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Proposal for
Wind Farm D
Table of Contents
Executive Summary.........................................................................................................................2
Introduction......................................................................................................................................3
Site Selection...................................................................................................................................5
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Overview of Potential Sites..........................................................................................................6
Data Analysis.............................................................................................................................16
Results of Analysis: Wind Resources.......................................................................................20
Xcel Load Data..........................................................................................................................24
Analyzing the Data.....................................................................................................................26
Final Site Selection....................................................................................................................33
Equipment Selection......................................................................................................................39
Construction Schedule...................................................................................................................51
Power Purchase Agreement...........................................................................................................55
Power Purchase Agreement
Wind Farm Development Response to Xcel Energy RFP2
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Public Service Company of Colorado
Executive Summary
Ventus, Inc. is submitting this response to the Request for Proposal given to us by Xcel
Energy. This response meets all and in some cases exceeds the specific requirements set forth in
theRFP.
Ventus, Inc. brings a unique and highly informed perspective to the installment of a new
potential wind farm. The group members who have helped put this proposal together have had
lessons in operations and information management to help them with this response. The
development plan calls for intensive research and analysis of wind data along with other
environmental factors.
This proposal lays out our selection of one of eight different sites that we looked at over
the course of four months. This plan allows for Xcel to start development of a wind farm that
they want to reduce carbon emissions by implementing an eight-year 1,600 MW plan.
This submission also looks at many different factors other than wind data. Anything from
proximity to transmission lines and access roads to community acceptance of wind farms. We
have drilled down into these important factors, as you will see in this proposal. Not only have we
looked at these factors, but we have also done intensive research on the product. Cross-
functionally analyzing specifically which turbines and other structural elements will be the most
cost efficient for Excel.
Throughout this period of research and development, we have really tried to look into
aspects that are not the obvious ones. Really looking specifically at what one Xcel really cares
about according to the RFP they sent out, are the ones we wanted to focus on. Because of that, it
is as part of its continued commitment to Excel, that we present the development plan presented
herein.
Wind Farm Development Response to Xcel Energy RFP3
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Public Service Company of Colorado
Introduction
In this study, we were given the task to respond to an RFP given by Xcel Energy. Their
proposal lays out that they want to meet their standards and requirement for their renewable
energy sector by implementing an eight year plan. In this eight-year plan, Excel wants to reduce
their carbon emissions with an approximate
1,600 MW output to be able to cover peak seasons over these eight years. The Public sector
estimates that they will acquire 850 MW going up each year by 100-200MW. From those
guidelines, our job is to choose one out of eight sites given to come up with which site we think
would be the best for Xcel to invest in economically. In order to analyze data given and other
factors to consider, our group decided to split it up into three different sections: wind data, social
& environmental factors and finances related to purchasing all the equipment.
Wind data is a small unit, but there are so many angles to look at it that we though it
deserved its own group. Being order to slice and dice the data for each site and cross-analyze it
over different time periods will give us an optimum view on which site to choose. We will look
at the data by month, by season, by time of day, by elevation, etc. Being able to drill down into
these numerous categories will allow us to broaden or perspective on little details that could go a
long way when it comes down to picking a site.
Along with the data analysis, there are many social factors to consider before picking a
site. The biggest social factor we will look at is community acceptance. Are people aware of
wind energy? What is their take on it? Do they like it? How would they feel if they had to look at
turbines all day? Is there some already in place? Getting these insights early will allow us to not
run into any problems later when we talk about selection and implementation of the project.
Wind Farm Development Response to Xcel Energy RFP4
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Public Service Company of Colorado
Other social factors are proximity to different structures like cities, dwellings and other
population centers. How will people react if it was close to their homes? Close to where they
work? On the environmental side we need to look at foundation. Do we need to lay concrete
down? How is the soil? With that we need to understand how close these sites are to
transmission lines and access roads because costs like that on these minor details can add up in
the end.
The last section comes after all this preliminary background work. Now that we have
gone ahead and look at all eight sites side by side, how are we going to pay for this? We will
look at many different companies that sell turbines to see which ones will gives us the most
profit. We need to understand costs of the building process. Which turbines need more
maintenance than others? Which companies turbines have the best track record? All of these
costs of the actual hardware will be another huge factor we consider in this response to the RFP.
In this proposal to follow, you will see the steps that we took to take all of these factors
and put them into an informed decision on which site we believe would be the smartest choice
for Xcel to move forward on.
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Site Selection
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Site Selection
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Overview of Potential Sites
Community Acceptance
Having community acceptance is a small task, but is something that needs to be taken care of atthe forefront. If you do not have community acceptance and you go ahead and start spendingmoney and planning to but a wind farm in place, it only takes one person to really but a speedbump in your process. These are the results that I found on community acceptance whether itwas through the county commissioner or on the Internet.
Peetz: We were not given a ton of information from the commissioner on community acceptanceother than there has not been extensive talk about it but seemed open to all ideas and thoughtcommunity would react positively to it.
Keystone: Commissioner was stubborn. A lot of environmental factors with being on top of a
mountain that people are a little concerned about but are interested in learning more about it. Themain concern that was brought up to me was that it could potentially be a big eye sore for peoplegoing up to the mountains to relax not wanting to see the turbines.
Lamar: Wind farm already in place so there is great community acceptance for Lamar. Peoplehave been open to the idea for a while and there has been a positive reaction to the farm alreadyin place according to the commissioner that I spoke with.
Kit Carson: Talking with the county commissioners office, there is a plan in place to startdevelopment of a wind farm in Kit Carson. There has been great community support for thisdevelopment so another development would be great here because the community is alreadyinvested in this type of renewable energy.
East Monument: Not much information and questionnaires sent out to public for feedback but ifthey opportunity rose, they would support trying to get community acceptance for a wind powerproject. The commissioner was very helpful an interested in telling me that from what he knew,the community would generally have a positive reaction to it.
West Pueblo: Good support all around. Community is all for the idea of wind projects. Theyhave seen the success of other wind farms around the U.S. especially Colorado and like the idea.There have been talks about it according to the commissioner, and the overall consensus is good.
Wyoming: Talked briefly with the county commissioners office and could not get too much
information. They seem to be open to the idea, but there has not been too much talk about it fromwhat I could tell.
Nebraska: Have not been contacted by personnel we tried to get in contact with. Left messagesand sent email and have not gotten a reply.
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Proximity to Population CentersBeing close to population centers could pose a problem. These can be anything from nationalforests to residential areas. Structures already in place that might slow the project down is
another aspect you have to handle before the project gets going.
Peetz: Close to Pawnee National Grasslands. Pretty far from all major roads.
Keystone: Really close to White River National Forest. Other than that there are not anyestablishments that would distract people and make them not want this wind farm at thislocation.
Lamar: Middle of nowhere. Close to smaller roads and about 5 miles from a major highway.
Kit Carson: Pretty wide open other than it being about 10-15 miles from I-70. Possible NIMBY
problems with a couple people.
East Monument: Pretty good location in terms of disturbances. It is wide open around the area.Not many roads, public institutions or homes. There is a country club about 8-10 miles southwestof the location. Also there are a couple national or state parks in the area but nothing as close as4 miles.
West Pueblo: Pretty good, not to close to major roads but it about 10-15 miles from the SpanishPeaks Airfield. Being that far away should not cause a problem to the airfield especially becauseit is a smaller municipal airport so there is not as much traffic coming in and going out.
Wyoming: Great spot as well. About 4-5 miles away from a pretty big highway.
Nebraska: Middle of nowhere. 10-15 miles from a major highway. Away from cities so greatspot to not interfere with community.
Proximity to Transmission LinesThe map on the next page is an overlay of the transmission map compared to where each site islocated. This map marks each site with a yellow pin. The transmission lines map is laid over thetop to show how close each site is in relation to the power lines.
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Proximity to transmission Lines and Access Roads
Map Key: Blue Lines: proximity to transmission linesRed Lines: proximity to access roads
Keystone
Transmission: 1.8 miles from siteAccess Roads: .19 miles from site
West Pueblo
Transmission: 12 miles from siteAccess Roads: .19 miles from site
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Monument
Transmission: .85 miles from siteAccess Roads: .04 miles from site
Wyoming
Transmission: 18 miles from siteAccess Roads: .15 miles from site
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Nebraska
Transmission: 10 miles from siteAccess Roads: .18 miles from site
Lamar
Transmission: 6 miles from site
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Access Roads: .10 miles from site
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Kit Carson
Transmission: 3.8 miles from siteAccess Roads: 2.1 miles from site
Peetz
Transmission: 9 miles from siteAccess Roads: .37 miles from site
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Capacity
This allows us to see how many turbines are allowed on each site. The National
Renewable Energy Lab website allows you to pin point the exact location and they will tell you
how many turbines would fit that site. These are the results we found from this source:
Monument: 25-30 turbines
Wyoming: > 40 turbines
Nebraska: 30-35 turbines
Lamar: 30-35 turbines
Kit Carson: 30-35 turbines
Peetz: 25-30 turbines
West Pueblo: 35-40 turbines
Keystone: > 40 turbines
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Look at these numbers it is essential to find a site that not only has enough room for the
amount of turbines you want to build, but also a site that makes sense with the capacity factor on
how many that percentage suggests you put on your site.
The screen shot above is from the program JEDI. This program also shows you how you
can figure out your optimal number of turbines to use on your site. By plugging in the number of
MW, turbine size and other elements it will generate what they believe would be a good number
of turbines to put in place at your site. From that you can look at the numbers from the NREL
site to see if that agrees with how many they believe can fit on that particular site. This will allow
us to make sure that we are being smart about how many turbines we want for our site. It will
make sense because the number of turbines we select will agree with the range NREL gives us,
plus the number the JEDI program states.
Power Capacity
To understand power capacity, you must understand the equation to figure out the amount
of electricity you are going to produce in a year. This equation is:
turbine size x number of turbines x number of hours in a yearx
capacity factor=total annual electricity generation
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This equation shows you that in general a higher capacity factor will generate more total
electricity. Looking at the bar chart above you can see that sites like Keystone, Wyoming and
West Pueblo have a higher capacity than the others. This is definitely something that needs to be
looked at to understand how this could affect how much electricity we produce in a given year.
Data Analysis Starting with the data Analyzing the Xcel Load Data The creation of the data sheets Results of Wind Resource Analysis Analyzing the Data
Starting with the Data
The National Renewable Energy Laboratory (NREL) provided all of the data files for this
proposal. Each data file, including 157,000+ data points, was based on each site location.
Wind Data
The wind data for each site was originally composed of the NREL location ID, power
density, wind speed, elevation, power capacity, date of each point, 100 meter wind speed, rated
output at 100 meters, and a corrected score for each data point. The same data categories were
consistent with all eight potential locations.
Figure 1 - Original West Pueblo data file.
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Upon looking at all of the data points, we discovered much of the information was not
needed to help with making a decision of wind farm location. Each spreadsheet originally
contains several unneeded columns, including the location ID and elevation. Categories like
these do not change throughout the spreadsheet, and in order to save on file size, we removed
them. Also, we removed the latitude and longitude columns as these provided no assistance in
determining a location.
In the end, the complete list of unnecessary data in each spreadsheet included the removal
of the location ID, latitude and longitude, location name, state, power density, elevation, power
capacity, rated power output, and corrected score. None of these categories would help us to
make a decision of wind farm location. Also, the original file size for each spreadsheet of data
was close to 12 MB, containing over two million individual cells with text. A file of this size
takes a considerable amount of time to load, even on the fastest computers. Taking the extra time
to load a spreadsheet to view data quickly slowed down out productivity, and therefore this
particular data needed to be removed. After removing the categories, the file size was about 4.5
MB, with five-hundred thousand data pointsconsiderably less than our starting point.
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Figure 2 - Condensed East Monument data file.
We did include the date the data point was taken, the wind speed, and the SCORE-lite
power output. This ultimately made using the data much easier than originally anticipated.
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Xcel Load Data
In order to make a proper comparison to the energy demanded by Xcel, the Energy
Company provided a load data file for one year. This file helped to understand the consistency of
power output needed to meet the demand, as well as the amount of energy demanded for each
hour of the day. A chart was helpful in visually seeing the demand move throughout the year.
The average of each point was compared against the load data.
Figure 3 - Xcel Load Data and Average Load chart.
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Results of Analysis: Wind Resources
Average Wind in each location by hour
This chart demonstrates the trend of wind on average each hour for all locations. The
chart shows that Keystone has a very high average wind and Nebraska usually has a very low
average wind speed. This graph tells a lot about the sites and what kinds of wind each are
capable of producing over the life of the farm. Though Keystone has a high wind capacity, it is
not the only thing to take into consideration.
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Wind in each location by season
This chart displays the wind consistency in each location by season. Again, Keystone has
the highest wind output, but the large decrease of wind during the summer is something to take
into consideration. We also looked at consistency in the wind between seasons. Though a
location has high winds, we had to see if this speed stayed the same throughout the year. All of
the locations had a dip in wind speed during the summer, which raises concern of the possible
output of the locations. We must then look at the speed of the wind and the consistency across.
Many of the locations have very similar wind speeds and consistency, so we cannot make a final
location decision at this point.
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Average Output in Each Location by Hour
Using this third chart we were able to get an idea of how much output each location can
produce and at what times. Using this chart we looked for consistency and high output levels
throughout the day. We also considered the times that most people would demand energy, and
the times when a high output may not be necessary. Early in the morning and very late at night
seem to be the times of lower demand, and therefore a lower output at those times is acceptable.
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Average Output in Each Location by Season
Using this chart we were able to see the possible output in each location by season. This
provides a better idea of how each location will meet the demands of Xcel over the course of a
year. We know that the greatest demand will be during the summer when most people will run
their air conditioning units. As with the wind speeds for each location, we observed the
consistency of output throughout the year, ensuring that the output is not eratic.
