This is an economics of energy transmission assignmnet. It must be all done in Excel and the excel must be neat and organized and the final answers to each questions must be clearly marked.
1. Suppose we are planning a 100 MW wind farm with a 1-year p-50 capacity factor of 44% and a 1-year p-99 capacity factor of 36%. The total cost to build the plant is $1,400/kW, and all power will be sold on a long-term power purchase agreement for $35/MWh. The plant has fixed operating costs of $40/kW-yr. A lender is willing to offer a 25-year loan at an interest rate of 4.5%. (a) What is the wind farm’s Cash Flow Available for Debt Service (CFADS) if the lender sizes the debt based on a debt service coverage ratio of 1.30x at the p-50 level? (b) What would the CFADS be if the lender instead used a DSCR of 1.00x at the p-99 level? (c) Suppose the lender uses the smaller of the annual payments implied by parts (a) and (b). What is the total debt capacity (i.e., maximum loan size) for the project? (d) Assuming the project developers use the maximum amount of debt on offer, what percent of the project will be funded by the equity investors? Answers to this question have been provided in the Excel file. Use the information in this question and the answer provided to answer the next questions. 2. Suppose we are planning power system operations for 24 hours. Data for a typical spring day in the San Diego Gas & Electric territory has been uploaded to an Excel workbook on Canvas (with generators aggregated to avoid exceeding Excel Solver’s limit of 200 decision variables). Data includes the resources, the availability of renewable resources in each of the 24 hours, and demand. Note that demand is recorded at the level of the transmission-distribution interface, and accordingly does not include any load served by distribution-level photovoltaics. Construct a model in Excel describing this system and solve to determine an optimal production schedule for the six resources. Assume a gas price of $3.50/MMBtu, but leave in the capability to modify this assumption for future problem sets. (a) What is the total cost to operate the system for the day? (b) In what hours is the combined cycle gas plant on the margin? What is the price during these hours? Answers to this question have been provided in the Excel file. Use the information in this question and the answer provided to answer the next questions. 2. Consider the linear program from Problem 2. If you did not produce a sensitivity report that yielded prices in each of the 24 hours, do so now (or consult the posted answers). Instead of the system problem, consider the optimization problem faced by the CCGT, which wants to maximize profit. Suppose that the system operator sets prices equal to the shadow prices calculated in the sensitivity report. The operator of the CCGT then determines a production schedule that maximizes revenue (quantity times price) minus its production cost. Note that we assume that the CCGT is a price taker, i.e., it cannot change the price by changing its production. (a) For this optimization problem, what is the objective function? (b) For this optimization problem, what are the decision variables? (c) Construct a model describing the CCGT’s problem in Excel and solve to determine a profit-maximizing production schedule. How does the profit-maximizing schedule compare to the socially optimal schedule determined in problem 2? 3. Consider a modification to the 100 MW wind farm from problem 2. Suppose the annual capacity factor from the plant is normally distributed with mean of 44% and standard deviation of 4%. The total cost to build the plant is $1,400/kW, and the plant has fixed operating costs of $40/kW-yr. A lender is willing to offer a 25-year loan at an interest rate of 4.5%. However, unlike in problem 1, the plant does not sell its power on a long-term contract. Instead, it operates on a merchant basis, selling in the spot market. Spot market prices for the wind farm are a product of the natural gas price, the average market heat rate for the year, and a nodal scalar, each of which (we assume) follows a normal distribution. The natural gas price has mean $3.50/MMBtu and standard deviation $0.35/MMBtu. The average market heat rate has mean 10 MMBtu/MWh and standard deviation 0.5 MMBtu/MWh. The nodal scalar has mean 1.0 and standard deviation .03. This means that the expected price is $35/MWh, the same as the contracted price in problem 1. All random variables are assumed to be independent. (a) In Excel, draw 1,000 samples of the 4 random variables and compute the annual electricity revenue for the plant under each draw. What is the average electricity revenue across the 1,000 samples? How does it compare to the p-50 revenue in problem 1? (b) Compute the p-50 and p-99 CFADS under these assumptions, i.e., the 500th and 990th ranked outcomes in your sample. (c) Given the increased uncertainty, suppose the debt provider insists on a debt service coverage ratio of 2.25x at the p-50 level. What is the total debt capacity of the project? (d) Assuming the project developers use the debt size calculated in (c), what percent of the project will be funded by the equity investors? How does this compare to the contracted case we considered in problem 1? Note that since Excel will recalculate every time a new sample is drawn, it is okay if output values fluctuate slightly upon recalculation. Problem 1 Assumptions Unit Plant Capacity100MW Capital Cost1,400$/kW P-50 Capacity Factor44.0%% P-99 Capacity Factor36.0%% Operating Expenses$40.00per KW-Year PPA Price$35.00per MWh Sizing DSCR p-991.00x Ratio Sizing DSCR p-501.30x Ratio Interest Rate4.5%% Length25Years Hours in Year8,760Hours Conversion to USD 0001,000USD Debt Sizing p-50p-99 Electricity Production (MWh)385,440315,360 PPA Rate (/MWh)$35.00$35.00 Electricity Revenue$ 13,490,400$ 11,037,600 Operating Expense4,000,0004,000,000 EBITDA$ 9,490,400$ 7,037,600 Cash Flow Available for Debt Service (CFADS)$ 9,490,400.00$ 7,037,600.00 Maximum debt service$ 7,037,600.00 Debt Capacity($104,355,003.40) Capital Cost140,000,000 Equity share25.5% Demand HourDemand_MW 11615 21553 31518 41562 51733 61976 72274 82597 92838 103023 113125 122963 132743 142666 152578 162482 172422 182374 192378 202501 212506 222258 231988 241760 Resources R_IDResourceExisting_Cap_MWVar_OM_cost_per_MWhFuelHeat_rate_MMBTU_per_MWh 1biomass21.45.234None12.76 2natural_gas_fired_combined_cycle1928.53.4pacific_naturalgas7.52 3natural_gas_fired_combustion_turbine788.410.8pacific_naturalgas10.69 4onshore_wind_turbine217.60None0 5small_hydroelectric7.320None0 6solar_photovoltaic5000None0 Availability 123456789101112131415161718192021222324 onshore_wind_turbine0.75050.78030.5290.46210.37030.63960.34090.22690.76910.60460.5110.42330.23940.29730.22620.30060.26280.36130.24180.28230.33050.44140.58120.6637 small_hydroelectric0.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.43510.4351 solar_photovoltaic0000000.05530.22110.47760.57570.60390.61390.64460.64550.62410.56950.46780.32360.047700000 Sensitivity Report 1 Microsoft Excel 16.0 Sensitivity Report Worksheet: [ps3_answers.xlsx]Model Report Created: 10/28/2022 11:51:55 AM Variable Cells FinalReducedObjectiveAllowableAllowable CellNameValueCostCoefficientIncreaseDecrease $C$13biomass Hour121.4-24.4865.23424.4861E+30 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Hour2321.4-24.4865.23424.4861E+30 $Z$13biomass Hour2421.4-24.4865.23424.4861E+30 $C$14natural_gas_fired_combined_cycle Hour11427.106268029.7218.49524.486 $D$14natural_gas_fired_combined_cycle Hour21358.621788029.7218.49524.486 $E$14natural_gas_fired_combined_cycle Hour31378.304668029.7218.49524.486 $F$14natural_gas_fired_combined_cycle Hour41436.862108029.7218.49524.486 $G$14natural_gas_fired_combined_cycle Hour51627.837788029.7218.49524.486 $H$14natural_gas_fired_combined_cycle Hour61812.238108029.7218.49524.486 $I$14natural_gas_fired_combined_cycle Hour71928.5-18.49529.7218.4951E+30 $J$14natural_gas_fired_combined_cycle Hour81928.5-18.49529.7218.4951E+30 $K$14natural_gas_fired_combined_cycle Hour91928.5-18.49529.7218.4951E+30 $L$14natural_gas_fired_combined_cycle Hour101928.5-18.49529.7218.4951E+30 $M$14natural_gas_fired_combined_cycle Hour111928.5-18.49529.7218.4951E+30 $N$14natural_gas_fired_combined_cycle Hour121928.5-18.49529.7218.4951E+30 $O$14natural_gas_fired_combined_cycle 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