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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chamola, Vinay | - |
dc.date.accessioned | 2023-03-17T06:51:34Z | - |
dc.date.available | 2023-03-17T06:51:34Z | - |
dc.date.issued | 2014 | - |
dc.identifier.uri | https://ieeexplore.ieee.org/abstract/document/7024821 | - |
dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9806 | - |
dc.description.abstract | This paper presents a methodology for dimensioning the photo-voltaic (PV) and battery requirements of stand-alone, solar-powered cellular base stations. In contrast to existing methodologies that use intuitive methods or are based on Typical Meteorological Year (TMY) data, this paper proposes the use of series-of-worst-months data for dimensioning the base station. The proposed approach has the advantages of higher accuracy as well as being computationally more efficient. The proposed methodology has been verified using real meteorological data for a number of geographical locations. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | EEE | en_US |
dc.subject | Batteries | en_US |
dc.subject | Base stations | en_US |
dc.subject | Power demand | en_US |
dc.subject | Optimization | en_US |
dc.subject | Solar energy | en_US |
dc.subject | Photovoltaic systems | en_US |
dc.subject | Data models | en_US |
dc.title | Dimensioning stand-alone cellular base station using series-of-worst-months meteorological data | en_US |
dc.type | Article | en_US |
Appears in Collections: | Department of Electrical and Electronics Engineering |
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