Virtual Wind Farm Simulation

No. 6September 2017 Volume 13

INTERNATIONAL

A Closer Look at the WakeBlaster Project

This article appeared in the September 2017 issue of Windtech International and is displayed with permission. Copyright 2017 by Siteur Publications.

| Reprinted from September 2017 Windtech International |

The development of fast and accurate wind farm simulation software is a crucial step to meet the needs of the industry. Developers and operators can simulate the response of wind farms before construction, optimise their strategies during operation and gain an advantage in electricity trading. We are living in interesting times, and with the new tools developed in the WakeBlaster project we can now realise adaptive wind farm control strategies.

A wind turbine converts part of the incoming kinetic energy of the ambi-ent airflow into electrical energy. This creates an area (the wake) of reduced wind speed and increased turbulence downstream of the wind turbine. An accurate description of the wake hands back control to the wind farm operator.

A Brief History of Wake ModellingThe earliest wind turbine wake models, developed in the 1970s, were based on mesoscale models with a typical resolu-tion in the order of 1 kilometre, and turbines were represented by a momen-tum sink. The approach described the large-scale interaction of the atmos-pheric boundary layer with the wind turbines. Models of infinite wind farms were parameterised by the density of

turbines placed, and provided first indi-cations for the optimum turbine spac-ing in wind farms.

The industry today uses microscale wake models that were first introduced in the late 1970s and 1980s. Most are derived from models developed for rocket engines and jet aircraft. To create a jet, the flow of air through an area is accelerated by a device (actuator), and then it develops freely downstream. Using the jet analogy, detailed models of single wakes were developed and implemented in commercial wind farm design software. Single wake models are then superimposed, using semi-empirical models.

Wake Models in Use TodayWakes evolve in a complex way as they gradually dissipate, due to turbulent mixing with the ambient airflow. A wake model used to model today’s wind farms needs to be able to cope with length scales ranging over six orders of magnitude: from a few metres (the width of a rotor blade or blade tip sec-tion) to well over 100 kilometres (the size of a cluster of wind farms).

The complexity of wake models used by industry varies. Very broadly speak-

ing, for industrial application there are only two families of wake models in use today: Jensen/Park and Ainslie.

The Jensen/Park Family of Wake ModelsThe simplest wake model in use today is known as the Jensen/Park model. It was developed in the mid-1980s, with further refinements added over time. It is a relatively simplistic model of tur-bine wake behaviour and uses a single parameter (the wake angle, k) to charac-terise the wake expansion downstream from the turbine.

The Jensen/Park model is calibrated to describe the wake losses of a small wind farm. Due to its lack of detail, the model is not very good for describ-ing wake losses for either individual turbines or large wind farms. To com-pensate for this, different adjustments of the k parameter are in use for rough-ness, turbulence or offshore conditions.

Although somewhat crude, this model is computationally very fast and use-ful for first estimates of annual energy production for a wind farm. Thereafter, most experts would use a more sophis-ticated model to obtain more detailed annual energy estimates.

The Ainslie Family of Wake ModelsIn the late 1980s the Ainslie wake model was developed. This numerical approach involves the solution of the Navier Stokes equations (fundamental conservation laws for fluids). To run the model on a personal computer, it was at the time, and still is even today, necessary to use the Reynolds Averaged Navier Stokes Equations (RANS) and a turbulence model (closure) to describe

The WakeBlaster project team was formed in January 2017 and is an interdisciplinary team of six dedicated

scientists, software engineers, expert computer modellers and wind industry professionals. Together the team has

over 55 years of experience in the wind industry. Its mission is to produce a cloud-based software component

which delivers down-to-earth, cost-effective, scalable and dynamic yet accurate wind farm simulations.

A Closer Look at the WakeBlaster Project

Virtual Wind Farm Simulation By Dr Wolfgang Schlez, Director of ProPlanEn, UK

Figure 1. The ProPlanEn team outside Bristol Cathedral

| Reprinted from September 2017 Windtech International |

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the information lost through averag-ing. The assumption of cylindrical sym-metry of the jet reduced the problem by one dimension, from 3D to 2D.

The Ainslie family of models is today the wake model most often used in the industry, with distinct implemen-tations in all major wind farm design software packages. Several approxima-tions have been introduced over the years, either to further speed up the cal-culation or expand the model’s opera-tional envelope for specific cases (wake meandering, large wind farms, close spacing, etc.).

Research ModelsMore complex computational fluid dynamics (CFD) approaches are used in academic environments, including general purpose 3D RANS solvers with sophisticated turbulence modelling, detached eddy simulation (DES) and large eddy simulation (LES). The more complex the approach, the more com-putationally intensive it becomes. A great amount of detail can be modelled and a lot can be learned from the ongo-ing active research in the area. On the other hand, the research models tend to be too demanding for industrial application.

WakeBlaster – A New Approach to Wake ModellingOver time, various refinements have been made to the existing wake models. However, from a modelling perspective it is not satisfactory to increase the number of semi-empirical approxima-tions contained in what are already over 30-year-old wake models. What the industry needs is a fresh approach.