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Xcel Load Data
Each of the following charts shows the total output of each location based on an average
of each hour of the day thoroughout the year. On the charts, the red line represents the Load Data
provided by Xcel Energy, and the blue line represents the load for the location mentioned in the
title of the chart. The units for the Xcel data are different than the units for each location. These
charts are used to show how the output at each location can meet the consistency demand of Xcel
Energy.
These charts are very useful in determining the possibility of using a particular location
for our wind farm. Since the farm is based on how we can supply the needs to Xcel Energy, we
must know which farms can in fact do that.
Map Key: Xcel Load Data Location Output
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Analyzing the Data
Overall Look
When considering the data, we realized many different outlooks were needed to get a true
evaluation of the correct site to choose. Taking a look at the data as a whole will limit the
effectiveness of the data. It is too hard to fully evaluate the data without drilling it down into
smaller pieces. Such methods of drilling down the data include consolidating the data points to
get a true average for each time of year, looking at trends in the data for each month, season,
quarter, and time of day. Digging deeper into the data helped to find trends for each wind
location, turning the data into useful information.
All the data points individually provided a better idea of each locations strengths and
weaknesses. For example, looking at the wind speed for a particular site can tell about the
realistic possibility of a farm there. The wind speed averages were examined to get a better sense
of how high or low the wind speed is in each location, as well as the consistency of the wind. It
was realized that a too high wind speed would ultimately cause problems for the turbine, where a
low wind speed may not even have enough energy to turn the turbine. Also, time of day for each
wind speed was key in knowing how the location could supply the demand of Xcel Energy.
Even more of a concern after looking at the characteristics of the wind is the amount of
energy output from a turbine. A particular location may have consistent winds throughout the
day, but still produce little energy. Another location may have inconsistent wind throughout the
day, but sufficient winds to produce the necessary amount of energy during the peak load time.
Recognizing all of these facts, we were able to get a good starting point for analysis. We
set a plan of what we wanted to know from the data and determined how to achieve each goal in
the plan. The following information is execution of our plan and the results that came out of our
data analysis.
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Actual Analysis
We started this project with the provided data files for each location, containing
thousands of data points from three years worth of collection. Looking at this data as a whole,
we knew we could not make a decision without doing further investigation. We stated by
viewing the raw data files as they were when we received them. NREL provided all of the data to
help with the finding the right location to build our wind farm. Though each file included
thousands of points, drill down techniques helped to evaluate the data more clearly.
Figure 4 - Original West Pueblo data file.
After evaluating the data, we realized much of the information could be condensed for
easier manipulation and consideration. The only relevant information needed to make further
evaluation included the date and time, wind speed, and the SCORE-lite data points. Also, in
order to reduce the size of the wind file and the number of points, and to easily compare to the
load data from Xcel, the average of each location was found to consolidate all three years of data
collection. This was the foundation built for finding answers within all of the data points.
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Figure 5 - Condensed East Monument data file.
Consolidating a single file to remove unnecessary data points took approximately ten to
fifteen minutes of non-stop commands. In order to speed up this process and cut down on wasted
time, we used Excels Macro tool, designing a system to perform the same actions on each of the
data files. This Macro helped save many hours of work, allowing our team to continue with
finding a wind farm location. All of the condensed files contain the average wind speed and
SCORE-lite for each location, however the points are organized in a way that allows for easier
average calculation. This helped us to move to our next stage in the plan of analyzing the data.
After consolidating each data file, we were able to import each condensed file into
Microsoft Access where it was much easier to develop queries to meet our research needs. Excel
provided many tools for data analysis, but Access helped to truly consolidate all of the data
points for ease of use. This tool allowed for easier data manipulation to get the answers we were
looking for from the data files.
One problem we came across when using Excel was that the program would not allow a
straight copy of a filtered column into another spreadsheet. We were able to utilize the query tool
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of Access to bypass this problem in Excel. This query was used to pull out only the data from
each hour for each location. From this, we could copy the data from Access into Excel in order to
compare it against Excels load data.
Figure 6 - Access query design to find load data at each hour, and query result (overlay).
Using Access, we were able to import all of the condensed data files. In order to bypass
the previously-stated problem found in Excel, we created this query to filter through the Each
Hr column heading and return only results containing an hour value. This was achieved by
setting the query criteria for Each Hr to an * which would return a result only if text was
found. From this query result, we could copy the data back into Excel. We repeated this same
process for all of the potential wind farm locations. The following image shows the outcome of
this task.
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Figure 7 - Load data from Xcel with load data for each location.
