Alternative Energy Feasibility Study for The Pettit National Ice Center

Transcription

1 Senior Design Project Alternative Energy Feasibility Study for The Pettit National Ice Center Group 2 Jason T Krajewski Kimberly Jonet John Noegel University of Wisconsin Milwaukee Department of Mechanical Engineering Milwaukee, WI Submitted to: B.A. Price University of Wisconsin Milwaukee Department of Mechanical Engineering Milwaukee, WI May 2, 2002

2 ABSTRACT The following report is a feasibility study for on site energy generation at the Pettit National Ice Center (PNIC) located in West Allis, Wisconsin. The PNIC has high utility bills with an average monthly cost of $22,000 to $25,000. In attempt to reduce high electricity costs, an alternative energy generation system is examined and designed. Four methods including solar power, fuel cells, wind power and gas turbines, are considered. A specific selection criterion is used to determine the feasibility of each system. Based on the selection criteria, wind and gas turbine power generation systems are further examined. An economic analysis of the two systems shows that the cost of electricity per kwh produced by a gas turbine is $ and results in a buyback time of years while the cost of electricity per kwh produced by a wind turbine is $ and results in a buyback time of years. Therefore a gas turbine system is the most feasible alternative energy generation to implement into the PNIC s current system. ii

3 TABLE OF CONTENTS Section page ABSTRACT... TABLE OF CONTENTS... LIST OF FIGURES... LIST OF TABLES... ACKNOWLEDGMENTS... ii iii v vi vii 1. INTRODUCTION ENERGY GENERATION METHODS Introduction Selection Criteria Methods Solar Power Fuel Cells Wind Power Gas Turbines System Selection Summary SYSTEM DESIGN Wind Power Design Weibull Wind Analysis Wind Turbine Selection Gas Turbine Design ECONOMIC ANALYSIS Gas Turbine Economics Wind Turbine Economics CONCLUSIONS AND RECOMMENDATIONS REFERENCES BIBLIOGRAPHY Appendix A Monthly energy consumption at the PNIC Appendix B Weibull Distribution Parametric k Study Appendix C Weibull Distribution Data for k= Appendix D Weibull Distribution for Average Wind Speeds +/-3mph iii

4 Appendix E Vestas Power Curve Data Appendix F Monthly Power Outputs +/-3mph Average Wind Speed Appendix G Saturn 20 Gas Turbine Specifications Appendix H Economic Analysis of Systems iv

5 LIST OF FIGURES Figure Page 1 Global Solar Energy Distribution Energy Generation Efficiency Comparison Wisconsin Wind Map Relative Noise Comparison Chart (AWEA, 2002) Weibull Distribution for k = Weibull Distribution for k = 2.0 ± 3 mph Vestas V kw Power Curve (Vestas, 2002) Monthly Power Output (± 3 mpg) v

6 LIST OF TABLES Table Page 1 System Selection Average Monthly Wind Speeds (mph) for Milwaukee, WI Economics General Assumptions Turbine Economic Results Wind Turbine Economic Results vi

7 ACKNOWLEDGMENTS The design team thanks Jim Gulczynski of the Pettit National Ice Center for his assistance in acquiring energy consumption data for the facility. The design team also acknowledges Carl Siegrist, David Schigoda, and Len Pawlak of We Energies for their aid in energy resources. Finally, the design team acknowledges Professors Andrew Price, Kevin Renken, and John Reisel for their guidance on this project. vii

8 1 1. INTRODUCTION In recent years, problems with traditional energy production have become difficult for the world to ignore. The problems include a limited supply of fossil fuels and uncertain effects on the environment. The rate at which fossil fuels are being consumed is growing annually, while the amount available remains finite. The environmental effects of burning fossil fuels are becoming more visible as numerous studies indicate detrimental climate effects and adverse personal health risks (EIA, 2000). These effects have resulted in political scrutiny and ensuing regulatory legislation for the energy industry. This legislation combined with the growing energy costs creates an economic concern for consumers in all sectors of the energy market. One solution to these problems comes in the form of alternative energy generation. Methods such as wind, hydraulic, solar, and nuclear power generation continue to advance in technology and as a result have experienced increases in production efficiency (EREN, 2001). Also, technologies such as fuel cells and wind turbines are presenting themselves as viable options to traditional methods with the promise of advanced efficiency in the future. Until recently, many alternative energy generation techniques have been used solely in largescale energy production environments. However, many of these methods are now available for smaller scale operations such as individual building systems and even home use. With projected energy consumption bypassing the rate of domestic energy production, and the subsequent cost of energy importing, on-site power generation can no longer be ignored (EIA, 2002). One local facility fighting increasing costs due to high-energy consumption is the Pettit National Ice Center (PNIC). Located in West Allis, Wisconsin, the PNIC is one of the premier ice-skating facilities in the world. It houses a 400-meter speed skating oval, a 450-meter running

