Preprocessing uncertain photovoltaic data

Miao Fan; Vijay Vittal; Gerald T. Heydt; Raja Ayyanar

doi:10.1109/TSTE.2013.2287992

Preprocessing uncertain photovoltaic data

Miao Fan, Vijay Vittal, Gerald T. Heydt, Raja Ayyanar

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

This letter suggests a method to manage the uncertainty of photovoltaic (PV) data by removing the periodic effect of the annual position of the sun in the sky. The least squares method is applied to determine the low-frequency (annual) periodic component which is predictable in the system operation. This method can be applied to estimate the probabilistic characteristics of PV generation at various locations on the earth with differing insolation due to changing solar position.

Original language	English (US)
Article number	6677516
Pages (from-to)	351-352
Number of pages	2
Journal	IEEE Transactions on Sustainable Energy
Volume	5
Issue number	1
DOIs	https://doi.org/10.1109/TSTE.2013.2287992
State	Published - Jan 2014

Keywords

Least squares method
Photovoltaic (PV) generation
Probability density function (pdf)
Renewable energy
Uncertainty

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment

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10.1109/TSTE.2013.2287992

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abstract = "This letter suggests a method to manage the uncertainty of photovoltaic (PV) data by removing the periodic effect of the annual position of the sun in the sky. The least squares method is applied to determine the low-frequency (annual) periodic component which is predictable in the system operation. This method can be applied to estimate the probabilistic characteristics of PV generation at various locations on the earth with differing insolation due to changing solar position.",

keywords = "Least squares method, Photovoltaic (PV) generation, Probability density function (pdf), Renewable energy, Uncertainty",

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AU - Ayyanar, Raja

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AB - This letter suggests a method to manage the uncertainty of photovoltaic (PV) data by removing the periodic effect of the annual position of the sun in the sky. The least squares method is applied to determine the low-frequency (annual) periodic component which is predictable in the system operation. This method can be applied to estimate the probabilistic characteristics of PV generation at various locations on the earth with differing insolation due to changing solar position.

KW - Least squares method

KW - Photovoltaic (PV) generation

KW - Probability density function (pdf)

KW - Renewable energy

KW - Uncertainty

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Preprocessing uncertain photovoltaic data

Abstract

Keywords

ASJC Scopus subject areas

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