A time series model for Kt with application to global synthetic weather generation

V. A. Graham; K. G.T. Hollands; T. E. Unny

doi:10.1016/0038-092X(88)90075-8

A time series model for K_t with application to global synthetic weather generation

V. A. Graham, K. G.T. Hollands, T. E. Unny

Mechanical & Aerospace Engineering

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

120 Scopus citations

Abstract

This article describes a general mathematical procedure for generating synthetic daily solar irradiation values. The procedure should be useful for simulating solar energy systems, requiring only the 12 monthly means (K_t), as input. The procedure is based on a time series analysis of the daily K_t values, described in the article. It incorporates the well-known probability distribution function for K_t, by using a transformed variable, rather than K_t, as the fundamental random quantity.

Original language	English (US)
Pages (from-to)	83-92
Number of pages	10
Journal	Solar Energy
Volume	40
Issue number	2
DOIs	https://doi.org/10.1016/0038-092X(88)90075-8
State	Published - 1988

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
Materials Science(all)

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title = "A time series model for Kt with application to global synthetic weather generation",

abstract = "This article describes a general mathematical procedure for generating synthetic daily solar irradiation values. The procedure should be useful for simulating solar energy systems, requiring only the 12 monthly means (Kt), as input. The procedure is based on a time series analysis of the daily Kt values, described in the article. It incorporates the well-known probability distribution function for Kt, by using a transformed variable, rather than Kt, as the fundamental random quantity.",

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AB - This article describes a general mathematical procedure for generating synthetic daily solar irradiation values. The procedure should be useful for simulating solar energy systems, requiring only the 12 monthly means (Kt), as input. The procedure is based on a time series analysis of the daily Kt values, described in the article. It incorporates the well-known probability distribution function for Kt, by using a transformed variable, rather than Kt, as the fundamental random quantity.

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