9 2 track, and two international size ice rinks. Due to the size and nature of its operation, the PNIC has high monthly energy bills in terms of both electricity and heating/cooling. Average electric and heating costs range from $22,000 - $25,000 and $6,000 - $9,000 respectively (Appendix A). Since the entire electrical supply for the ice center is delivered from the local power grid, the PNIC views on-site generation as a possible solution to reducing its energy costs. The objective of this study is to examine the feasibility of four electrical generation techniques. The methods to be investigated include solar photovoltaic, gas turbines, wind power, and fuel cells. Each method will be rated using predetermined selection criteria to determine the two most feasible options. A life-cycle cost analysis of the two best systems will be used to determine the most feasible alternative energy generation source for the PNIC. Although some of these methods are attractive in terms of electrical cost reduction, they all provide a benefit in demonstrating alternative energy generation to the public. Being an Olympic training facility, the PNIC is both a popular local and tourist attraction. As a result, the PNIC could provide an excellent demonstration site for alternative energy generation. The remainder of this study examines each of the alternative generation methods and discusses the advantages and disadvantages of applying these methods to the PNIC. The four energy generation methods and selection criteria for the two most feasible options is discussed in Section 2. The two most feasible options are further examined in Section 3, with an economic comparison between them given in Section 4. Finally, conclusions and recommendations are given in Section ENERGY GENERATION METHODS 2.1 Introduction In order to determine the feasibility of an alternative energy generation system, four primary methods are examined. These methods include solar power, fuel cells, wind power and gas

10 3 turbines. Information about each of the methods is given in Section 2.3. The attributes of the four generation methods are compared using selection criteria to determine the two most feasible options. Seven specific criterion are selected as the most important aspects for determining the feasibility of an alternative generation method. These criteria are given in Section 2.2. The methods are rated using a numbered scale in each of the selected areas. The sum total of each method is computed and the methods with the highest total are selected as the two most feasible methods. A breakdown of the selection criteria can be seen in Section Selection Criteria The four alternative energy generation systems are compared using the following selection criteria: 1. Aesthetics The expected visual appeal of the system. 2. Noise The noise pollution potential of the system. 3. Space The amount of space the system would require. 4. Annual Maintenance The cost of annual maintenance. 5. Initial Cost The initial investment required to implement the system. 6. Lifetime The life expectancy of the system. 7. Energy Cost The cost to produce the energy, taking into account any fuel costs. The aesthetics and noise criterion are chosen because of possible social implications since the PNIC is highly visible and located near a residential area. The space consumption criterion is chosen as a means to determine the spatial feasibility of the system. The annual maintenance, initial cost, and energy costs are chosen to provide an economic basis for comparison. Finally, the life expectancy criterion is selected to provide not only an assisting economic basis but also a measure of the projected reliability of the generation method.

11 4 The systems are independently rated in each of the categories on a scale of 1 to 5. A value of 1 represents a least favorable option and a value of 5 represents a most favorable option. The highest total for each of the four alternative energy systems is then used to determine the two most feasible options. 2.3 Methods Four alternative energy generation methods are evaluated. The methods consist of solar power, fuel cells, wind power, and gas turbines Solar Power Since the ability to convert sunlight into electrical energy was discovered, extensive research has gone into advancing this capability. In 1999, 76 trillion BTUs of energy were produced by solar power, which is equivalent to about 13 million barrels of oil or 3.4 million tons of coal (EIA, 2001). This corresponds to 0.1% of the energy produced by the U.S. This was in contrast with the 80% being generated by fossil fuel consumption (EIA, 2001). Although the amount produced by solar power is a small portion of the overall amount, it has spawned a multi-billion dollar a year business. With a projected yearly growth of 10 15% by 2010, increased availability will cause the price of solar energy to decrease. (Siemans Solar, 2001) There are two main categories of technologies that harness solar energy solar thermal and photo-electrics. Solar thermal focuses on capturing and transporting thermal energy from the sun. These systems have several applications including steam generator preheating, water heating, and passive building heating and cooling. The primary methods of electricity generation using solar thermal technology are concentrating solar power systems. These systems consist of lenses that focus the solar energy onto a receiving surface. The receiver absorbs the energy and converts it to

12 5 heat. The heat is transferred by a working fluid to a steam turbine generator where steam expansion in a turbine produces electricity. Using the solar energy as a pre-heater increases the overall temperature of the fluid entering the boiler, thereby reducing the required boiler energy input, i.e., coal or gas. This increases the system efficiency and reduces the overall cost of electricity generation. These systems are utilized in larger scale operations (>10MW) where steam generators are already employed as the main power station (DOE-EREN, 2001). The second type of solar energy system, photovoltaic, makes use of the photoelectric effect. The photoelectric effect is caused by a flux of photons (sunlight) striking a charged plate. Electrons are released and directed onto another surface, thus creating a current. This current can be utilized either as a direct current (DC) or may be transformed into an alternating current (AC). This method of solar energy generation lends itself to a variety of applications ranging in size from hand-held calculators to large commercial buildings and villages. The use of photovoltaic energy presents a variety of advantages including an unlimited and free fuel, and non-polluting energy generation. Since there is no combustion in the process, there is no emission of carbon monoxide, hydrocarbons, or nitrogen oxides. Another valuable aspect of solar generation systems is their long equipment lifetimes and easy maintenance. A solar system can last up to 25 years or longer with no substantial replacement necessary (BP Solar, 2002). The minimum number of moveable parts leads to low maintenance costs, and low noise levels. Several disadvantages exist in the use of solar energy systems including cost and space requirements. The most important of these is cost. Although solar cell material and technology have advanced since their creation, the cost can be prohibitively expensive. On average, a complete system, including necessary components such as storage batteries, inverters, and wiring, will cost between $2 - $30 per Watt (Repp-Crest, 2002). This range may not be acceptable for many

