Conference proceeding
Distributive MPPT Approach Using ANFIS and PerturbObserve Techniques Under Uniform and Partial Shading Conditions
ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2017, v 668, pp 27-37
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
PV systems work under different weather conditions such as uniform and partial shading weather conditions. This causes inconsistent power in PV systems. This paper presents a reconfigurable interconnections approach that uses and compares between two powerful maximum power point tracking (MPPT) techniques of artificial neuro-fuzzy inference system [ANFIS front-end distributive MPPT (DMPPT)] technique and Perturb&Observe distributive MPPT technique. This approach is introduced in order to decrease the partial shading and mismatch effect caused by varying light falling on the PV arrays, which will lead to extract more power from the PV modules. The PV systems were configured as series-connected PV string that uses Perturb&Observe MPPT technique and as a PV series-connected system that uses ANFIS-MPPT technique. The proposed PV systems were tested under uniform and partial shading weather conditions. The results show that MPPT could be tracked accurately with the ANFIS-DMPPT for both cases of uniform irradiance and partial shaded irradiance conditions.
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Details
- Title
- Distributive MPPT Approach Using ANFIS and PerturbObserve Techniques Under Uniform and Partial Shading Conditions
- Creators
- Adedayo M. Farayola - University of JohannesburgAli N. Hasan - University of JohannesburgAhmed Ali - University of JohannesburgBhekisipho Twala - University of Johannesburg
- Contributors
- S S Dash (Editor)PCB Naidu (Editor)R Bayindir (Editor)S Das (Editor)
- Publication Details
- ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2017, v 668, pp 27-37
- Series
- Advances in Intelligent Systems and Computing
- Publisher
- Springer Nature
- Number of pages
- 11
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Engineering Leadership and Society/Engineering Technology
- Web of Science ID
- WOS:000550312800003
- Scopus ID
- 2-s2.0-85044426511
- Other Identifier
- 991022004638304721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Computer Science, Software Engineering
- Engineering, Electrical & Electronic
- Mathematics, Applied