Toolkits for tranquility and windfarms

Sunday 3rd July 2011
Tranquility and windfarm.

Bradford University researchers in the UK have developed a toolkit for measuring tranquility that could enable neglected or overlooked urban parks to flourish and become havens for stressed city workers. At Technical University of Denmark, nine national and international partners working on EU project TOPFARM have developed a five calculation toolbox to optimise windfarm layouts and topology.

Professor of Transportation Noise in  Centre for Sustainable Environments at the School of Engineering, Design and Technology at the University of Bradford, Greg Watts, says the method will help urban planners design better parks, and improve existing amenity areas.

“We know that tranquil environments are important for wellbeing,” he says. “When people are surrounded by images of nature and hear natural sounds rather than mechanical noises they find it easier to recover from stress. Our research assessed what particular factors would improve tranquillity in green open spaces, and what factors would degrade it, so that an overall tranquillity rating can be calculated.”

Professor Watts has devised a series of methods to assess noise levels and the visual scene to give each amenity an accurate and consistent ‘tranquillity rating’ and volunteers recruited.

Factors that were taken into consideration included the amount of man-made noise, for example traffic or aircraft noise, natural features such as water, trees and plants, and man-made features such as historical or traditional buildings.

The method was put to the test in three parks in Bradford. Using photographs, ‘noise maps’ published by DEFRA  and spot readings of noise levels, researchers were able to rate each amenity, and also make a series of recommendations for improvements. (Those who want to play noise maps in Scotland will find this disappointingly limited to just Glasgow and Edinburgh).

“Local councils are in difficult financial straits at the moment, but they need to consider the needs of their citizens and continue to adequately maintain and improve existing parks and where necessary create new green open spaces,” urges Professor Watts. “Investing in urban parks can have a big impact on the health and stress levels of the people who use them.

"Research we have carried out previously shows that even leaving litter in a park can significantly reduce the tranquillity of the environment. Ensuring that these urban green spaces are maintained to the right standard is an important investment for the long-term well-being of citizens.”

Prof. Watts’ research demonstrates that even in densely populated areas planners can calculate best value approaches to improving urban amenities that will achieve acceptable levels of tranquillity.

“If the park has a low tranquillity rating, there are a number of options to consider and the formula we have developed would enable planners to select the best value approach in each case,” says Prof. Watts.

“For example, we could calculate what effect reducing traffic noise would have on a park’s tranquillity rating. We would then be able to predict which improvement measures, would be most effective in terms of cost and impact. A range of measures could be considered, including erecting screens or barriers to redirecting traffic or even resurfacing roads with a low noise surface.

On the other hand it might prove more cost-effective to improve the visual scene by the introduction of more shrubs and trees and by the screening of surrounding buildings if of little historical value or installing an appropriate water feature.”

Five module toolbox for windfarm planning

The completed project, TOPFARM, has focused on how a wide range of factors affect economic optimum locations of each wind turbine within wind farms – in technical terms the topology of a wind farm turbine wakes.

Contrary to common practice, production as well as costs associated with the establishment and operation of each wind turbine are included in the model of calculation.

The picture shows first the current location of wind turbines in wind farm Middelgrunden, then the economically optimized location calculated using TOPFARM tools. (photo: Gunner Chr Larsen)
 


These costs generally cover expenses which depend on the topology of the farm. They could be costs associated with operation and maintenance; costs related to the fatigue load of the main components of a wind turbine and startup expenses related to foundations, grid, roads etc.



”A selected case analysis of Middelgrunden Windfarm has shown, that the exact expenses to establish, for example, an electricity network, means a lot to the total benefit.

"The analysis also shows the load caused by turbulent wakes behind each wind turbine that could have an impact on the optimum wind farm topology and on the economy of a wind farm - this aspect would naturally not be considered by an optimisation model exclusively relying on the final product, namely power generation, " explains Gunner Chr. Larsen, senior scientist, Risø DTU. 

He has been the project coordinator for TOPFARM with its 9 national and international partners from industry as well as research.



Tool box 

The core of the optimization tool consists of 5 calculation modules. The first module consists of models (of varying complexity) that describe the wind inside a wind farm.

The second module is a detailed model of how the wind affects each wind turbine in a wind farm. The input to this module is the wind field from the first module and the result is production data and load data from the individual turbines.



The third module comprises models of the control system at both wind farm level and wind turbine level, while the fourth module contains cost models, that make it possible to formulate the optimisation problem in economic terms. 



The last fifth module is a pack of optimisation algorithms that, with the input from the other four modules, generates the optimum layout of a given wind farm. This is the module that gave rise in the case story to the new location of turbines at Middelgrunden wind farm, as seen on the picture (above)."

From the direct economic output of the wind farm – power generation - costs with regard to the wearing down caused by load, for example, must be deducted because of the consequent repair and reduced service life of key wind turbine components.

But startup expenses, which are directly affected by the location, can also be crucial to the economy – eg at sea where foundation costs typically depend on the depth of water.

Should the turbines be arranged differently so that they 'provide less shade’ from each other?  Is it necessary to build a road or some other infrastructure in connection with a particular location of wind turbines inside a wind farm? If so, it is important to include these considerations in your calculations,” explains Larsen.



The simplified models used today to set up wind farms, primarily looks at how much power is generated from the farm. But the TOPFARM project clearly shows that there is a need for a more complex model that can incorporate far more and more complex factors.



Next step: a user-friendly program 

When one takes the optimal location of each turbine as one's starting point, there will be millions of location options for the wind turbines. This means that even a supercomputer will have a demanding job, if you do not ensure that  calculations at each level of the optimisation platform are carried out as efficiently as at all possible.



Consequently, it has been a big challenge for TOPFARM to develop fast models without jeopardising the essential physics of the individual sub-modules.

In addition, the amount of calculations in the optimisation procedure can be reduced using so-called structured grid, where the location options of the individual wind turbines are limited in advance, for example by only allowing locations on selected curves. 



The TOPFARM optimisation platform is currently a research tool, but the vision of Risø DTU scientists is to pursue opportunities to create a more user-friendly programme that can be used by wind farm developers in their daily work.

The basic sub-models have already been developed in the TOPFARM project, and efforts will therefore primarily concentrate on a more streamlined implementation of software and on developing a suitable user interface.
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