13 6 larger scale operations where the return on the system investment may never be realized during the lifetime of the equipment. This is the case for the PNIC where the estimated system cost is between $7 and $30 million before state and national incentives for alternative energy generation. Another disadvantage is the required space. Since solar modules must be large enough to gather as much light as possible, they tend to lend themselves to applications where plenty of space is available. There has been a trend in recent years to use available roofing space on buildings to accommodate solar arrays. In many cases this has proved a viable option. The effect of location can be a major disadvantage of a solar system. Due to the amount of energy being closely related to the intensity and directness of the sunlight, certain locations are not suitable for solar systems. Figure 1 shows a general sunlight intensity map with respect to global location. Figure 1 Global Solar Energy Distribution (BP Solar, 2002). As seen in Figure 1, the Midwest region of the United States has a fairly high solar energy density rating and may be conducive to solar energy generation. These intensity ratings do not

14 7 include microclimates where frequent cloud cover may take place. Areas where sunlight is obscured usually are not conducive to solar power generation Fuel Cells Fuel cells combine hydrogen and oxygen from the air to produce electricity and heat. This process is virtually pollution free and highly reliable. However, most fuel cells use natural gas to produce Hydrogen and since there is currently no reliable source of Hydrogen, the costs of energy from this method is high. It also is a highly efficient means of obtaining energy because the fuel is converted directly into electricity. (Fuel Cells, 2000) Basic fuel cell operation is the same, but the constituent materials may vary. Fuel cells consist of an electrolyte sandwiched between a negatively charged cathode and a positively charged anode. When hydrogen is introduced to the anodic side of the fuel cell, a coating on the anode separates the electrons and protons of the hydrogen atom. Protons are allowed to pass through the electrolyte while electrons are made to flow through a circuit. This flow of electrons produces a current that is utilized for power. Oxygen, from the air, is supplied to the cathodic side of the system where a special coating (usually platinum) enables oxygen protons to combine with the electrons and produce pure water and heat. One advantage of fuel cells is their high reliability and constant power production. Fuel cells can achieve a reliability of 99.99% when connected to a power grid (UTC, 2002). They also can maintain a constant power output as long as fuel is supplied to the system. Fuel cells also have high efficiencies. A comparison of the different efficiencies of various energy generation methods is given in Figure 2. Compared to gas electric systems (20%), micro turbines (23%), and diesel electric (31%), fuel cell systems can convert 40% percent of the supplied fuel to electricity. This amount can be increased to 80% if the waste heat is utilized in a heat

15 recovery/cogeneration process (UTC, 2002). These high efficiencies reduce fuel cost and preserve natural fuel resources. 8 Energy Generation Effeciencies 100 Gas Electric Effiency (%) Energy Generation Method Micro Turbines Diesel Electric Fuel Cell Fuel Cell w/heat Recovery Figure 2 Energy Generation Efficiency Comparison (UTC Fuel Cells, 2002). Although fuel cells provide many advantages, they also have several disadvantages including system cost. The average cost of a fuel cell is nearly $3,000 per kilowatt of capacity and does not include fuel and system subcomponent cost. An initial gross estimate of the fuel cell cost for use at the PNIC is greater than 3 million dollars not including system subcomponents. (Breakthrough Technologies Institute, 2000) Wind Power One form of alternative energy generation available to the PNIC is the harnessing of wind energy. Wind is renewable, nonpolluting, and abundant in the mid-latitudes making West Allis a viable candidate. Continuing developments in the wind harnessing process have reduced the cost of producing wind energy such that it is expected to be one of the least-expensive forms of new electrical generation in the 21 st century (Thresher and Hock, 1994). Furthermore, wind energy could supply approximately 20% of this nation s electricity (AWEA, 1999).

16 9 Wind is converted into energy through the use of a wind turbine. A wind turbine transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. The most common type of wind turbine is the horizontal-axis machine, consisting of a rotor, a drive train and generator, and a tower, and has power ratings of up to 1.65 MW. However, maximum power ratings are dependent on the wind speeds of the location in which a turbine is installed. In general, utility-scale wind power plants recommend a minimum average wind speed of 13 mph to provide sufficient energy generation (AWEA, 1999). A wind map of Wisconsin is given in Figure 3 and shows that the average wind speed near the PNIC is 15.0 to 15.5 mph. This average is based on one year of data collected at a height of 60 meters above ground, which is a typical wind turbine height (WI Dept. of Admin, 2002). Therefore, based on average wind speeds alone, the possibility of harnessing wind power as an alternative energy source is a viable option for the PNIC. However, due to the fact that there are only twelve tower locations throughout the entire state of Wisconsin, more data should be collected near the PNIC in order to determine the actual average wind speeds.

17 10 Figure 3 Wisconsin Wind Map (WI Dept of Admin., 2002) One factor affecting most projects is the cost of installation and the resulting savings associated with the project. Average costs for the energy generated by wind turbines is as low at 4 cents per kilowatt-hour (AWEA, 1999). The cost of installing a wind turbine may be reduced through government funding. In the past, production tax credit (PTC) has been available for the harnessing of wind energy.

18 11 Other aspects of wind turbines to be considered are aesthetics and noise. Although some may consider a wind turbine located near the PNIC to be visually unappealing, the demonstration value that could be achieved by installing a widely visible renewable energy resource may be beneficial to the organization s public image. In the past, noise was also an issue with several wind turbine designs. However, developments have reduced noise levels to the point that a wind turbine located 250 meters (0.16 miles) from a home is no noisier than a kitchen refrigerator (AWEA, 1999). Figure 4 shows the relative noise production of various sources including a wind turbine, which is fairly low at only 45 decibels. Figure 4 Relative Noise Comparison Chart (AWEA, 2002). Finally, wind energy has several important advantages and disadvantages to be considered. First, wind is renewable and nonpolluting, making it an energy generation source that does not harm the environment. Wind turbines are reliable and said to be down for maintenance only about 2% of the time (Wisconsin Engineer Journal, 1999). However, wind turbines only generate energy when the wind blows, resulting in unpredictable energy production Gas Turbines

19 12 Gas turbines are separated into three major categories, micro, mini, and small-scale. They all operate under the same principle and are readily adaptable to gas or liquid fuels. Fuel and air are injected into a premix chamber, which then flow into a combustion chamber where the mixture is ignited. The combustion reaction is forced through turbine blades, which turn the generator producing the electricity. The combustion process is efficient and clean. The turbines are typically air-cooled by transferring air along the outside of the liner (Valenti, 1996). Waste heat from the combustion can then be utilized. For the PNIC, the waste heat is a desired benefit due to the year round heating demands of the facility. For the size of this project, true micro-gas turbines, rated at less than 60 kw, are not feasible and true mini-turbines, rated less than 1 MW, are too experimental (Schigoda, 2002). Micro-gas turbines typically have a life expectancy of only a few years, with a one-year warranty, and are highly unreliable with start up failures of greater than 1 per month (Schigoda, 2002). It would require nearly twenty micro-gas turbines to power the facility. Mini-gas turbines are still experimental, with the first projected units to be constructed in two to three years (Schigoda, 2002) leaving the option of a one or two megawatt turbine. A one-megawatt turbine would supply the energy needs of the PNIC most of the time with some minimal demands on the power grid at peak usage, and have the benefit of energy buyback the rest of the time (Pawlak, 2002). With an average power consumption of 0.83 MW, the PNIC would likely receive credit from We Energies during most of the year and be eligible for a cost savings for consumption reduction during on peak demand. A larger two-megawatt plant would cover all the power needs for the PNIC and would offer a constant power supply to the power grid with increased rates for selling energy due to a large excess supply.

20 System Selection To select the most feasible alternative generation method, each of the four systems is rated in seven categories. The selection criterion consists of aesthetics, noise, space consumption, annual maintenance, initial cost, life expectancy, and total energy cost. In rating the systems, the design team attempted to use quantifiable data when possible. This method is used in the lifetime, energy cost, initial cost and annual maintenance categories. In the area of aesthetics, the design team is forced to use a subjective rating to establish a value. Table 1 lists the values assigned to each of the alternative energy generation systems. Table 1 System Selection Wind Power Solar Power Fuel Cells Gas Turbine Aesthetics Noise Space Annual Maint Initial Cost Lifetime Energy Cost TOTAL As can be seen from the table, wind power and gas turbines are the most favorable alternative energy generation methods. These two systems are selected to continue on to the design and life-cycle cost analysis to determine the most feasible option.

21 Summary Four energy generation methods, wind power, fuel cells, solar power, and gas turbines, are examined and compared on the basis of aesthetics, noise, space consumption, annual maintenance, initial cost, life expectancy, and total energy cost. The methods are assigned numerical values in each of the categories and individual totals are computed. Based on these totals it is determined that wind power and gas turbines are the two most feasible alternative energy generation methods.

