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Modeling the Future Energy Demands of Oklahoma University of Oklahoma School of Chemical, Biological, and Materials Engineering Vu Le Joseph Nick.

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Presentation on theme: "Modeling the Future Energy Demands of Oklahoma University of Oklahoma School of Chemical, Biological, and Materials Engineering Vu Le Joseph Nick."— Presentation transcript:

1 Modeling the Future Energy Demands of Oklahoma University of Oklahoma School of Chemical, Biological, and Materials Engineering Vu Le Joseph Nick

2 So what is our project all about? Dirty Energy Clean Energy How much will it cost energy companies? How much will it cost Oklahomans? What can the government do to foster the much needed transition?

3 Dirty Energy Clean Energy High CO 2 emissions Fossil Fuel derived CHEAP Low CO 2 emissions Sustainable energy Currently expensive Compared to Dirty energy

4 Just how Dirty are we talking? Oklahomas Current Electricity Oklahomas Current Transportation Fuels Oklahoma total CO 2 emissions from fossil fuels Coal fired plants have the highest amount of CO 2 emissions for any power plant Over 215 billion pounds of CO 2 every year!! 52% from coal fired plants Less than 1% from Bio-fuels

5 Cost model - predict the optimal yearly energy use in Oklahoma, by industry, so as to minimize total energy costs (net present cost) while reducing carbon dioxide emissions and increasing total job salaries paid in Oklahoma to specified levels. The objective of this project is to create mathematical models that will be used to plan Oklahomas move toward cleaner energy through the year 2030. Profit model - predict the optimal yearly energy use in Oklahoma, by industry, so as to maximize total profitability, net present value. Utility pricing decisions and government tax incentives will be researched and their effect on overall profitability will be characterized.

6 Develop Cost model Develop Profit model Model all energy used in Oklahoma from 2010 - 2030 Easy enough right??

7 Forecasted U.S. natural gas consumption data – available Forecasted Okla. natural gas consumption data – not available Oil Refinerys Revenues Vary month to month & year to year Vary from refinery to refinery Each one produces different products How accurate are forecasted commodity prices?

8 Location is not considered Constant operation cost for plants and refineries Switchgrass used as ethanol feedstock Soybean used as biodiesel feedstock Construction times for new plants Wind – 1 year Everything else – 3 years

9 Residential Commercial Industrial Plant Gasoline and Diesel Biodiesel Ethanol Coal-fired plants Natural gas fired plants Hydroelectric plants Wind farms Fuels Electricity Heating

10 Past data Present data Projected data Energy Information Administration U.S. Department of Energy Oklahoma Wind Power Initiative Oklahoma Renewable Energy Council Some forecasted data was readily available, while other data had to be independently forecasted by us.

11 Total cost of energy Total carbon dioxide emissions Total Revenues Total salaries paid to Oklahoma workers Number of existing plants (by type) Capacity of existing plants Total plant operating hours Plant CO 2 emissions Current fuel prices Forecasted energy supply (by type) Forecasted energy demand (by type) Forecasted fuel prices Cost of building new plants Examples of required data in calculating:

12 Fig.1 A coal fired power plant Fig.2 Repower wind turbines Fig. 3 A hydroelectric Dam Coal and natural gas plants Hydroelectric plants and Wind farms

13 Comparison of coal & natural gas plants to wind & hydroelectric plants Fuel Type Current Capacity (MW) Emissions (lb. CO2/MWh) Approx Total yearly Emissions (lb. CO2/ yr)ProsCons Coal 5,3622,300 ~ 75 billion -High existing capacity -Cheap energy -Enormous CO2 emissions -Contributes greatly to global warming Nat. gas 12,883960 ~2.6 billion Wind 689negligible -Nearly zero emissions - Low O&M costs (esp. wind) -Sustainable energy source -Low existing capacity -High capital costs for new plants/farm Hydro 1,110 negligible

14 Gasoline and Diesel (Crude Oil Refineries) Biodiesel and Ethanol Refineries Canadian Sand Oil Field Sunflower field, Biodiesel production Switch grass field, Ethanol production

