OPIM Final Project External

8/7/2019 OPIM Final Project External

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Proposal for

Wind Farm D

Table of Contents

Executive Summary.........................................................................................................................2

Introduction......................................................................................................................................3

Site Selection...................................................................................................................................5


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Public Service Company of Colorado

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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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.



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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.



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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


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




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Nebraska


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




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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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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

Documents

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