22 15 3. SYSTEM DESIGN Upon selection of the two most feasible methods, the design team initiates a design of each system. The design of a wind-powered system is found in section 3.1 and the design of the gas turbine is found in section Wind Power Design The following sections pertaining to the design of a wind power system for the PNIC consist of a Weibull distribution of the average monthly wind speeds, the power curve for the selected wind turbine and the anticipated energy supply per month and year for a wind turbine system Weibull Wind Analysis The first step in determining the amount of energy that could be harnessed by a wind turbine located near the PNIC is to obtain the average wind speed data for West Allis, WI. Table 2 lists the average monthly wind speeds in miles per hour for Milwaukee, WI from 1940 to 1993 (NWS, 2002). Table 2 Average Monthly Wind Speeds (mph) for Milwaukee, WI Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual The above average wind speed information does not specify the height at which the data is collected. Typically, when obtaining wind data for use in a feasibility study for wind turbines, the wind data should be collected at the average turbine height of 60 meters. Since this data is unavailable, data from the National Weather Service is also noted for the cities of Des Moines and Sioux City, IA, which because of the accuracy of the wind data for these two cities will be used as a

23 16 control variable in this study. The average wind data for these two cities is compared to the average monthly wind data available on the Iowa Energy Center website that has been measured at a height of 60 meters at several measurement sites across the state. On average, the data from the National Weather Service is found to be 3 mph lower than the Iowa Energy Center data for the two cities named above. Therefore, for this feasibility study, the average wind speed data for Milwaukee, WI will be shown at the National Weather Service data plus 3 mph. If the PNIC decides to look further into the use of a wind turbine, more accurate wind data needs to be collected at the site and the following study should be repeated. The next step in the analysis is to create a Weibull distribution for the average monthly wind speeds. The Weibull distribution takes the average wind speed and separates it into average wind speed intervals that correspond to the number of hours per month that that average wind speed will occur. The probability density function for the Weibull distribution is as follows: ( k 1) u k c k u f ( u) = e ; (k>0, u>0, c>1) (1) c c where k is the shape factor, u is the average wind speed interval, and c is the scale factor (Rohatgi,1994). A parametric study on the shape factor was completed and the results are shown in Appendix B. As k increases, the peak of the curve moves to a higher average wind speed. However, the range of the wind speed over the entire month is reduced with an increasing k value. Since adequate wind data was not available for Milwaukee, WI, the actual k-value for the area near the PNIC is unknown. Therefore, a k-value of 2.0, which is used in the Weibull distribution for the Iowa data, is used for this feasibility study. Figure 5 shows the number of hours per month for the average wind speeds between 0 and 20 mph for a k-value equal to 2.0.

24 17 Hours Ave Wind Speed (m/s) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 5 Weibull Distribution for k=2.0 To illustrate the difference in ±3 mph, Figure 6 shows the Weibull distribution for k=2.0 for the month of January at the average wind speed of ±3 mph Hours Jan Ave Jan Ave + 3m/s Jan Ave - 3m/s Ave Wind Speed (m/s) Figure 6 Weibull Distribution for k=2.0 +/- 3mph

25 Wind Turbine Selection Once the wind data is collected, a specific turbine is selected and the power curve is obtained. The design team selected the Vestas V kw wind turbine. This selection is based on comparative costs among other suppliers and its successful operation by We Energies in Byron, WI. The power curve data is extrapolated from the Vestas website and is illustrated in Figure Power Output (kw) Wind Speed (m/s) Figure 7 Vestas V kw Power Curve (Vestas, 2002) Once the power curve is known, the amount of energy that can be produced per month is calculated. This is done by multiplying the number of hours at a specific average wind speed by the power produced at that same average wind speed. Energy = (Power Avg Wind Speed) x Avg Wind Speed) (2)

26 19 This calculation is done for each month and the total of all months is added together to compute the energy produced by a wind turbine for one year. Figure 8 represents the total power output for each month for one turbine at the average wind speeds ±3 mph. 250,000. Power Output (kwhrs) 200, , , mph Ave +3mph 50, Jan Feb Mar Apr Ma Jun July Aug Sept Oct Nov Dec Month Figure 8 Monthly Power Output (+/- 3mph) The power output for each month is then compared to the actual energy consumption per month for the PNIC in order to determine how many turbines are required to sufficiently decrease the amount of energy purchased by the PNIC. Figure 9 illustrates the difference in installing one wind turbine versus two wind turbines.

27 20 800, , ,000.0 Power (kwh) 500, , , Turbine PNIC Consumption 2 Turbines 200, , Month Figure 9 Power Output versus PNIC Demand Based on the above graph, it is recommended that two wind turbines be installed to reduce the PNIC energy costs. Due a required safety radius around the base of the turbine, the design team proposes placing the two wind turbines inside the Milwaukee Mile racetrack. 3.2 Gas Turbine Design The system selected for the PNIC life-cycle analysis is a 1.2 MW gas turbine. The turbine, model Saturn 20, is produced by Solar Turbines. The turbine also produces klb/hr of steam per hour. When the steam is utilized, the system operates at 70% efficiency. The turbine could be used to replace the existing boilers onsite, additionally reducing the costs by $6000-$9000 per month and allowing the PNIC to go to a more efficient backup boiler. The size of the turbine is approximately x 5 8 x 7 0 allowing for possible installation inside the building. Specifications and drawings of the Saturn 20 gas turbine can be found in Appendix G.

