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3. Wind Farm Mac Os 7

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Note:

This example use case presents an approach to using ArcGIS to perform a preliminary environmental impact study on wind farm proposals. While the data is real, the scenario, analysis, and resulting decisions are hypothetical.

The primary objective of this case study is to demonstrate proximity analysis using multiple methods. The workflow includes selection tools (Select By Attributes and Select By Location), Hillshade, Viewshed, and Near. Parts of the workflow below require the use of ArcGIS Spatial Analyst extension, which is available with a Spatial Analyst license. If you do not have access to Spatial Analyst, you may use ArcGIS 3D Analyst extension or skip a section of the workflow.

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Going green

As the threat of climate change increases globally, many countries are turning to renewable energy to reduce carbon dioxide and other greenhouse gas emissions. Wind farms are an important source of green energy that are being used to replace electricity derived from fossil fuels, such as coal. While the environmental benefits of replacing fossil fuel-derived energy with wind energy are vast, there can be some environmental concerns with the installation of wind farms in certain areas of ecological importance. The construction of wind farms requires access for large trucks and equipment and can have a temporary but significant impact on the ecosystem.

The GIS analyst in the Scotland Department of Environment performs a preliminary review of the wind farm applications to determine which proposals should be submitted for further assessment. She uses a dataset that includes both existing and proposed wind farm locations. The dataset includes a Status field, which specifies each wind farm as Application, Scoping, Approved, or Installed:

• Application—New wind farm proposals that have not been reviewed.
• Scoping—Wind farms that are in an on-site review phase.
• Approved—The proposal passed all reviews and is ready to be installed.
• Installed—The wind farm has been constructed and is currently operating.

Shutter chance mac os. The analyst is only concerned with the application and scoping phases because those wind farms have not passed all the necessary reviews to move to the approved phase. The analyst reviews the applications and rejects any new wind farms located on or visible from areas designated as wild lands by Scottish Natural Heritage. She also evaluates road access to the remaining proposal sites and uses the information to choose which proposals will be submitted for further review. The steps in her assessment are outlined below.

Which proposals are not on wild lands?

The analyst finds the wild land areas using a polygon dataset created by Scottish Natural Heritage. According to their criteria, wild lands are required to have natural land cover, rugged terrain, and remoteness from modern artefacts (including roads and buildings). Wind farms located on wild lands would impact the remoteness of the areas, as well as disturb the wildlife that rely on the areas as a refuge from human developments. In order to protect the wild lands from any new modern artefacts, the analyst selects any wind farm proposals in the application and scoping phase that are located on wild lands. Those applications are removed from the proposal list and are not submitted for further review.

Which proposals are not visible from wild lands?

It is important that wild land areas have visible remoteness from modern artefacts as well as the physical remoteness determined above. Visible remoteness is important in the wild lands because it helps people who visit the areas experience a more natural and engaging environment. The analyst creates viewsheds from observer points within the wild lands. She is able to use the viewsheds to select proposals that are not visible from the observer points and remove the other proposals from the study.

Which proposals have the best road access?

Installing wind farms can have temporary, negative ecological impacts, especially in vulnerable ecosystems and remote areas with little or no road access. The installation process will include transporting large equipment and materials to and from the site, which will require road access. Thief of hearts - a juno steel dating simulator mac os.

In order to minimize negative effects from constructing new roads, the analyst measures the distance of each of the proposals to the closest road and plots the distances in a histogram. The histogram is used to choose a cutoff distance where wind farms are too remote for further consideration.

The 92 proposals that remain are submitted for a more detailed review to determine potential impacts on the environment based on land cover, habitat, and proximity to bird and bat flyways.

Workflow using ArcGIS Desktop

Note:

The steps below are based on ArcGIS Desktop10.4. Some of the steps require access to Spatial Analyst, but can also be completed with 3D Analyst.

The data can be accessed using the Download button at the top of the page. Double-click on the map package to open the .mxd in ArcMap. The data and .mxd will automatically be saved in your DocumentsArcGISPackages folder. You can also use the Extract Package tool and save the data in a folder of your choice.

Wind farm infringement on wild land areas

The criteria for designating an area as a wild land include perceived naturalness of land cover, ruggedness of terrain, remoteness from public roads and modern artefacts, and visible lack of buildings, roads, and modern artefacts. This section of analysis will ensure that all wind farm applications remain remote from modern artefacts.

1. Use Select By Attributes to select the new proposals (status of Application or Scoping). Use Select By Location to remove the wind farms that intersect with the wild lands from the current selection.

   Note:

   Select By Attributes and Select By Location can be run from the UI or as geoprocessing tools. The images above show the two tools being run from the UI through the Selection menu.

2. Create a new layer using the Copy Features tool. You can apply the symbology from the original wind farm layer by clicking Import on the Symbology tab of the Layer Properties dialog box. The new layer contains the wind farm applications that do not overlap wild lands. Clear the selected features.

Wind farm visibility from wild lands

The criteria for designating areas as wild lands includes a visible lack of buildings, roads, and modern artefacts. This section of analysis will reduce the number of wind farms that are visible from the wild lands.

Note:

This section of the workflow requires access to Spatial Analyst. If you do not have a Spatial Analyst license, you can continue the workflow at step 1 of Wind farm accessibility using the output from step 2 above.

Tip:

It is important to set the Environment Settings for your map document when working with raster data. Set the Output Extent to Same as layerScotland Elev and the Cell Size to 50. You can also set your Scratch Workspace to your current folder.

A Digital Elevation Model (DEM) was created using 50-meter contours and has been provided for elevation-related analysis. Due to the amount of data, the contour files are not included in this case study. If you would like to learn more about creating a DEM from contours, see the References section for the preprocessing steps.

1. Use the Hillshade tool to create a Hillshade raster. Move the raster to just below the elevation raster in the Table of Contents and set the transparency of your elevation raster to 40 percent.

Tip:

You can set the layer transparency in the Display tab of the Layer Properties dialog box.

2. In order to create Viewsheds, you will need a set of observer points representing the spots where the observer is standing. Use the Feature to Point tool to create a layer of points representing the wild lands.
3. Add two new fields to the point dataset (Type=Float). The fields must be named OFFSETA and OFFSETB. The Viewshed tool uses the two offsets to determine the height of the observer (OFFSETA) and the height of the observed features (OFFSETB). Since your data frame's projected coordinate system is in meters, you will have to set the values of OFFSETA and OFFSETB to the height in meters. Use the Field Calculator to set OFFSETA to 1.78 meters (equal to 5'10', an average male height) and OFFSETB to 100 meters, the height of a popular wind turbine model.
4. Use the Viewshed tool to determine which areas are visible from each of the observer points. Using the Viewshed tool is a computer-intensive process; you can decrease the processing time by setting a larger cell size in the tool's Environment Settings. Set a Cell Size of 100 meters under Raster Analysis. The tool may take several minutes to run. You may increase the cell size if necessary.

Tip:

Turn off the elevation layer and set the transparency of the Viewshed to 40 percent to see the relief of the Hillshade under the Viewshed.

5. Open the attribute table of the Viewshed raster. Cells with a value of 0 are not visible from any of the observer points. All other values represent cells that are visible by one or more observer points. Select rows with a VALUE of 1 or higher and use the Raster to Polygon tool to convert the selected raster cells to polygons.
6. Use Select By Location to select the wind farm applications that intersect the visibility polygon. Switch the selection so applications that are not visible from the observer points are selected. Use the Copy Features tool to create a new layer from the selected applications. Clear the selected features.

Wind farm accessibility

Wind farm construction and maintenance requires the use of large vehicles to transport workers and materials. Environmental impacts can be reduced during installation by choosing areas with preexisting road access. This section of analysis will use the distance between each wind farm and the closest road to make the final approval for the preliminary analysis.

1. Calculate the distance of each wind farm polygon to the nearest road using the Near tool. The distance is measured in meters to correspond with the projected coordinate system of the data frame.
2. Create a histogram showing the frequency of the distances. The vast majority of the wind farms are less than 90 meters from preexisting roads; therefore, the analyst can be strict when selecting proposals based on the distance from roads.
3. Wind farm proposals that touch roads or have roads running through them have a NEAR_DIST of 0 meters. Use Select By Attributes to select proposals that already have access to roads.
4. Create a new layer with the selected proposals using the Copy Features tool. Clear the selected features. The remaining applications will be submitted for a more thorough environmental review and final approval.

Workflow using ArcGIS Pro

Note:

The steps below are based on ArcGIS Pro2.0. Some of the steps require access to Spatial Analyst, but can also be completed with 3D Analyst.

The data can be accessed using the Download button at the top of the page. To use the data, extract the package in ArcGIS Pro or ArcGIS Desktop and import the .mxd into ArcGIS Pro.

For information on finding geoprocessing tools, using the Project pane, and other topics, see the ArcGIS Pro help page.

Wind farm infringement on wild land areas

The criteria for designating an area as a wild land include perceived naturalness of land cover, ruggedness of terrain, remoteness from public roads and modern artefacts, and visible lack of buildings, roads, and modern artefacts. This section of analysis will ensure that all wind farm applications remain remote from modern artefacts.

1. Use Select Layer By Attribute to select the new proposals (status of application or scoping).

   Use the following parameters in Select Layer By Attribute:

   • Layer Name or Table View: Onshore Wind Farm Proposals
   • Selection type: New selection
   • Expression: STATUS = 'Application' Or STATUS = 'Scoping'
2. Use Select Layer By Location to remove the wind farms that intersect with the wild lands from the current selection.

   Use the following parameters in Select Layer By Location:

   • Input Feature Layer: Onshore Wind Farm Proposals
   • Relationship: Intersect
   • Selecting Features: Wild Land Areas
   • Selection type: Remove from the current selection
3. Create a new layer using the Copy Features tool. You can apply the symbology from the original wind farm layer by clicking Import in the Drawing group of the Appearance tab or access the Apply Symbology From Layer tool through the Geoprocessing pane. The new layer contains the wind farm applications that do not overlap the wild lands. Clear the selected features.

   Use the following parameters in Copy Features:

   • Input Features: Onshore Wind Farm Proposals
   • Output Feature Class: Wind_Farms_Not_Wild_Lands

Wind farm visibility from wild lands

The criteria for designating areas as wild lands includes a visible lack of buildings, roads, and modern artefacts. This section of analysis will reduce the number of wind farms visible from the wild lands.

Note:

This section of the workflow requires access to Spatial Analyst. If you do not have a Spatial Analyst license, you can continue the workflow at step 1 of Wind farm accessibility using the output from step 3 above.

Tip:

It is important to set the Environment Settings for your map document when working with raster data. Set the Output Extent to Same as layerScotland Elev and the Cell Size to 50. You can also set your Scratch Workspace to your current folder.

A Digital Elevation Model (DEM) was created in ArcGIS Desktop using 50-meter contours and has been provided for elevation-related analysis. Due to the amount of data, the contour files are not included in this case study. If you would like to learn more about creating a DEM from contours, see the References section for the preprocessing steps.

1. Use the Hillshade tool to create a Hillshade raster.

   Use the following parameters in Hillshade:

   • Input Raster: Scotland Elev
   • Output raster: Scot_Hillsh

   Move the hillshade raster to just below the elevation raster in the Table of Contents and set the transparency of your elevation raster to 40 percent.

Tip:

You can set the layer transparency of the selected layer in the Effects group of the Appearance tab.

2. In order to create Viewsheds, you will need a set of observer points representing the spots where the observer is standing. Use the Feature To Point tool to create a feature class of points representing the wild lands.

   Use the following parameters in Feature To Point:

   • Input Features: Wild Land Areas
   • Output Feature Class: WildLand_Points
   • Inside: Checked
3. Add two new fields to the point dataset (Type=Float). The fields must be named OFFSETA and OFFSETB. The Viewshed tool uses the two offsets to determine the height of the observer (OFFSETA) and the height of the observed features (OFFSETB). Since your projected coordinate system is in meters, you will have to set the values of OFFSETA and OFFSETB to the height in meters. Use Calculate Field to set OFFSETA to 1.78 meters (equal to 5'10', an average male height) and OFFSETB to 100 meters, the height of a popular wind turbine model.
4. Use the Viewshed tool to determine which areas are visible from each of the observer points. Using the Viewshed tool is a computer-intensive process; you can decrease the processing time by setting a larger cell size in the tool's Environment Settings. Set a Cell Size of 100 meters in Raster Analysis. The tool may take several minutes to run. You may increase the cell size if necessary.

   Use the following parameters in Viewshed:

   • Input raster: Scotland Elev
   • Input point or polyline observer features: WildLand_Points
   • Output raster: Viewshed

Tip:

Turn off the elevation layer and set the transparency of the Viewshed to 40 percent to see the relief of the Hillshade under the Viewshed.

5. Open the attribute table of the Viewshed raster. Cells with a value of 0 are not visible from any of the observer points. All other values represent cells that are visible by one or more observer points. Select rows with a Value of 1 or more and use the Raster to Polygon tool to convert the selected raster cells to polygons.

   Use the following parameters in Raster to Polygon:

   • Input raster: Viewshed
   • Field: Value
   • Output polygon features: Visible_poly
   • Simplify polygons: Unchecked
6. Use Select Layer By Location to select the wind farm applications that intersect the visibility polygon. Switch the selection so applications that are not visible from the observer points are selected.

   Use the following parameters in Select Layer By Location:

   • Input Feature Layer: Wind_Farms_Not_Wild_Lands
   • Relationship: Intersect
   • Selecting Features: Visible_poly
   • Selection type: New selection
7. Use the Copy Features tool to create a new layer from the selected applications. Clear the selected features.

   Use the following parameters in Copy Features:

   • Input Features: Wind_Farms_Not_Wild_Lands
   • Output Feature Class: Wind_Farms_Not_Visible

Wind farm accessibility

Wind farm construction and maintenance requires the use of large vehicles to transport workers and materials. Environmental impacts can be reduced during installation by choosing areas with preexisting road access. This section of analysis will use the distance between each wind farm and the closest road to make the final approval for the preliminary analysis.

1. Calculate the distance of each wind farm polygon to the nearest road using the Near tool. The distance is measured in meters to correspond with the projected coordinate system of the map.

   Use the following parameters in Near:

   • Input Features: Wind_Farms_Not_Visible
   • Near Features: Roads

   The NEAR_DIST field is added to the Wind_Farms_Not_Visible

2. Create a histogram showing the frequency of the distances. You can create a chart by right clicking Wind_Farms_Not_Visible and choosing Create Chart. Select NEAR_DIST as the number variable.

   Note:

   Retro combat mac os. You may have to remove and re-add the Wind_Farms_Not_Visible layer before you can use the newly added fields in a histogram.

   The vast majority of the wind farms are less than 90 meters from the preexisting roads; therefore, the analyst can be strict when selecting proposals based on the distance from roads.

3. Wind farm proposals that touch roads or have roads running through them have a NEAR_DIST of 0 meters. Use Select Layer By Attribute to select proposals that already have access to roads.

   Use the following parameters in Select Layer By Attribute:

   • Layer Name or Table View: Wind_Farms_Not_Visible
   • Selection type: New selection
   • Expression: NEAR_DIST = 0
4. Create a new layer with the selected proposals using the Copy Features tool. The remaining applications will be submitted for a more thorough environmental review and final approval.

   Use the following parameters in Select Layer By Attribute:

   • Input Features: Wind_Farms_Not_Visible
   • Output Feature Class: Wind_Farms_For_Review

Workflow using ArcGIS Online

Note:

The workflow for ArcGIS Online uses the Find Existing Locations and Create Viewshed tools. Analysis tools are available with an ArcGIS Online organizational account with administrator privileges. Running analysis tools in ArcGIS Online also requires credits. Check the number of credits required to run a tool using the tool pane.

Use the workflow from the Environmental Assessment of Wind Farms in Northern Scotland Story Map to perform the environmental assessment in ArcGIS Online. The data used in the app includes a sample of the Onshore Wind Farm Proposals, Wild Land Areas 2014, and ROAD shapefiles, as well as a sample of the point file created from the Wild Land Areas 2014 layer.

Resources

Data resources

Photo attribution

Preprocessing steps for creating a DEM from contours

Digital Elevation Models (DEMs) are raster datasets that store an elevation value in each cell. Many of the tools in the Spatial Analyst toolbox require raster data as input. However, a DEM may not always be available for download. The process for converting vector-based elevation data, such as contours, into a raster is outlined below. Although the process is simple, the size of the area and contour interval may make the process time consuming. If you are converting contours to DEMs frequently, you may want to automate the process using a model or a Python script.

Note:

It is important to set the Environment Settings for your map document when working with raster data. Set the Output Extent to Union of Inputs and the Cell Size to 50. You can also set your Scratch Workspace to your current folder.

1. Order the free OS Terrain 50 and Boundary-Line datasets from the OS OpenData website. You will be able to download the data using links that will be sent to you by email after the order form is filled out. You may also choose to complete these steps using your own data.
2. Use the National Grid Reference Squares to determine which datasets are required for your study area. This example will use data from square NS. The folders contain zipped files numbered from 00 to 99 as seen below.
3. Use theMerge tool to merge the NS files into four larger files using the color scheme seen in step 2 above.
4. Use the Topo to Raster tool to convert the contours to a raster. Use a shapefile from the Boundary-Line download to set a Mask in the Topo to Raster tool's Environment Settings. The mask will limit the interpolation process to the boundaries of the shapefile, which also corresponds to the boundaries of the contours. Without a mask, the Topo to Raster tool will interpolate the elevation of the entire raster extent, including areas where there are no contours, which could lead to interpolation errors in coastal areas.
5. If necessary, use the Mosaic To New Raster tool to combine multiple rasters into one large raster. You can determine the appropriate input for the Pixel Type and Number of Bands from the Source tab of the Layer Properties dialog box for one of the rasters created in the previous step.

Summary

This case study demonstrates a number of analytical methods that can be adapted to many different application areas, allowing you to answer a variety of questions.

Sarah Herman
WindFarmer Specialist
GL Garrad Hassan
Austin, Texas
www.gl-garradhassan.com

Wind-farm designs and energy assessments are complex processes that vary greatly depending upon the constraints and challenges of each site. Stakeholders such as developers, utilities, and financiers must technically evaluate a project to determine its profitability and feasibility. Software that can model the performance of all types of farms is essential in the wind industry. Some key features and models needed in such wind-farm design software are highlighted here, using the latest WindFarmer 4.2 software developed by GL Garrad Hassan as a platform for discussion. A number of features in the software come from years of development and hence deserve attention. For example:

The graphic user interface on WindFarmer software shows a few selections and results for a large proposed layout. Panels on the left show selections and those on the right, calculations. The graph inset describes a turbulence model.

