An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems
المؤلفون المشاركون
Hantash, Neda
Khatib, Tamer
Khammash, Maher
المصدر
Applied Computational Intelligence and Soft Computing
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-03
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
In this paper, an improved particle swarm optimization method (PSO) is proposed to optimally size and place a DG unit in an electrical power system so as to improve voltage profile and reduce active power losses in the system.
An IEEE 34 distribution bus system is used as a case study for this research.
A new equation of weight inertia is proposed so as to improve the performance of the PSO conventional algorithm.
This development is done by controlling the inertia weight which affects the updating velocity of particles in the algorithm.
Matlab codes are developed for the adapted electrical power system and the improved PSO algorithm.
Results show that the proposed PSO algorithm successfully finds the optimal size and location of the desired DG unit with a capacity of 1.6722 MW at bus number 10.
This makes the voltage magnitude of the selected bus equal to 1.0055 pu and improves the status of the electrical power system in general.
The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s.
In addition to that, the proposed PSO algorithm reduces the active power losses by 31.6%.
This means that the average elapsed time is reduced by 21% by using the proposed PSO algorithm as compared to the conventional PSO algorithm that is based on the liner inertia weight equation.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hantash, Neda& Khatib, Tamer& Khammash, Maher. 2020. An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems. Applied Computational Intelligence and Soft Computing،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1126037
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hantash, Neda…[et al.]. An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems. Applied Computational Intelligence and Soft Computing No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1126037
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hantash, Neda& Khatib, Tamer& Khammash, Maher. An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems. Applied Computational Intelligence and Soft Computing. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1126037
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1126037
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر