الاستثمارية والتشغيلية، ولا يكون وضعها قابلاً للتطبيق إلا إذا تغلبت هذه التكاليف على خسائر الطاقة. لذلك، تبحث الورقة الحالية في الحجم الأمثل لمولدات الديزل ووضعها في شبكات التوزيع مع مفهوم جديد لتقليل تكلفة الطاقة الإجمالية في وقت واحد إلى جانب فقدان الطاقة الكلي وانخفاض متوسط الجهد. تُقترح خوارزمية مستعمرة النحل الاصطناعي (ABC) لحل المشكلة متعددة الأهداف المعتبرة. يتم اختبار أداء خوارزمية ABC المقترحة باستخدام خوارزميات قياسية. يتم إجراء تحليل تدفق حمل نيوتن رافسون (NRLF) على الشبكات الشعاعية IEEE 33 و 69 - bus وعلى شبكة قياس الجهد المتوسط CIGRE (MV). تم تشكيل حالتين اختباريتين والتحقيق فيهما. تثبت النتائج أن خوارزمية ABC المقترحة تتفوق في الغالب على الخوارزميات الأخرى.

Keywords

Optimization, Distribution Systems, Power flow, Distributed Power Generation, Geometry, Distributed Generation, Quantum mechanics, Electric power system, Visual arts, Engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Line loss, Demand Response in Smart Grids, Electrical and Electronic Engineering, Grid, Sizing, Artificial bee colony algorithm, Optimal Power Flow, Geography, Newton Raphson Load flow (NRLF) analysis, Physics, Mathematical optimization, Voltage, Power (physics), Engineering (General). Civil engineering (General), Computer science, Integration of Distributed Generation in Power Systems, Algorithm, Distributed generation (DG), Control and Systems Engineering, Optimal sizing and placement of DGs, Electrical engineering, Physical Sciences, Control and Synchronization in Microgrid Systems, TA1-2040, Benchmark (surveying), Voltage drop, Mathematics, Art, Geodesy

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
81
Top 1%
Top 10%
Top 1%
gold