After creating a spreadsheet containing all of the load data for the year, we were able to
create another query to average out the load of each location and the Xcel demand in order to
create charts of the data to compare location load by Xcel demand.
Figure 8 - Query to find average load for each location, and query results (overlay).
All of this information was copied back into Excel once again and used for more tasks
within the program. This helped to create a spreadsheet with only twenty-four rows of data rather
than the original data sheet with close to nine-thousand rows.
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Figure 9 - Load data by hour for one day.
From this table, we were able to make charts comparing each locations load data against
Xcels demand. This helped to get a better idea of which location could meet the demand of Xcel
Energy. Each chart gives a graphical representation of the load for each location on average for
each hour of the day.
Figure 10 - Example of a chart created from the load table.
A necessary component in determining the wind farm location is to understand how the
location can meet needs during particular times of a day or year. In addition to the load data by
hour previously calculated, we looked at the output capacity and wind speed for each season of
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output and wind speed. Also, the ideal site would provide the best output and wind speed during
the demanded times of the day or year.
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Final Site Selection
Final Site Selection First Site Elimination Breakdown of strengths and weaknesses Why we chose our site Determined wind farm size
Choosing the Location
Upon taking into consideration many different factors, we came to the conclusion that
only one site could hold our wind farm. Although all eight sites have their strengths and
weaknesses, we determined that the West Pueblo site would be the best location to build a wind
farm for energy production. This section will reveal our findings and our reasons for choosing
West Pueblo as the only location to build our wind farm.
Primary Eliminations
From the very beginning, we decided that the two out-of-state locations, Nebraska and
Wyoming, would already be eliminated with the understanding we wanted to keep this farm
within the state of Colorado. We continued to look at both sites and analyze them throughout our
decision process in order to have further confirmation that our final site selection was the best
choice.
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Strengths and Weaknesses
The following is a table applying values to each of the locations for particular categories
that we observed through our research. The rated values are on a scale from 0-10, with 10 being
the best possible score in a single category.
Category
East
Monument Keystone
Kit
Carson Lamar Nebraska Peetz
West
Pueblo Wyoming
In State 10 10 10 10 0 10 10 0
Distance to
Transmission10 9 7 7 4 5 6 2
Distance to
Access Roads10 10 4 9 8 5 10 8
Quality of
Terrain9 2 7 9 7 8 9 8
Community
Support8 2 10 10 0 7 10 0
Surrounding
Area9 3 7 7 6 7 9 6
Ease of
Transport8 0 7 10 7 7 10 8
Ease of
Access10 2 7 10 7 7 10 8
Maximum
Output6 10 8 9 6 6 9 9
Output
Consistency8 4 8 6 9 9 4 3
Summer
Output 2 5 5 10 2 2 5 6
Maximum
Wind Speed5 10 6 6 6 6 8 8
Average
Wind Speed5 10 6 5 6 6 8 8
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Peak-Time
Output
2 10 2 2 3 4 8 8
Overall
Quality of
Weather
7 0 7 8 5 6 8 6
Total 109 87 101 118 76 95 124 88
From this table, the numbered ratings clearly indicate that West Pueblo is the best overall
site to build our wind farm.
Reasons for Choosing West Pueblo
After reviewing the table of strengths and weaknesses, some categories stuck out most of
all. The lowest ratings came from distance to transmission, output consistency, and summer
output. We compared each of these categories to the other sites and realized that all of them were
about the same in terms of ratings, and therefore these three lower ratings did not pose much of a
threat to West Pueblo. Our site has a considerable distance to the transmission lines, but we felt
the extra cost added to construction would be outweighed by the benefits of overall output.
The output consistency seemed to be a problem with West Pueblo, but we looked deeper
into the output chart created.
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This chart shows somewhat of an irregular consistency throughout an average day, but
the thing we liked most about this location was the ability to have a high output even at its lowest
point. The output for West Pueblo does descrease during the night, but this output on average is
will above 10.0 kW, allowing the site to continually achieve Xcels demand.
The final weakness of West Pueblo turned out not to be a weakness at all. When
compared to all of the other sites, we realized that all locations have a decrease in output during
the summer months. The strength of West Pueblo in this regard was its ability to maintain an
output higher than the majority of the other sites. The output during the summer months is still
very high, producing more than 6 MW on average.
The strengths of West Pueblo are what really sold us in our decision. In all of the other
categories West Pueblo scored an eight or higher. Some of the primary factors in our decision
were West Pueblos high marks in the NIMBY factor. West Pueblo is in a location that really has
no obstuctions for the surrounding aread. The location is out in the open, and not on a farm or
near a population center. As a result, the number of citizens affected by the wind farm would
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greatly be minimized. Any and all communities around the West Pueblo location are in great
support of utilizing renewable energy sources. We spoke with a commissioner in Pueblo who
said he has seen success with wind farms throughout Colorado and neighboring population
centers. He said that gathered information shows that a wind farm would be profitable and a
good idea for the community.
West Pueblos terrain type was a huge influence in deciding this location. It is very flat,
allowing for more wind and easier access for delivery, construction, and maintenance. The trucks
delivering each turbine will not have a difficult time accessing the location. The site it located
relatively close to the Interstate 25, allowing for faster transport, and ultimately faster constrction
time.
The wind speed of West Pueblo was also a great influencing factor in determining this as
the site to build our wind farm. When compared against the other possible sites, West Pueblo had
the third highest average wind output by hour throughout a day. The benefit of West Pueblos
place behind Keystone and Wyoming was that the average was not too high. The cutout speed of
a turbine would mean the turbine would not function for the majority of the time because the
wind speeds are well in excess of the cutout speed. West Pueblo caters to the ideal efficiency of
our turbine, allowing the turbine to operate as much time as possible.
The weather in West Pueblo seems to always remain very consistent. As opposed to other
locations, West Pueblo does not have extreme winters which would cause blade to ice. Also, a
steady wind blows year-round in West Pueblo, allowing constant energy production. Keystone,
for example, is known for its extreme winters, making it very likely that the turbines will require
a lot of downtime or maintenance if ice builds up on the blades.
Our reason for choosing both Vestas as our tubine company and West Pueblo as our site
lies greatly in knowledge that Vestas is building a plant for turbine production in Pueblo,
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Colorado. Many of the other turbine companies are not even located in Colorado, but Vestas
presence in Pueblo, and other cities in Colorado, helped to influce our decision in choosing West
Pueblo for our wind farm. Having our turbine manufacturer located only miles away will help
cut down on transportation costs.
Wind Farm Size
Our determined wind farm size is 105 MW, comprised of 35 three-megawatt Vestas
Turbines. We determined this size based on a few different factors. The first of these factors is
West Pueblos maximum capacity of 35-40 turbines. We calculated the costs of producing 36-40
turbines and determined that an increase in turbines would actually cost more money than we
would receive over the acquisition period. Building a farm with 35 turbines will ultimately allow
us to meet Xcels demand over our agreed time period. The capacity factor in Pueblo is the third
highest, behing Keystone and Wyoming. Having a high capacity factor is critical in choosing a
site for a wind farm. Since Wyoming was already eliminated, West Pueblo is second only to
Keystone. Based on other rating factors, however, Keystone will not provide the best site for a
wind farm.
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When it came to picking a wind turbine for our wind farm, no major factor went
overseen. Cost and efficiency are the two main focuses our team focused on to choose the most
appropriate and profit maximizing turbine. Three brands and six models were narrowed down
quickly by simply evaluating market share, manufacturing facility location (shipping), power
outputs by model, costs, and reliability by brand. We then decided to evaluate Vestas, General
Electric, and Siemens for an in-depth comparison on what turbine to ultimately choose for our
wind farm. -Figure 3-1 shows market share of wind turbines in the United States
Figure 13 - A Pie chart displaying annual installed capacities of wind turbines.
Vestas
1. The leading wind turbine manufacturer is Vestas with a 20 percent market worldwide and 3rd
largest In the United States with over 39,000 wind turbines installed, they were a very
practical choice with world class leading technology. The two models most appropriate for
Excel Energys request were their 2MW and 3MW models.
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3 MW Vestas Turbine
The 3 MW Vestas turbine was chosen because of its reliability and efficiency it can bring
to our wind site. Vestas manufactures this low/med wind speed turbine here in Colorado making
it a great option for our group. It comes equipped with great rotor-to-generator ratio, meaning
increased reliability and even more important efficiency. It is an all weather machine that can
take high and low temperatures making it ideal for Colorado. The cooling system on this is
above average enabling it to be installed all the way up to almost 5,000 feet. So having many
sites above 5,000 feet make this turbine applicable only at a few sites. Nonetheless with a
company specializing in blade design, nacelle design, cooling systems, and load-optimized
operation resulting in a world class wind turbine for altitudes below 5,000 feet.-Figure 3-2 shows
the specifications of the 3 MW turbines as provided by Vestas
Figure 14 - Vestas power curve.
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V80-2.0MW Vestas Turbine
The 2MW Vestas model is smaller older more seasoned model that carries a reputation of
reliability and high ROI. Since, after all, we are a business trying to make money and be
efficient, a wind turbine as small as 2MW could be ideal for us and more importantly for Excel
energy. This turbine specializes in reliability, quick maintenance, and fast easy shipping to sites.
It executes this by shielding all moving parts of the turbine. This model carries an option of a 67
meter tower or an 80 meter tower however they both have identical 39 meter blades. These
blades are made out of glass fibers in an epoxy resin to withstand harsh weather Colorado might
bring to these turbines. This turbine can withstand temperatures as low as -30 degrees Celsius,
allowing us to put it anywhere in Colorado. It also has a minimum 20 year operating cycle in
which they guarantee if you choose to go with their AOM plan, also known as Active output
management. This program adds the added security of a maintenance plan, online turbine
monitoring, troubleshooting, optimization, and special insurance scheme. So with all the benefits
of the 2 MW turbine, the only obvious downside is the output of only 2,000 Kwh.-The power
schedule as provided by Vestas is shown in figure 3-3 and 3-4.
Figure 15
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Figure 16
General Electric
2. General Electric is a very sophisticated company making products across many industries
including Wind power, which they produce many wind turbines including over 12,000
2.5MW installed to date. They were our second choice from companies to narrow it down to
and a strong contender in the Wind power industry.
GE 1.5MWxle Turbine
The 1.5xle MW turbine from General Electric is a low speed high efficiency turbine with
high reliability. What makes this turbine different is that it actually has a low speed boost of
energy that is created through a larger than normal 82.5 meter rotors diameter and a hub height
of 80 meters. This would be helpful for the summer months when wind is more calm and steady
and energy demand is high. However the drawback is that the cut-out wind speed is 20m/sec.
This is a rare occasion in some wind sites making this not much of a problem. This turbine can
go to temperatures as low as -30C and as high as 40C, making it in the range of our wind sites.
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So with 12,000 of these turbines in operation today, this makes for one of the most widely used,
easy to maintain, and reliable(97%) wind turbine on the U.S. market. The only drawback is that
it makes a low 1.5MW of rated power. But with GE having an overwhelming market share in the
U.S. market, it makes for a great potential wind turbine.
Figure 17 - Display of important specifications.
GE 2.5xl
With a 100 meter rotor diameter and a very high 85% installation availability, this wind
turbine is suitable for lower speed and harder to install sites. Being in Colorado this is a very
important benefit to this turbine produced by General Electric. This specific model that gives it
the benefit over many other models is the fact it comes with a permanent magnet generator
versus the traditional copper coil. This system works much more efficient at partial load or lower
speeds, making it perfect more the summer season for most potential wind sites. Another benefit
to this system is that it is available I hub heights of 75, 85, or even 100 meters. This could help
for certain restrictions on hub heights or even to cut cost with a lower tower. The maintenance
interval is an automated 12 months lubrication system making this turbine possibly the most
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efficient in the whole bunch. Its no wonder why GE has almost half the total U.S. market share
with extremely high efficient turbines being produced. So with 4 years and over 500,000 hours
run time, the 2.5xl wind turbine is possibly the most efficient and reliable wind turbine to date.
Figure 18 - 2.5xl specs as shown by GE.
Figure 19 - Features as shown by GE.
Siemens
3. The third and final pick of our in-depth comparison was Siemens because of the late
emergence and power they possess in the Wind power industry. With more than 25 years
experience in the wind industry, they have gown to be North Americas third largest supplier
of wind power and have recently been installing 565MW of energy in California, Oklahoma,
Washington, and Wyoming.
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Siemens 2.3
The Siemens 2.3 model is a highly experimental model with only 633 installed
worldwide. This model is below average for a good rated wind speed, but has a very
sophisticated blade system. There are no weak points or open areas on the blades where ice and
lightning could potentially break the multi-million dollar equipment. Considering all the
competitors wind turbines are probably just as safe against ice and lightning, I do not know if
this really a valid advantage. The new wind turbine plant for Siemens will be located in Salt
City, Kansas. This is very close yet still much farther away than the very close Colorado native
Vestas plant. Overall this is a l below average wind turbine with a price about the same as all the
others at about 2,300,000.-Figure 3-8 sand 3-9 show Siemens 2.3 specs as shown by Vestas
Figure 20
Figure 21
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Siemens 3.6
The Siemens 3.6MW turbine is the biggest power generator of the whole group and
therefore is also the most expensive at about 4 million dollars. This turbine is available for on
and off shore applications with a heavy favor for off shore. The reason being is you typically get
a lot more wind off shore so if this is to be used on an application in Colorado it needs to be a
high wind site. The blades are made with the standard fiberglass epoxy resin formula making
them just as strong as all the other manufacturers. An advantage this system has is a long range
remote control to use the turbine and make adjustments. But with Siemens there are very few
examples of this product out making it an unreliable source to go with. Having profitability and a
great answer to excel energy being our prime concern, this turbine falls short not knowing
exactly how well it will work. Siemens is a great manufacturer for some, but for what our team is
trying to accomplish they dont hold up with Vestas and General Electric.
