Zagazig University Digital Repository
Home
Thesis & Publications
All Contents
Publications
Thesis
Graduation Projects
Research Area
Research Area Reports
Search by Research Area
Universities Thesis
ACADEMIC Links
ACADEMIC RESEARCH
Zagazig University Authors
Africa Research Statistics
Google Scholar
Research Gate
Researcher ID
CrossRef
Parameters identification of PV triple-diode model using improved generalized normal distribution algorithm
Faculty
Computer Science
Year:
2021
Type of Publication:
ZU Hosted
Pages:
995
Authors:
Staff Zu Site
Abstract In Staff Site
Journal:
Mathematics Multidisciplinary Digital Publishing Institute
Volume:
9
Keywords :
Parameters identification , , triple-diode model using improved
Abstract:
To simulate the behaviors of photovoltaic (PV) systems properly, the best values of the uncertain parameters of the PV models must be identified. Therefore, this paper proposes a novel optimization framework for estimating the parameters of the triple-diode model (TDM) of PV units with different technologies. The proposed methodology is based on the generalized normal distribution optimization (GNDO) with two novel strategies: (i) a premature convergence method (PCM), and (ii) a ranking-based updating method (RUM) to accelerate the convergence by utilizing each individual in the population as much as possible. This improved version of GNDO is called ranking-based generalized normal distribution optimization (RGNDO). RGNDO is experimentally investigated on three commercial PV modules (Kyocera KC200GT, Ultra 85-P and STP 6-120/36) and a solar unit (RTC Si solar cell France), and its extracted parameters are validated based on the measured dataset points extracted at generalized operating conditions. It can be reported here that the best scores of the objective function are equal to 0.750839 mA, 28.212810 mA, 2.417084 mA, and 13.798273 mA for RTC cell, KC200GT, Ultra 85-P, and STP 6-120/36; respectively. Additionally, the principal performance of this methodology is evaluated under various statistical tests and for convergence speed, and is compared with a number of the well-known recent state-of-the-art algorithms. RGNDO is shown to outperform the other algorithms in terms of all the statistical metrics as well as convergence speed. Finally, the performance of the RGNDO is validated in various operating conditions under varied temperatures and sun irradiance levels. View Full-Text
Author Related Publications
Department Related Publications
Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini Environmental Economic Dispatching Based on Artificial Networks", لايوجد, 1900
More
Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini An Efficient Second Order Fast Load Flow Method in Rectangular Coordinates", لايوجد, 1900
More
Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini An Efficient Reduced Order Controller for Inter - Connected Power Systems", لايوجد, 1900
More
Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini An Efficient Method for Alleviating Line Overloads and Voltage Violations by Corrective Active and Reactive Rescheduling", لايوجد, 1900
More
Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini Alleviation of Post Outaged Overloads by Line Switching", لايوجد, 1900
More
جامعة المنصورة
جامعة الاسكندرية
جامعة القاهرة
جامعة سوهاج
جامعة الفيوم
جامعة بنها
جامعة دمياط
جامعة بورسعيد
جامعة حلوان
جامعة السويس
شراقوة
جامعة المنيا
جامعة دمنهور
جامعة المنوفية
جامعة أسوان
جامعة جنوب الوادى
جامعة قناة السويس
جامعة عين شمس
جامعة أسيوط
جامعة كفر الشيخ
جامعة السادات
جامعة طنطا
جامعة بنى سويف