Energy calculations: Energy-production values calculated for a wind farm require several inputs to properly evaluate a site's estimated energy generation. The topography for a wind farm and its site boundaries can be loaded into the software as ESRI shape files. The wind flow should be characterized from on-location measurements and extrapolated to the rest of the site. Its historical air density must also be evaluated.

Efficiencies and loss factors specific to the site should be understood, and a turbine layout and power curve must be selected. Once this basic site information is entered, the type of analysis method chosen to calculate energy depends on the characteristics of the wind farm being assessed.

A wind farm's energy production greatly depends on the wake effects from upwind turbines. Hence, an accurate wake model is key to an accurate estimate. WindFarmer software has several wake models that can consider specific challenges found in the broad range of wind farms in development and operation.

Wind-farm wake modeling: The Eddy Viscosity Wake Model is a CFD model developed, refined, and validated using operational wind-farm data for many years. The model provides a successful wake-modeling algorithm for a wide variety of common situations. The software also includes several modifications to this base model for wind farms that fall outside a normal operational envelope of the model. With these adjustments, the exceptional characteristics of regions with such observed wind regimes can be taken into account.

Wakes in complex terrain: Environmental parameters such as air density and turbulence levels as well as development of the wake are a function of the underlying topography. Based on the turbine's position in the terrain, the software adjusts turbine-wake development and the energy calculated.

The inset image suggests how the wind farm will appear from ground level.

Closely spaced wind farm layouts: A closely spaced wake model allows completing wake modeling on wind farms that are built for one or two-directional wind regimes. This type of wind farm has unique challenges. Such regimes lend themselves to turbine layouts that are positioned close together in one direction to maximize electricity generation per given area. Turbine wakes in such a layout do not propagate independently, and so must be modeled differently. The software's Eddy Viscosity Model for Closely Spaced Turbines effectively models wakes propagated for this type of wind farm by altering the classic Eddy Viscosity model and letting velocity deficits caused by the wake effects add cumulatively.

Large wind-farm model: As the wind industry has developed, the size of wind farms has increased on and offshore to include some that are greater than 100 MW in size and many rows deep. A Large Wind Farm Wake Model simulates increased wakes generated by large wind farms. The model works by considering several characteristics specific to large wind farms, the most important being alterations to the boundary layer caused by the presence of many turbines extracting momentum from the atmosphere. As a result, the wind profile varies across the farm, an effect analogous to an increase in surface roughness length. Within WindFarmer, this technical and crucial feature is engaged with a check box where the software performs all analysis of upstream turbines to derive added wake losses due to the large wind-farm wake effect. The Large Wind Farm Wake Model has been tested and validated with operating offshore and onshore data. Furthermore, the speed of the energy yield calculation – typically 10 to 15 minutes for a 100-turbine array – lets wind farm designers explore many different layout options within a reasonable timeframe.

Data from site assessments display in WindFarmer showing an inset wind rose of wind speed and directional probability along with a contour map of color coded wind-energy levels.

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Uncertainty analysis: Once a site's estimated energy production calculations complete, the uncertainty associated with the results must be quantified. Uncertainty calculations are essential to quantify and assess the asset's viability and profitability to raise project financing. As such, the software includes uncertainty analyses into its results to evaluate the many sources of uncertainty present within the development process, such as data collection sensors, topographic modeling, and yearly variations of the on-site wind regime. These uncertainties derive the relevant exceedance levels so stress cases can run and debt-service coverage ratios converted into currency for pro forma preparations.

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Efficient wind farm design: Software for designing wind farms offer a range of tools to support the engineer designing a productive wind farm. These tools include aids for automatic generation of both random and symmetric layouts with high-energy yield. Using the advanced tools to design a wind farm can help mitigate project deficiencies found later in the detailed energy assessment. As wind farms become larger and more complex, scientific research is increasing understanding of how wakes behave within such a complex environment. Software such as WindFarmer is essential to leverage this knowledge and produce reliable estimates of electrical-power production.

WPE