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Thursday, 13 March 2014
09:00 - 10:30 The model chain: First steps towards tomorrow's technology
Resource Assessment  


Room: Tramuntana
Session description

Recent advances in the software and computational resources available to the wind industry have opened a new frontier; the ‘model chain’. A single approach to such a concept has yet to emerge as the industry standard, although a general idea of a dynamic process across progressively smaller scales is emerging. This session intends to give delegates a broad view of how research institutes and private companies are dealing with this challenge, what the most promising approaches are and which range of applications is foreseen for the coming years.

Learning objectives

  • Understand some of the challenges of multi-scale modelling
  • Get a first glimpse of current approaches in this topic
  • Talk directly to the main players in this research field
Lead Session Chair:
Pep Moreno, Vortex, Spain

Co-chair(s):
Hans E. Joergensen, DTU Wind Energy, Denmark
Andrea Hahmann Technical University of Denmark, Denmark
Co-authors:
Andrea Hahmann (1) F P Jake Badger (1) Joakim Refslund (1) Chris Lennard (3) Jens Carsten Hansen (1) Niels Mortensen (1)
(1) Technical University of Denmark, Roskilde, Denmark (2) University of Cape Twon, Cape Town, South Africa (3) University of Cape Town, Cape Town, South Africa

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2014 and are published here unedited

Andrea Hahmann is a senior scientist in the department of wind energy at the Danish Technical University (DTU Wind Energy). She has worked with atmospheric mesoscale and climate models for the past 20 years. Before coming to the wind energy field 5 years ago, she worked in research of the influence of land cover to climate and in atmospheric transport and dispersion problems. She now works on research applied to forecasting wind power through models and in regional wind energy resource assessment.

Abstract

Validation and comparison of numerical wind atlas methods: the South African example

Introduction

The Wind Atlas for South Africa (WASA) is a 4-year project with the objective to develop and employ numerical wind atlas methods and develop capacity to enable planning of large-scale exploitation of wind power in South Africa. The main deliverable of the WASA project, which is scheduled to end in March 2014, is a numerical wind atlas and database for South Africa.


Approach

Two numerical wind atlas methods were used in the project: a statistical-dynamical downscaling method (KAMM/WAsP) and a purely dynamical method based on simulations using the mesoscale Weather Research and Forecasting model (WRF). In this presentation we describe the techniques used and analyze the wind atlases produced by these two methods. These two models represent to different links in the modeling chain.

Main body of abstract

The wind climate of South Africa is driven by a variety of processes: thermally driven jets and sea breezes along the west and east coasts, and strong synoptic-scale systems in the south. The complex terrain in the interior has also a significant effect on the wind climatology. Therefore, using models to simulate the mesoscale wind climatology is challenging. Two methods were used for the production of the numerical wind atlas of South Africa.

Firstly, the statistical-dynamical KAMM/WAsP method was used. In this method, the large-scale atmospheric patterns (from reanalysis) are binned into approx.150 wind classes according to pressure gradients (geostrophic winds), wind direction and atmospheric stability. Idealized simulations are performed for each of these wind classes and the results combined according to their frequency of occurrence. Generalization of the wind climatology is used for verification against measurements and for coupling to microscale models.

Secondly, the WRF reanalysis method was used. In this method, time-dependent simulations covering most of South Africa are performed using the state-of-the-art WRF model. The resulting winds from these simulations are combined into a wind climatology and generalized using an approach similar to that in the KAMM/WAsP method. The procedure, based on a large ensemble of simulations, used to identify the best WRF model configurations to be used for South Africa, is described.


Conclusion

Results from the two methods are compared against each other and validated against 3 years of measurements from WASA’s ten high-quality 62-meter masts. Assessment of the two methods is done in view of the geographical region and the physical process that is responsible for its wind climatology. The sensitivity of the wind climatology to the various WRF setups is also explored in the presentation.


Learning objectives
The learning objectives of the presentation are the knowledge of the different methods used to simulate the wind climate over South Africa and how they validate against observations for different regions and climate regimes.