A Study of Deep Neural Network Controller-Based Power Quality Improvement of Hybrid PVWind Systems by Using Smart Inverter

Joint Authors

Ab-BelKhair, Adel
Rahebi, Javad
Abdulhamed Mohamed Nureddin, Abdulbaset

Source

International Journal of Photoenergy

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-22, 22 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-17

Country of Publication

Egypt

No. of Pages

22

Main Subjects

Chemistry

Abstract 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.

American Psychological Association (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

Modern Language Association (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

American Medical Association (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

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1173287