15 Biofuels vs. Petroleum Fuels FuelFeedstock Capacity (bbl/d) Refining Emissions (ton CO2/ bbl) Net Emissions (kg CO2/MJ) ProsCons Gasoline Oil 240,0000.40794 -High existing cap. -Currently cheaper -High emissions -Non sustainable Diesel200,0000.10283 EthanolBiomass1300.466 -24 (switchgrass) -Sustainable energy -Reduces CO2 in 2 ways 1.Crops absorb CO2 2.Less CO2 produced in refining -Low existing cap. this means high costs of new plants -Lower energy per vol. than diesel Biodiesel Vegetable oil & animal fat 2,6000.100~ 43

16 Fig. The CO2 cycle of ethanol production Cellulosic biomass (switchgrass) cellulose fermentation sugars ETHANOL enzymatic breakdown & pyrolysis processing

17 (Clockwise from bottom left) Residential- Household use Industrial- Heat, power, and chemical feedstock use Commercial- Use by non- manufacturing establishments Plant- Fuel use in N.G. processing plants Natural Gas Electricity

18 Oklahoma Natural Gas Consumption (2007) Type Consumption (MMcf) Consumption (GJ) CO 2 Emissions (billion lbs/yr) % of total use Residential 59,84263,254,185 11.17 17.4 Industrial 175,881 185,909,869 32.87 51.2 Commercial 40,84943,178,730 7.64 11.9 Plant 66,44170,229,810 12.52 19.5 Total 343,015362,572,594 64.2 100 Various estimates place natural gas at 75-90% of total heating (all sectors)

19 Total Cost i = (Fixed Opr. Cost) + (Var. Opr. Cost) + (Fuel Cost) + (Capital Cost) + (Expansion Cost) + (Transportation Cost) + (E Carbon Capture Cost) [ (Fixed Opr. Cost) + (Var. Opr. Cost) + (Fuel Cost) + (N Carbon Capture Cost New) ] new Electricity Heating Fuels

20 o CO 2 emissions o Fuel cost o New plant capital cost Each energy type has varying data for: o Existing capacity o Future demand o Job salaries creation Increased demand New plants Lower CO2 emissions Energy types with lower emissions or Carbon capture More job salaries Choose energy with most jobs Minimize Cost Choose most cost effective energy

21 For both fuels and electricity, these costs were approximated as: Cost = X Capacity -or- Cost = X Fuel Used Where X is a function of the energy type. Fixed operating and maintenance (Fixed O&M) costs Salaries Wind farm lease payments Insurance payments Variable operating and maintenance (Var. O&M) costs Raw material costs Utility payments Fuel costs Fuels Crude Oil, Switchgrass, Soybean Electricity Coal, Natural Gas

22 The Fixed and Variable O&M costs for all 9 energy types were not readily available from one source. Examples of organization and company websites were used to locate our O&M cost data Energy and Environmental Economies Incorporated Energy Information Administration U.S. Department of Agriculture American Wind Energy Association Baker & OBrien Incorporated Resource Dynamic Corporation Documented, credible sources.

23 Capital costs are the costs of building new plants or expanding existing plants. Cost = ( X Capacity ) + Y Unlike fixed and variable O&M costs, capital costs have a minimum associated cost and thus can not be approximated as easily. What to do? Analyze data from previous plant constructions and plant expansions

24 Data we were able to find made no distinctions between electricity plant fuel sources (coal, natural gas, etc) Not including hydro-electric and wind energy Unlike fuels, new electricity plants can be built and are not limited to expansions Minimum cost for new coal and NG plant construction, regardless of capacity ~ 259 million

25 There is no minimum installed capital cost for new wind energy operations Capital cost is a function of capacity where X is the average installed cost per MW Installed cost = 1,750,000 $ MW Cost = X capacity

26 Total Salary = Existing Salaries (2009) + New Salaries New Salaries = New Operation Salaries + New Construction Salaries Operation Salaries = Wages paid to engineers and employees who work to operate and maintain energy creation facilities Example: Plant managers, plant engineers, plant operators, etc Construction Salaries = Wages paid to engineers and employees who work in constructing new energy creation facilities Example: Construction engineers, construction workers, transportation drivers We are evaluating job creation in the state of Oklahoma using total wages paid to Oklahoma workers yearly