Figure 22 - Siemens 3.6 specs as provided by Siemens.
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Vestas has come out on top because of the competitive nature they had with General
Electric and the rest of the wind energy market. Our group knew that both brands had the best
models that were to fit our criteria of the best wind Turbine. The 3MW Vestas turbine had a lot
of attributes that made it win the comparison test however. The biggest attribute was the fact that
Vestas is building a brand new manufacturing plant in both Brighton and pueblo, Colorado. This
made the cost of shipping millions of dollars less making it logical to choose Vestas. Another
great attribute was the big 3 Mega Watt output the turbine has to offer. Our group thinks that
Europe is a great model to follow because they have been in the wind energy market for so much
longer than us. So because we noticed a trend there to go bigger and bigger and it was yielding
big profits, we wanted to follow that experienced model. I feel like we are a little behind here in
America with smaller turbines that the overhead costs associated with installing turbines shows
that for ROI this 3MW turbine built here in native Colorado cannot be beat. Vestas has a superior
product and a great maintenance plan to go along with it, thus making it our turbine of choice for
our wind farm.
Maintenance Plan
A great attribute about Vestas is the maintenance plan they offer for their products
worldwide. They have 24 hours seven days a week maintenance and security for our wind farm.
This is the best option for us considering they have trained professionals on call at all hours of
the day. Financially we benefit from this because we will have optimal energy being created
through careful inspections by Vestas themselves. They are known to keep down time on
turbines to a minimum maximizing our utility. Along with their maintenance they offer a long
term asset management service letting you have different option along the life of the investment
to increase our revenues. This is the best plan we found and the best fit for our site, so we made
this an absolute program to go with.
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Construction schedule (January1, 2010-October 31, 2011)1
Access roads
Constructionis to begin January 1, 2010 with access roads being the first priority. All
roads are expected to take about 12 weeks to finish. Included in these roads will be turnarounds
for the large loads and passing lanes for trucks coming in and out. They will be hard wide dirt
roads to accommodate all possible loads into the site. It is expected to have about 30 personnel
on site that will be needed for this job to end in a timely manner. This phase will end around no
later than February 28, 2010.
Foundations
Power Lines and foundations will be done at the same time starting February 1, 2010 to get
foundations poured and power lines put in. We believe if these are done in the same step power
lines will be appropriately organized with the foundations/wind turbines. The reason we are
getting a jump start on these is to brace ourselves for when the towers start arriving from Vestas.
The nearby Vestas plant in Pueblo will not be operational until March 2010. Since these
1 These are just estimates that we understand can have shorter or longer finish times than stated. It is important toremember that we will adapt to kinks in the construction schedule appropriately to the specific concern.
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foundations and power lines can take a while to build, we as a group have found it beneficial to
start a few months before the towers, turbines, and blades all arrive. All 35 foundations should
take about 35 weeks making us pump out 1 foundation every week. These foundations are
relatively big, because we are going with the 3MW Vestas turbine. This leads us into the power
lines being constructed.
Power Lines
We need 12 miles of power lines to the grid so these will start January 1, 2010 to get
power to the grid as timely as possible. We expect the full operation of the lines to take about 48
working days or at 6 days a week, 8 weeks. We are expected to see about a quarter mile a day
progress according to a Colorado power company named Manta. Another power line team will
start the foundation to foundation lines February 1, 2010 to keep up with turbines construction
and potential problems with connecting lines through foundations. These inner lines through the
site will be built following the schedule of the foundations and in accordance with its progress to
build the site most efficiently.
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Power Purchase Agreement
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WIND ENERGY PURCHASE AGREEMENT
BETWEEN
PUBLIC SERVICE COMPANY OF COLORADO
AND
VENTUS, INC.
DECEMBER 11, 2009
The table below displays the planned output of West Pueblo at given intervals.
Hour Day Week Month Year
Generation (kWh) 37,800 907,200 6,350,400 27,216,000 331,128,000
Length of Contract
According to the RFP presented by Xcel Energy, the contract term for purchase of
electricity is between five and 25 years. For our wind farm, we decided to make the contract
length 20 years. We feel that in this time, the needs to Xcel will be met, and we as a company
will find the best profit during this time.
Price of Power MWh
We decided that the best price to charge for power per MWh is $94.90, or $0.0949 per
kWh. We arrived at this price through trying to get to our target of 15% ROI, and staying under
$100 per MWh. The price may seem high, but for the quality product Xcel is receiving, our price
per MWh is worth the higher expense. We determined that we will keep our price constant
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