Conference proceeding
Use of MPPT Techniques to Reduce the Energy Pay-Back Time in PV Systems
International Renewable Energy Congress (Online), pp 1-6
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Photovoltaic (PV) energy is a free energy used as an alternative to fossil fuel energy. However, PV system without maximum power point tracking (MPPT) produces a low, unstable power and with a long energy payback time (EPBT). This paper presents an innovative artificial neuro-fuzzy inference system (ANFIS) MPPT technique that could extract maximum power from a complete PV system and with a lessened energy payback time (EPBT). To confirm the effectiveness of the ANFIS algorithm, its results was compared with the results of PV system using Perturb&Observe (P&O) technique, non-MPPT technique, combination of artificial neural network and support vector machine as ANN-SVM technique and using Pretoria city weather data as case studies. Results show that ANFIS-MPPT yielded the best result and with the lowest EPBT.
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Details
- Title
- Use of MPPT Techniques to Reduce the Energy Pay-Back Time in PV Systems
- Creators
- Adedayo M. Farayola - University of JohannesburgAli N. Hasan - University of JohannesburgAhmed Ali - University of Johannesburg
- Publication Details
- International Renewable Energy Congress (Online), pp 1-6
- Series
- International Renewable Energy Congress
- Publisher
- IEEE
- Number of pages
- 6
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Engineering Leadership and Society/Engineering Technology
- Web of Science ID
- WOS:000434869100111
- Scopus ID
- 2-s2.0-85048484682
- Other Identifier
- 991022004202004721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Energy & Fuels
- Engineering, Electrical & Electronic
- Green & Sustainable Science & Technology