28 21 The design for the system involves specifying an appropriate area for equipment placement, electrical cables, foundation stability, and integration into heating and gas lines. Since the equipment is relatively small in size, it would fit in the same area as the existing boilers. Those boilers would be replaced with the co-generation of the gas turbine and another smaller, more efficient and reliable natural gas boiler. This replacement boiler would have to be sized large enough to maintain the system for short periods of time when the gas turbine undergoes routine maintenance. Additional considerations for design include hold voltage cables to the transformer yard. Due to overproduction of power, excess energy would be sold back to We Energies. Existing connections would have to be left in place for routine outages, but for the majority of the year, the PNIC would be selling energy. The foundation would have to be checked to determine if could handle the load of the generation set in the existing place of the boilers or if a new position or modification of the existing position would be necessary. Finally, integration of the gas lines from the boilers to the gas turbine and output steam to a heat exchanger would be necessary. The natural gas lines should be sized properly to handle the load of the turbine, but would have to be checked for proper size. The output of the steam would be routed into a heat exchanger that exists in the boiler room. The capacity of the co-generation system would be sufficient to handle the necessary loads in most conditions, but an additional boiler would also need to be tied into the system to keep system reliability high.

29 22 4. ECONOMIC ANALYSIS The economic analysis of the wind turbine and gas turbine is performed to determine the most feasible system. The system that saves the most money is chosen as the final system. Some assumptions are made in the calculations. It is assumed that the annual inflation rate is 4% and the number of years in calculation is equal to 20 years. (See Appendix H) The average electrical consumption is computed as the average electrical consumption per month (determined from the PNIC billing statements) multiplied by 12 months Con yr = Con mon x (12) (3) where Con yr is the average yearly electrical consumption at the PNIC, and Con mon is the average monthly consumption at the PNIC. The average cost per year is computed as the average cost per month multiplied by 12 months C yr = C mon x (12) (4) where C yr is the average yearly cost of electricity at the PNIC, and C mon is the average monthly cost of electricity at the PNIC. The cost of electricity is computed by the following equation: C E = Con mon / C yr (5) where C E is the cost of electricity per kilowatt hour. The total present value cost is calculated according to the following equation: ( C P = E ) x((1 + i) i(1 + i) n n + 1) (6) where P is the present worth of the investment, C E is the cost of electricity per kilowatt hour, i is the interest rate over the period, and n is the number of years over which the interest is taken. The total future value cost is calculated according to the following equation:

30 23 n 1 ( CE ) x((1 + i) ) F = i (7) where F is the future worth of the investment. Using the above equations, the following final values are obtained: Table 3 Economics General Assumptions General Assumptions Inflation Rate 4% Interest Rate 6% Number of years = n 20 Loss factor Average cosumption/yr 6,706, kw hr Average cost/yr of elec. 297, $ Cost of Electricity kw Total cost over n (P) 3,411, $ 4.1 Gas Turbine Economics The objective of the gas turbine analysis is to arrive at the savings per year. In doing so, factors such as energy buyback, maintenance, and gas cost are taken into consideration. In order to determine savings, the entire system cost is first computed as: C tot = C sys + C ins + C gas + C main S heat E sell (8) where C net is the total cost of the gas turbine system, C sys is the cost of gas turbine system components, C ins is the cost of gas turbine installation, C gas is the average cost of gas per year, C main is the cost of annual system maintenance, S heat is the average savings in heat expenses per year, and E sell is the amount of energy sold back to utilities per year. The cost per kilowatt hour (kwh) is calculated according to the following:

31 24 C kwh = C net / (E prod x t) (9) where C kwh is the cost of energy per kilowatt hour, E prod is the average energy produced per year, and t is the lifetime of the system. The savings of the gas turbine system was calculated according to the following: S = C cur (C kwh x Con ave ) (10) where S is the total savings of implementing the gas turbine system, C kwh is the cost of the gas turbine system per kilowatt hour, and Con ave is the average annual electric consumption. 4.2 Wind Turbine Economics The total cost of the wind turbine is calculated according to the following equation: C net = C sys + C main + E pur (11) where E pur is the cost of subsequent energy purchases. The cost per kwh is calculated according to: C kwh = C net /( E tur x t) (12) where E tur is the energy production of 2 wind turbines. The savings of the wind system is calculated in the same manner as the gas turbine system. 4.3 Economic Results The results show that the more cost feasible of the two systems is the gas turbine. The system pay back time for the gas turbine is just over 16 years while the wind turbines take twice as long to break even. These costs however do not include special energy buyback programs like Dollars for Power or Power Marketing Incentives, which can save several thousand dollars per year, but are difficult to predict. Another factor that may drastically change the cost of the wind turbines is

