Identification

Title

Assessing evidence for weather regimes governing solar power generation in Kuwait

Abstract

With electricity representing around 20% of the global energy demand, and increasing support for renewable sources of electricity, there is also an escalating need to improve solar forecasts to support power management. While considerable research has been directed to statistical methods to improve solar power forecasting, few have employed finite mixture distributions. A statistically-objective classification of the overall sky condition may lead to improved forecasts. Combining information from the synoptic driving conditions for daily variability with local processes controlling subdaily fluctuations could assist with forecast validation and enhancement where few observations are available. Gaussian mixture models provide a statistical learning approach to automatically identify prevalent sky conditions (clear, semi-cloudy, and cloudy) and explore associated weather patterns. Here a first stage in the development of such a model is presented: examining whether there is sufficient information in the large-scale environment to identify days with clear, semi-cloudy, or cloudy conditions. A three-component Gaussian distribution is developed that reproduces the observed multimodal peaks in sky clearness indices, and their temporal distribution. Posterior probabilities from the fitted mixture distributions are used to identify periods of clear, partially-cloudy, and cloudy skies. Composites of low-level (850 hPa) humidity and winds for each of the mixture components reveal three patterns associated with the typical synoptic conditions governing the sky clarity, and hence, potential solar power.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7xd14wb

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2019-11-20T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact