NDLI: A novel global MPP tracking scheme based on shading pattern identification using artificial neural networks for photovoltaic power generation during partial shaded condition

Content Provider	IET Digital Library
Author	Kota, Venkata Reddy Bhukya, Muralidhar Nayak
Abstract	Efficiency of the photovoltaic (PV) power generating system is affected during partial shaded condition (PSC). The power-voltage characteristic of PV system exhibits multiple peaks during PSC. It is the task of maximum power point tracking (MPPT) controller to track global maximum power point (GMPP). Conventional MPPT schemes stop at first peak and fail to accomplish GMPP during PSC. Metaheuristic algorithms developed to track GMPP are complex, costly and require much time to track GMPP. Hence, this study put forwards a novel GMPPT scheme for effective tracking based on shading pattern identification using artificial neural network (ANN). In this scheme, ANN is used to estimate the shading pattern on PV panels and a two-dimensional lookup table supplies the MPP voltage corresponding to the shading pattern. By maintaining this voltage across PV panel, maximum power is extracted. The proposed scheme is compared with the existing artificial bee colony and particle swarm optimisation algorithms under different shading configurations to verify their performance under PSC. It is observed that the proposed scheme extracts maximum power effectively under various partial shading conditions. The proposed scheme is implemented in field-programmable gate array (FPGA) controller and the experimental results prove effectiveness of the proposed scheme.
Starting Page	1647
Ending Page	1659
Page Count	13
ISSN	17521416
Volume Number	13
e-ISSN	17521424
Issue Number	Issue 10, Jul (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/13/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2018.5142
Journal	IET Renewable Power Generation
Publisher Date	2019-04-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Artificial Neural Network Control of Electric Power System Conventional MPPT Scheme Different Shading Configurations Effective Tracking Existing Artificial Bee Colony Existing Local Peaks Field Programmable Gate Array Global Maximum Power Point GMPP Logic Circuit Maximum Power Point Trackers Maximum Power Point Tracking Controller MPP Voltage Multiple Peaks Neural Computing Technique Neural Nets Novel Global MPP Tracking Scheme Novel GMPPT Scheme Optimisation Technique Partial Shaded Condition Partial Shading Condition Particle Swarm Optimisation Particle Swarm Optimisation Algorithm Pattern Identification Photovoltaic Power Generating System Photovoltaic Power Generation Photovoltaic Power System Power–voltage Characteristic PSC PV Panel PV System Shading Pattern Solar Cell And Array Solar Cell Array Solar Power Stations Table Lookup
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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