Applications for the Next-Generation ModelThe WakeBlaster project marks the dawn of a new generation of wind farm simulation tools. The new software component features are scalable, and faster than real-time simulation, with improved accuracy and a higher level of detail than conventional methods. Previous semi-empirical approxima-tions for 3D effects are replaced by numerical modelling.

Wind farms are continuously subjected to dynamic changes over their lifetime, triggered (for example) by environ-

mental or technical curtailments, or by maintenance or construction phases. Conventional models can only account for these effects on a statistical basis. On the other hand, dynamically changing conditions (time dependency model-ling) are second nature to WakeBlaster. Time domain modelling can bring deci-sive advantages, as detailed under the headings below.

Energy Assessment and Planning• Reduced uncertainty – current

models assume a range of fixed wind speeds and direction sce-narios at neutral stability. Using a time-based wind farm simulation, atmospheric stability (density, tur-bulence, shear profile) becomes a variable which is continuously adjusted, so the model can better represent the true situation.

• Improved 12x24 (months x hours) production assessment – the mar-ket value of wind power changes from hour to hour and day to day, depending on the energy mix and actual demand. Traditionally a fixed set of scenarios is used. Modelling this temporal variation directly allows us to achieve a more accurate representation of the energy produced.

• Reduced losses through optimised curtailment strategies, both tech-nical and environmental - The effect of switching turbines on or off can be modelled in faster than real time using live, incom-ing wind data. This allows for the optimal sequencing of curtailment strategies e.g. for turbine mainte-nance, grid-balancing, migrating birds etc; thus allowing the opera-tor to minimise losses.

Monitoring and Control• Real-time comparison with the

simulation enables the early detec-tion of performance issues with individual turbines that require action.

• Simulation of scenarios optimises the operation during scheduled or unscheduled maintenance periods.

• Simulation and implementation of wind farm control strategies that yield performance improvement or reduce turbine loading.

Forecasting and Energy Trading• Reduced uncertainty in short-

term forecasting based on past performance, giving the ability to schedule wind power and trade on capacity markets.

Figure 2. Development and merging of wakes in Horns Rev 2 wind farm (courtesy Bel Air Aviation Denmark – Helicopter Services. doi 10.3390/en10030317)

Figure 3. A wind farm simulator modelling the aerodynamic interaction (wakes) bet-ween the wind turbines for each timestep

Copyright Windtech International | Dr C Hofstede de Grootkade 28, 9718KB, Groningen, The Netherlands | www.windtech-international.com

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• An accurate simulation of scenar-ios enables the implementation of adaptive turbine control (e.g. when a gust hits the first turbines in a wind farm).

Integrating the New Software into Existing Modelling ToolsThe software is designed as a SaaS (Software as a Service) application with an open API (Application Programming Interface), and implementation exam-ples are provided, giving easy access for anyone with basic programming skills. The project team is working closely with major consultancies, oper-ators and software solution providers, to assist the integration of the software component into their existing software and processes. The model has been calibrated using data from over 15 wind farms and over 20 years of production data provided by operators.The project team has developed a new, purpose-built CFD model for indus-trial application which meets industry demands in five key areas:• RANS equations in 3D• full wind farm model• dynamic time domain simulation• fast, accurate and affordable for

everyday use

• cloud based with scalable perfor-mance

The model provides new insights and hands control back to the develop-er and operators. By leveraging cloud technology, we can provide fast, cost-effective and scalable solutions. It is a game-changer, and it ups the level of the state-of-the-art by quite a few notches.

Next StepsFor further testing and feedback ProPlanEn has released a Beta version of WakeBlaster and this is being put through its paces by interested par-ties. Model validation results will be published at industry events over the coming months.

In autumn 2017 WakeBlaster will be launched commercially. Potential cli-ents have been consulted about inte-grating WakeBlaster into their tool-kits, and suggested modifications to best suit their needs and approaches. Feedback, to date, has been extremely positive.The WakeBlaster project was co-fund-ed by the UK’s Innovation Agency, Innovate UK.

Further Reading• The 2016 Horns Rev Photo Case;

Creative Commons Attribution Licence, www.mdpi.com/1996-1073/10/3/317

• Flow and wakes in large wind farms: Final report for UpWind WP8, http://orbit.dtu.dk/fedora/objects/orbit:86070/datastreams/file_5587428/content

Dr Wolfgang Schlez holds an MSc (Dipl. Phys) from Oldenburg University in

Germany and a PhD from Loughborough University, UK. Since setting up his first wind measurement in 1990, he has worked in wind flow model-

ling and wind farm design, includ-ing 16 years at Garrad Hassan (now DNVGL). Dr Schlez is now Managing Director and runs the wind energy consultancy ProPlanEn.

AffiliationProPlanEn3 Portwall Lane, Bristol BS1 6NB, UKinfo@proplanen.comwww.wakeblaster.net