27 From Perrys Chemical Engineers Handbook Plant construction costs as % of total plant installation cost (total capital) Construction Labor Expenses34% Construction Material Expenses66% Total Expenses (total capital cost) 100%

28 [1] Convert our capacity data into kg / day [2] Estimate the number of process steps involved [3] Calculate salary paid from employee hours per day required The following graph was constructed using data from DESIGN, figure 6-9 Calculate average refinery employees salary Engineers vs. non-engineer workers

29 Electricity Heating Fuels o Operation Costs o New plant capital cost Each energy type has varying data for: o CCS cost Profitability Explored different scenarios for: Tax breaks New sustainable energy types Carbon Capture, existing plants Job creation Emissions and job creation Minimum price to consumers to meet specified return on investment o Revenues

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31 Indices t time period (yrs) i Individual boiler or refinery j Fuel type (i.e. coal/natural gas) Sets new New plants or refineries Electric, Fuel, Heat

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33

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35 *only new and electric plants are shown

36 Energy Generated must equal Demand

37 Net CO2 Emission must be reduced by a preset limit

38 Energy Generated must be less than capacity

39 Job Creation in Salary must increase by a preset limit

40 Annual profits from new plants and refineries must exceed a set ROI.

41 Operation Cost Electricity Industry Transportation Fuel Natural Gas Heating CO 2 Reduction Job Salary Profitability 3200 Lines of Codes ~ 2 min to run

42

43 GAMS Code (Fuel Model)

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45 This surface represent the maximum NPV possible at a certain CO 2 limit and Job creation for all industries combined.

46 Job salary creation has a minor effect on NPV CO 2 reduction has a major effect on NPV After 2% CO2 reduction, more carbon capture technology is used. - Primary reason for the steeper slope

47 *Jobs at 1% Tax Breaks (percent of profit) CO 2 ROI0%10%20%30% 0.0%2.5% N/A $ 0.05 0.0%5.0% N/A $ 0.07 $ 0.06 0.0%7.5% N/A $ 0.09 $ 0.08 0.0%10.0% N/A $ 0.10 $ 0.09 1.0%2.5% N/A $ 0.06 1.0%5.0% N/A $ 0.07 $ 0.06 1.0%7.5% N/A $ 0.09 $ 0.08 1.0%10.0% N/A $ 0.10 $ 0.09 2.0%2.5% N/A $ 0.07 2.0%5.0% N/A $ 0.07 2.0%7.5% N/A $ 0.09 $ 0.08 2.0%10.0% N/A $ 0.10 $ 0.09

48 *Jobs at 1% This table shows the minimum average electricity price _require to make a profit. Investors will not invests in new plants with no tax break Tax Breaks (percent of profit) CO 2 ROI0%10%20%30% 0.0%2.5% N/A $ 0.05 0.0%5.0% N/A $ 0.07 $ 0.06 0.0%7.5% N/A $ 0.09 $ 0.08 0.0%10.0% N/A $ 0.10 $ 0.09 1.0%2.5% N/A $ 0.06 1.0%5.0% N/A $ 0.07 $ 0.06 1.0%7.5% N/A $ 0.09 $ 0.08 1.0%10.0% N/A $ 0.10 $ 0.09 2.0%2.5% N/A $ 0.07 2.0%5.0% N/A $ 0.07 2.0%7.5% N/A $ 0.09 $ 0.08 2.0%10.0% N/A $ 0.10 $ 0.09

49 4 Scenario will be presented: Retail Price of Electricity at 10 cent/KWH ROI at 10% CO 2 JobsTax Breaks S10% 10% S21% 10% S32.2%2%10% S41% 20%

