From local wind energy resource to national wind power production

Wolf-Gerrit Früh; Wolf-Gerrit Früh

doi:10.3934/energy.2015.1.101

AIMS Energy

2015, Volume 3, Issue 1: 101-120. doi: 10.3934/energy.2015.1.101

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Research article Special Issues

From local wind energy resource to national wind power production

Wolf-Gerrit Früh ^,

Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, Scotland, UK

Received: 06 November 2014 Accepted: 28 January 2015 Published: 26 February 2015

Wind power is one of the most established renewable power resources yet it is also one of the most volatile resources. This poses a key challenge for successfully integrating wind power at a large scale into the power grid. Here we present an analysis of the time scales associated with wind power from hourly to seasonal fluctuations and how combining spatially distributed wind power sources helps to reduce its volatility. The analysis, based on observed wind speeds, is then generalised in a simple statistical model to develop a tool which can estimate the power output profile from a particular consortium of wind power sources. As the estimator only uses the local, or the mean national, wind resource and the mean distance between the sites to estimate the joint power output profile, it can be used by developers to estimate the reliability of their joint power output and to form the most effective consortium.
- wind energy resource,
- wind power production,
- regional aggregation,
- Virtual Power Plant
Citation: Wolf-Gerrit Früh. From local wind energy resource to national wind power production[J]. AIMS Energy, 2015, 3(1): 101-120. doi: 10.3934/energy.2015.1.101

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Abstract

Wind power is one of the most established renewable power resources yet it is also one of the most volatile resources. This poses a key challenge for successfully integrating wind power at a large scale into the power grid. Here we present an analysis of the time scales associated with wind power from hourly to seasonal fluctuations and how combining spatially distributed wind power sources helps to reduce its volatility. The analysis, based on observed wind speeds, is then generalised in a simple statistical model to develop a tool which can estimate the power output profile from a particular consortium of wind power sources. As the estimator only uses the local, or the mean national, wind resource and the mean distance between the sites to estimate the joint power output profile, it can be used by developers to estimate the reliability of their joint power output and to form the most effective consortium.

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