Zobrazeno 1 - 10
of 11
pro vyhledávání: '"C. Balakrishna Moorthy"'
Publikováno v:
International Journal of Smart Grid and Clean Energy. :662-669
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9a6b5ed4fa55c509d6be3d3ce29ce43
https://doi.org/10.12720/sgce.8.6.662-669
https://doi.org/10.12720/sgce.8.6.662-669
Publikováno v:
TENCON
Renewable energy systems like wind, solar, ocean and tidal are prone to consistent weather changes which can be abrupt and quick in nature. Extracting maximum power from generators that are powered from renewable sources can be demanding. Maximum Pow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::609360957ccba62a32251ab14979fbd8
https://doi.org/10.1109/tencon.2019.8929414
https://doi.org/10.1109/tencon.2019.8929414
Publikováno v:
Wind Engineering. 38:633-642
In the present work, genetic algorithm has been used to resolve the placement of wind turbines in a wind park giving maximum power and efficiency with minimum number of turbines. Unlike past approaches where each plot was subdivided into smaller squa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79f98a840836210f3e72c8f785015e31
https://doi.org/10.1260/0309-524x.38.6.633
https://doi.org/10.1260/0309-524x.38.6.633
Autor:
C. Balakrishna Moorthy, M. K. Deshmukh
Publikováno v:
International Journal of Sustainable Energy. 34:396-405
In the present study, particle swarm optimisation has been used to resolve the placement of wind turbines in a wind park giving maximum power and efficiency with minimum number of turbines. Unlike past approaches where each plot was subdivided into s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba63c897e396315c6437ab48dc2f074b
https://doi.org/10.1080/14786451.2013.860140
https://doi.org/10.1080/14786451.2013.860140
Autor:
C. Balakrishna Moorthy, M. K. Deshmukh
Publikováno v:
2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES).
In this paper, using hourly average wind data recorded for a period of one year is used to estimate wind power potential in a region of Goa, India. The wind power potential is estimated using Weibull probability density function. In this paper, the W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad9a3d7f77003855d1bb7af8a50a1371
https://doi.org/10.1109/pedes.2016.7914337
https://doi.org/10.1109/pedes.2016.7914337
Publikováno v:
Indian Journal of Science and Technology. 8
In this paper, the wind power is predicted using artificial intelligence techniques. The wind speed data as input and wind power data as output, measured at ten minutes interval for a period of eleven months are used for the study. The artificial int
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eea0993f576ad540b3badb2fc0a229f5
https://doi.org/10.17485/ijst/2015/v8i25/87891
https://doi.org/10.17485/ijst/2015/v8i25/87891
Akademický článek
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Autor:
C. Balakrishna Moorthy, M. K. Deshmukh
Publikováno v:
Energy Procedia. :141-148
Wind resource assessment is the key step in windfarm deployment at pre-investment stage. In a wind farm, it is often the case that wind climate data is measured at one place and it is required to estimate wind resource potential at any other point in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46425911b0d4941b9666e22ef176561f
Akademický článek
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Akademický článek
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