50 New hydro-plant capacity by scenario (MW) Plants20102013201420172020202420252026 Total 0% CO 2, 0% Jobs, 10% Tax Break 3121400357678 1% CO 2, 1% Jobs, 10% Tax Break 412140050345916 2.2% CO 2, 2% Jobs, 10% Tax Break 51191814003844001484 1% CO 2, 1% Jobs, 20% Tax Break 5180357376119501083 New Wind Capacity by scenario (MW) Plants2011201220132014201620182020202220252026 Total 0% CO 2, 0% Jobs, 10% Tax Break 51191952382373571147 1% CO 2, 1% Jobs, 10% Tax Break 51193052534405001617 2.2% CO 2, 2% Jobs, 10% Tax Break 517247227500 1492 1% CO 2, 1% Jobs, 20% Tax Break 5119 457 1271

51 New hydro-plant capacity by scenario (MW) Plants20102013201420172020202420252026 Total 0% CO 2, 0% Jobs, 10% Tax Break 3121400357678 1% CO 2, 1% Jobs, 10% Tax Break 412140050345916 2.2% CO 2, 2% Jobs, 10% Tax Break 51191814003844001484 1% CO 2, 1% Jobs, 20% Tax Break 5180357376119501083 New Wind Capacity by scenario (MW) Plants2011201220132014201620182020202220252026 Total 0% CO 2, 0% Jobs, 10% Tax Break 51191952382373571147 1% CO 2, 1% Jobs, 10% Tax Break 51193052534405001617 2.2% CO 2, 2% Jobs, 10% Tax Break 517247227500 1492 1% CO 2, 1% Jobs, 20% Tax Break 5119 457 1271 At low CO 2 reduction and Job creation, wind plants are favored At high CO 2 reduction and Job creation, either plants are favored equally At high CO 2 reduction, plants should be built at a later time No biodiesel and ethanol refineries are built

52 0% CO 2, 0% Jobs, 10% Tax Break 1% CO 2, 1% Jobs, 10% Tax Break 2.2% CO 2, 2% Jobs, 10% Tax Break 1% CO 2, 1% Jobs, 20% Tax Break # of Wind Plant 5 farms Total Capacity 1147 MW1617 MW1492 MW1271 MW # of Hydroelectric 3 plants4 plants5 plants Total Capacity 678 MW916 MW1484 MW1083 MW Avg ROI 9.6%10.1% 10.2% Std Deviation 2.0%2.4%2.7%2.3%

53 For all four scenarios, a 10% annual ROI is possible with a standard deviation ranging from 2.0%-2.7%. 0% CO 2, 0% Jobs, 10% Tax Break 1% CO 2, 1% Jobs, 10% Tax Break 2.2% CO 2, 2% Jobs, 10% Tax Break 1% CO 2, 1% Jobs, 20% Tax Break # of Wind Plant 5 farms Total Capacity 1147 MW1617 MW1492 MW1271 MW # of Hydroelectric 3 plants4 plants5 plants Total Capacity 678 MW916 MW1484 MW1083 MW Avg ROI 9.6%10.1% 10.2% Std Deviation 2.0%2.4%2.7%2.3%

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55 These graphs show the job creation represented by salary - Construction labor - Operation labor

56 Low operation labor due to wind farms and hydroelectric plants - Require less people to operate compared to coal and natural gas

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58 Higher CO 2 reduction limit results in less profit for the electric industry - This is due to the cost of CO 2 capture - Primarily from coal plants

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60 Profit decreases as the CO 2 limit and job creation increases Result is similar for all scenarios under a 2% CO2 reduction Larger then 2% reduction, the model chose to build plants later - Compensate by using a lot more CCS

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62 These tables include CO 2 emissions from plants and refineries and from consumers Majority of CO 2 emissions from plants and refineries are from electric plants. - Reduction is mostly from electric plants

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64 Use of CCS increases with the CO2 limit - Almost all from coal plants before 2% After 2% reduction, more CCS use from natural gas plants are done. Minor CCS usage from oil refineries

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66 No change in generation from coal and natural gas plants Generation from wind and hydroelectric plants shown to steadily increase - 24% wind by 2030 - 15% hydroelectric by 2030

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68 Transportation fuel industry is shown to remain virtually unchanged

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