32 25 Wisconsin Focus on Energy Now, since changing the initial costs of the wind turbines would decrease the cost per kwh. Table 4 represents the economic results for installing a gas turbine. Table 4 Gas Turbine Economic Results Gas Turbine System Cost 800, Installation Cost 800, Fuel Cost 3.5 $/MBtu Fuel Inflation Rate 2% Maintenance Costs(yr) 5, life of system 20 years Heating Savings/month 6, $ Heating Savings/yr 72, $ Typical Cost per kw for gas 0.04 $ Average kw/hr production 1150 kw Gas Cost/hr 46 $ Average Production/yr kw hr Average Gas Cost/yr 386, $ Energy Sell Back Savings/yr 130, $ Average Heat Saving/yr (P) 825, $ Average Gas Cost/yr (P) 4,431, $ Energy Sell Back Savings/yr (P) 1,502, $ Average Maint. Costs/yr(P) 61, $ Net Cost of System 3,765, $ Cost per kw hr $ Payback Time years Based on the economic analysis for the gas turbine, the cost of electricity per kilowatt-hour is $ with a system payback time of years. Similarly, Table 5 represents the economic results for installing two wind turbines. The economic analysis for the wind turbines results in a cost of electricity per kilowatt-hour of $ with a payback time of years.

33 26 Table 5 Wind Turbine Economic Results Wind Turbine System Cost 1,600, Installation Cost - included Misc. Start up Costs - included Fuel Cost - Fuel Inflation Rate - Maintenance Costs(yr) 6, life of system 20 average production/yr(+3) kw hr Average production X 2 turbines kw hr Average Use by PNIC minus Wind kw hr Cost of bought energy/ yr 124, $ Maintance Costs (P) 68, $ Energy Purchases (P) 1,427, $ Net Cost of Wind Turbine (P) 2,958, $ Cost per kw hr $ Payback Time years Based on the above data, the design team recommends installing a gas turbine at the PNIC in order to reduce the high energy costs.

34 27 5. CONCLUSIONS AND RECOMMENDATIONS In conclusion, the Pettit National Ice Center is experiencing high energy costs so a feasibility study was completed in order to determine the most viable alternative energy generation system. Four alternatives including solar power, fuel cells, wind power and gas turbines were researched. Based on a selection criterion, wind power and gas turbines were selected as the two best options for use at the PNIC. After determining representative equipment, a life-cycle cost analysis was performed on each of the two systems. Both systems were found to be cost beneficial to the PNIC in terms of yearly savings, but the gas turbine system demonstrated a better cost per kwh at $ per kwh and a better payback time of years versus years for the wind turbines. The wind turbines could be more feasible if the initial system cost was reduced. However, the more reliable and cost effective choice is the gas turbine since it will produce more energy and does not depend on a variable energy source. It is recommended that before a system is implemented, wind speeds at the PNIC location should be measured to obtain better local representative data. If the gathered data proves to provide higher power generation, the wind turbine generation scheme may be more feasible than the gas turbine. Although the two systems used in this study are meant to be representative of current market prices, it is recommended that several other wind and gas turbines be evaluated.

35 28 6. REFERENCES American Wind Energy Association, Accessed 2/14/02. BP Solar, Accessed 2/05/02 EIA, Annual Energy Outlook 2002, Accessed 212/02 Energy Efficiency and Renewable Energy Network, Accessed 2/15/02 Energy Information Administration, Accessed 3/20/02 MGE, 1999, New Wind Farm Offers Renewable Energy to Customers, Wisconsin Engineer Journal, Monroe, Ed, Personal Communication, Solar Turbines Saturn 20 Generation Set, San Diego, California, National Weather Service, Accessed 2/18/02 Pawlak, L, Personal Communication, We Energies Customer Owned Generating Systems, Milwaukee, Wisconsin, Repp-Crest, Accessed 1/30/02 Rohatgi, Jonardan S. and Nelson, Vaughn., 1994, Wind Characteristics An Analysis for the Generation of Wind Power, 147. Schigoda, D, Personal Communication, We Energies Customer Owned Generating Systems, Milwaukee, Wisconsin, Siemens Solar, Accessed 2/05/02

36 29 Siemens Solar, Accessed 2/05/02 Thresher, R. and Hock, S., 1994, Wind systems for electrical power production, Mechanical Engineering, UTC Fuel Cells, Accessed 2/02/02 Valenti, Michael (Aug.1996) A leaner, greener power turbine. Mechanical Engineering, Vestas Wind Turbine, Accesses 2/18/02 WI Department of Administration, 2002.

