Computational Intelligence in Photovoltaic Systems
Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant produc...
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| Format: | Online |
| Jezik: | angleščina |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Teme: | |
| Online dostop: | 42694 |
| Oznake: |
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| _version_ | 1869526606926577664 |
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| author | Ogliari , Emanuele Leva, Sonia |
| author_browse | Leva, Sonia Ogliari , Emanuele |
| author_facet | Ogliari , Emanuele Leva, Sonia |
| author_sort | Ogliari , Emanuele |
| collection | Directory of Open Access Books |
| description | Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, etc.) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue “Computational Intelligence in Photovoltaic Systems” is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, etc.); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators. |
| format | Online |
| id | doab-20.500.12854ir-43703 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-437032024-04-11T15:10:28Z Computational Intelligence in Photovoltaic Systems Ogliari , Emanuele Leva, Sonia TA1-2040 T1-995 artificial neural network online diagnosis genetic algorithm renewable energy unit commitment photovoltaic panel power forecasting metaheuristic monitoring system embedded systems firefly algorithm tracking system MPPT algorithm integrated storage day-ahead forecast solar radiation prototype model artificial neural networks parameter extraction thermal image thermal model solar cell PV cell temperature evolutionary algorithms uncertainty battery harmony search meta-heuristic algorithm single-diode photovoltaic model symbiotic organisms search photovoltaics tilt angle smart photovoltaic system blind orientation photovoltaic particle swarm optimization analytical methods computational intelligence statistical errors ensemble methods solar photovoltaic electrical parameters demand response metaheuristic algorithm thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, etc.) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue “Computational Intelligence in Photovoltaic Systems” is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, etc.); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators. 2021-02-11T10:19:04Z 2021-02-11T10:19:04Z 2019-12-09 16:10:12 2019 book 42694 9783039210992 9783039210985 https://directory.doabooks.org/handle/20.500.12854/43703 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/1541 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03921-099-2 10.3390/books978-3-03921-099-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039210992 9783039210985 180 open access |
| spellingShingle | TA1-2040 T1-995 artificial neural network online diagnosis genetic algorithm renewable energy unit commitment photovoltaic panel power forecasting metaheuristic monitoring system embedded systems firefly algorithm tracking system MPPT algorithm integrated storage day-ahead forecast solar radiation prototype model artificial neural networks parameter extraction thermal image thermal model solar cell PV cell temperature evolutionary algorithms uncertainty battery harmony search meta-heuristic algorithm single-diode photovoltaic model symbiotic organisms search photovoltaics tilt angle smart photovoltaic system blind orientation photovoltaic particle swarm optimization analytical methods computational intelligence statistical errors ensemble methods solar photovoltaic electrical parameters demand response metaheuristic algorithm thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Ogliari , Emanuele Leva, Sonia Computational Intelligence in Photovoltaic Systems |
| title | Computational Intelligence in Photovoltaic Systems |
| title_full | Computational Intelligence in Photovoltaic Systems |
| title_fullStr | Computational Intelligence in Photovoltaic Systems |
| title_full_unstemmed | Computational Intelligence in Photovoltaic Systems |
| title_short | Computational Intelligence in Photovoltaic Systems |
| title_sort | computational intelligence in photovoltaic systems |
| topic | TA1-2040 T1-995 artificial neural network online diagnosis genetic algorithm renewable energy unit commitment photovoltaic panel power forecasting metaheuristic monitoring system embedded systems firefly algorithm tracking system MPPT algorithm integrated storage day-ahead forecast solar radiation prototype model artificial neural networks parameter extraction thermal image thermal model solar cell PV cell temperature evolutionary algorithms uncertainty battery harmony search meta-heuristic algorithm single-diode photovoltaic model symbiotic organisms search photovoltaics tilt angle smart photovoltaic system blind orientation photovoltaic particle swarm optimization analytical methods computational intelligence statistical errors ensemble methods solar photovoltaic electrical parameters demand response metaheuristic algorithm thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | TA1-2040 T1-995 artificial neural network online diagnosis genetic algorithm renewable energy unit commitment photovoltaic panel power forecasting metaheuristic monitoring system embedded systems firefly algorithm tracking system MPPT algorithm integrated storage day-ahead forecast solar radiation prototype model artificial neural networks parameter extraction thermal image thermal model solar cell PV cell temperature evolutionary algorithms uncertainty battery harmony search meta-heuristic algorithm single-diode photovoltaic model symbiotic organisms search photovoltaics tilt angle smart photovoltaic system blind orientation photovoltaic particle swarm optimization analytical methods computational intelligence statistical errors ensemble methods solar photovoltaic electrical parameters demand response metaheuristic algorithm thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | 42694 |
| work_keys_str_mv | AT ogliariemanuele computationalintelligenceinphotovoltaicsystems AT levasonia computationalintelligenceinphotovoltaicsystems |