A Study of Deep Neural Network Controller-Based Power Quality Improvement of Hybrid PVWind Systems by Using Smart Inverter
المؤلفون المشاركون
Ab-BelKhair, Adel
Rahebi, Javad
Abdulhamed Mohamed Nureddin, Abdulbaset
المصدر
International Journal of Photoenergy
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-22، 22ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-12-17
دولة النشر
مصر
عدد الصفحات
22
التخصصات الرئيسية
الملخص EN
Presently, climate change and global warming are the most uncontrolled global challenges due to the extensive fossil fuel usage for power generation and transportation.
Nowadays, most of the developed countries are concentrating on developing alternative resources; consequently, they did huge investments in research and development.
In general, alternative energy resources including hydropower, solar power, and wind energy are not harmful to nature.
Today, solar power and wind power are very popular alternative energy sources due to their enormous availability in nature.
In this paper, the photovoltaic cell and wind energy systems are investigated under various weather conditions.
Based on the findings, we developed an advanced intelligent controller system that tracks the maximum power point.
The MPPT controller is a must for the renewable energy sources due to unpredictable weather conditions.
The main objective of this paper is to propose a new algorithm that is based on deep neural network (DNN) and maximum power point tracking (MPPT), which was simulated in a MATLAB environment for photovoltaic (PV) and wind-based power generation systems.
The development of an advanced DNN controller that improves the power quality and reduces THD value for the microgrid integration of hybrid PV/wind energy system was performed.
The MATLAB simulation tool has been used to develop the proposed system and tested its performance in different operating situations.
Finally, we analyzed the simulation results applying the IEEE 1547 standard.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ab-BelKhair, Adel& Rahebi, Javad& Abdulhamed Mohamed Nureddin, Abdulbaset. 2020. A Study of Deep Neural Network Controller-Based Power Quality Improvement of Hybrid PVWind Systems by Using Smart Inverter. International Journal of Photoenergy،Vol. 2020, no. 2020, pp.1-22.
https://search.emarefa.net/detail/BIM-1173287
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ab-BelKhair, Adel…[et al.]. A Study of Deep Neural Network Controller-Based Power Quality Improvement of Hybrid PVWind Systems by Using Smart Inverter. International Journal of Photoenergy No. 2020 (2020), pp.1-22.
https://search.emarefa.net/detail/BIM-1173287
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ab-BelKhair, Adel& Rahebi, Javad& Abdulhamed Mohamed Nureddin, Abdulbaset. A Study of Deep Neural Network Controller-Based Power Quality Improvement of Hybrid PVWind Systems by Using Smart Inverter. International Journal of Photoenergy. 2020. Vol. 2020, no. 2020, pp.1-22.
https://search.emarefa.net/detail/BIM-1173287
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1173287
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