37 30 7. BIBLIOGRAPHY Capstone Turbine Corporation, Accessed 2/10/02 Fuel Cells 2000, Accessed 2/05/02 Greenpeace Nederland, (1999), Solar Energy: from Perennial Promise to Competitive Alternative Accessed 2/20/02 Greenpeace, Accessed 2/14/02 Hutchinson, Harry (Oct 2000) Small-Scale Power. Mechanical Engineering, Siegrist, C., 2002, Personal Communication, Annual Average Wind Speeds, We Energies, Milwaukee, Wisconsin, Solar Turbine Incorporated, Accessed 2/21/02 Wolcott, Barbara (June 1999) Sun Worship, Mechanical Engineering,

38 31 Appendix A Monthly energy consumption at the PNIC Monthly energy conditions at the Pettit National Ice Center (11/15/00-1/15/02) Electricity Costs ($) Peak Off Peak Off Peak On Peak Period kwh kwh kwh Demand kw Demand kw 11/15-12/ /15-1/ /15-2/ /15-3/ /15-4/ /15-5/ /15-6/ /15-7/ /15-8/ /15-9/ /15-10/ /15-11/ /15-12/ /15-1/ Average

39 32 Appendix B Weibull Distribution Parametric k Study Weibull Distribution (k=1) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s) Weibull Distribution (k=1.2) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s)

40 33 Weibull Distribution (k=1.4) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed Weibull Distribution (k=1.6) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s)

41 34 Weibull Distribution (k=1.8) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s) Weibull Distribution (k=2.0) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s)

42 35 Weibull Distribution (k=2.2) Hours Jan Feb March Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s) Weibull Distribution (k=2.4) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s)

43 36 Weibull Distribution (k=2.6) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s) Weibull Distribution (k=2.8) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s)

44 37 Weibull Distribution (k=3.0) Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave Wind Speed (m/s)

45 38 Appendix C Weibull Distribution Data for k=2.0 Weibull Distribution for k=2.0 c: k: Month: Jan Feb March April May June July Aug Sept Oct Nov Dec Sum of months Days in Month: u hours at u Power Output: 112, , , , , , , , , , , , ,017,631.0

46 39 Appendix D Weibull Distribution for Average Wind Speeds +/- 3mph January Average Wind Speeds +/-3 mph c: k: Month: Jan Jan +3 Jan - 3 Days in Month: u hours at u Power Output: 112, , ,633.0

47 40 Appendix E Vestas Power Curve Data Wind Speed (m/s) Output (kw) Ave Range (m/s) Ave Output (kw)

48 Wind Speed (m/s) Output (kw) Ave Range (m/s) Ave Output (kw)

49 Wind Speed (m/s) Output (kw) Ave Range (m/s) Ave Output (kw)

50 Wind Speed (m/s) Output (kw) Ave Range (m/s) Ave Output (kw)

51 Wind Speed (m/s) Output (kw) Ave Range (m/s) Ave Output (kw)

52 Wind Speed (m/s) Output (kw) Ave Range (m/s) Ave Output (kw)

53 46 Appendix F Monthly Power Outputs +/-3mph Average Wind Speed Power Production versus Energy Bils Month: Jan Feb March April May June July Aug Sept Oct Nov Dec -3mph 41, , , , , , , , , , , ,316.9 Ave 112, , , , , , , , , , , , mph 194, , , , , , , , , , , ,738.6 Monthly Bills: 1/15-2/15/01 2/15-3/15/01 3/15-4/15/01 4/15-5/15/01 5/15-6/15/01 6/15-7/15/01 7/15-8/15/01 8/15-9/15/01 9/15-10/15/01 10/15-11/15/01 11/15-12/15/01 12/15-1/15/02 709, , , , , , , , , , , ,605-3mph 5.87% 5.53% 7.78% 7.20% 4.10% 2.23% 1.21% 1.12% 2.55% 4.23% 7.64% 6.88% Ave 15.87% 15.57% 19.84% 18.72% 13.84% 10.67% 7.55% 7.68% 12.18% 15.03% 21.10% 19.81% +3mph 27.43% 27.51% 33.24% 31.68% 26.97% 24.90% 20.03% 21.21% 28.43% 30.08% 36.87% 35.39% Monthly Bills: 12/15-1/15/02 1/15-2/15/01 2/15-3/15/01 3/15-4/15/01 4/15-5/15/01 5/15-6/15/01 6/15-7/15/01 7/15-8/15/01 8/15-9/15/01 9/15-10/15/01 10/15-11/15/01 11/15-12/15/01 527, , , , , , , , , , , ,049-3mph 7.89% 4.84% 7.62% 7.22% 4.18% 1.88% 1.33% 1.01% 2.26% 4.98% 7.14% 7.21% Ave 21.34% 13.64% 19.43% 18.77% 14.12% 8.97% 8.31% 6.91% 10.77% 17.70% 19.70% 20.73% +3mph 36.89% 24.10% 32.56% 31.76% 27.50% 20.94% 22.04% 19.08% 25.15% 35.42% 34.42% 37.05% 2 turbines (ave) 225, , , , , , , , , , , , turbines (ave+3) 389, , , , , , , , , , , ,477.2

54 Appendix G Saturn 20 Gas Turbine Specifications 47

55 48

56 49

57 50