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A Shadow Histogram Algorithm to Determine Clear Sky Indices for Sky Imager Short Term Advective Solar forecasting.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	A Shadow Histogram Algorithm to Determine Clear Sky Indices for Sky Imager Short Term Advective Solar forecasting./
Author:	Sheth, Nishank Mihir.
Description:	1 online resource (34 pages)
Notes:	Source: Masters Abstracts International, Volume: 56-03.
Subject:	Environmental science. -
Online resource:	click for full text (PQDT)
ISBN:	9781369697377

A Shadow Histogram Algorithm to Determine Clear Sky Indices for Sky Imager Short Term Advective Solar forecasting.
Sheth, Nishank Mihir.

A Shadow Histogram Algorithm to Determine Clear Sky Indices for Sky Imager Short Term Advective Solar forecasting. - 1 online resource (34 pages)

Source: Masters Abstracts International, Volume: 56-03.

Thesis (M.S.)--University of California, San Diego, 2017.

Includes bibliographical references

Sky imagers are used for short-term forecasting of solar irradiance, which can be used to counter ramp events caused by larger clouds or extensive changes in cloud cover. Sky imager forecast algorithms usually detect cloud classes in the image. However, the assignment of cloud optical depth or surface Global Horizontal Irradiance (GHI) to cloud classes remains a challenge. One method to connect GHI to cloud classes involves the use of a histogram of recently measured clear sky indices to assign a clear sky index/GHI to each cloud class. While this method improves upon choosing static GHI values for each cloud class, this paper presents a modification which improves the histogram method. Considering data from a significantly shorter time period than the existing method emphasizes more recent cloud conditions. Individual histograms for each cloud class self-consistent with modeled cloud coverage from the sky imager are used to analyze the data instead of a single histogram. The new algorithm gave a 39% reduction in root mean square error against the existing algorithm when tested over a month.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369697377Subjects--Topical Terms:

1179128
Environmental science.
Index Terms--Genre/Form:

554714
Electronic books.

A Shadow Histogram Algorithm to Determine Clear Sky Indices for Sky Imager Short Term Advective Solar forecasting.
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100 1 $a Sheth, Nishank Mihir. $3 1185596
245 1 2 $a A Shadow Histogram Algorithm to Determine Clear Sky Indices for Sky Imager Short Term Advective Solar forecasting.
264 0 $c 2017
300 $a 1 online resource (34 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 56-03.
500 $a Adviser: Jan Kleissl.
502 $a Thesis (M.S.)--University of California, San Diego, 2017.
504 $a Includes bibliographical references
520 $a Sky imagers are used for short-term forecasting of solar irradiance, which can be used to counter ramp events caused by larger clouds or extensive changes in cloud cover. Sky imager forecast algorithms usually detect cloud classes in the image. However, the assignment of cloud optical depth or surface Global Horizontal Irradiance (GHI) to cloud classes remains a challenge. One method to connect GHI to cloud classes involves the use of a histogram of recently measured clear sky indices to assign a clear sky index/GHI to each cloud class. While this method improves upon choosing static GHI values for each cloud class, this paper presents a modification which improves the histogram method. Considering data from a significantly shorter time period than the existing method emphasizes more recent cloud conditions. Individual histograms for each cloud class self-consistent with modeled cloud coverage from the sky imager are used to analyze the data instead of a single histogram. The new algorithm gave a 39% reduction in root mean square error against the existing algorithm when tested over a month.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Environmental science. $3 1179128
650 4 $a Atmospheric sciences. $3 1179392
650 4 $a Mechanical engineering. $3 557493
655 7 $a Electronic books. $2 local $3 554714
690 $a 0768
690 $a 0725
690 $a 0548
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, San Diego. $b Engineering Sciences (Mechanical Engineering). $3 845441
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10243453 $z click for full text (PQDT)