Abdullah M. Noman, Hamed Khan, H. A. Sher, Sulaiman Z. Almutairi, Mohammed H. Alqahtani, Ali S. Aljumah
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引用次数: 2
Abstract
This article proposes a hybrid scheme of maximum power point tracking (MPPT) based on artificial neural network (ANN) and ripple current correlation (RCC). ANN model is established using the data generated through RCC MPPT. Scaled conjugate gradient ANN is applied to gauge the performance improvement. The proposed scheme is validated through simulations. For this, the proposed system is applied to three different environmental scenarios which are standard testing condition of a PV module, under variable irradiance condition, and variable temperature condition. It is established that the proposed system is well capable of tracking the maximum power point under various test conditions.
期刊介绍:
International Journal of Photoenergy is a peer-reviewed, open access journal that publishes original research articles as well as review articles in all areas of photoenergy. The journal consolidates research activities in photochemistry and solar energy utilization into a single and unique forum for discussing and sharing knowledge.
The journal covers the following topics and applications:
- Photocatalysis
- Photostability and Toxicity of Drugs and UV-Photoprotection
- Solar Energy
- Artificial Light Harvesting Systems
- Photomedicine
- Photo Nanosystems
- Nano Tools for Solar Energy and Photochemistry
- Solar Chemistry
- Photochromism
- Organic Light-Emitting Diodes
- PV Systems
- Nano Structured Solar Cells