## Wind Energy Financial Model with Stochastic (Probabilistic) Wind Turbine Simulator for Annual Power Output and Capacity Factor

**Wind Energy Financial Model with Stochastic (Probabilistic) Wind Turbine Simulator for Annual Power Output and Capacity Factor**

Wind Turbine Generator (WTG) is the current darling of the renewable energy power generation industry.

It is clean, generally available, and cost-effective. It’s power output, however, is very variable, ever changing by the hour with time.

Now with the instantaneous wind speed as a function of the average speed +/- the positive and negative deviation multiplied by a random fraction, the probable wind speed and thus the power output can be simulated, and when aggregated in 24 x 365 hours in a year, the annual energy output and annual capacity factor is determined.

And using statistical analysis, the expected value (mean), standard error, median, standard deviation, variance, skewness and Kurtosis are calculated for both the annual energy output and annual capacity factor.

Turbine Model and kW rating | GE900 | 900 | GE1.5 S | 1500 | GE1.5 SL | 1500 |

MWH | % CF | MWH | % CF | MWH | % CF | |

1000 | 2,108 | 26.74 | 3,878 | 29.51 | 4,408 | 33.55 |

Mean | 2,126 | 26.96 | 3,911 | 29.76 | 4,446 | 33.83 |

Standard error | 0 | 0.00 | 0 | 0.00 | 0 | 0.00 |

Median | 2,126 | 26.97 | 3,911 | 29.77 | 4,446 | 33.83 |

Standard deviation | 8 | 0.10 | 14 | 0.11 | 13 | 0.10 |

Variance | 65 | 0.01 | 197 | 0.01 | 178 | 0.01 |

Skewness | 0.0079 | 0.0079 | 0.0105 | 0.0105 | 0.0123 | 0.0123 |

Kurtosis | 2.7407 | 2.7407 | 2.7155 | 2.7155 | 2.7468 | 2.7468 |

Expected value = | 2,126 | 26.96 | 3,911 | 29.76 | 4,446 | 33.83 |

The standard deviation*1.96 = | 16 | 0.20 | 27 | 0.21 | 26 | 0.20 |

95% of all outcomes, max = | 2,142 | 27.16 | 3,938 | 29.97 | 4,472 | 34.03 |

95% of all outcomes, min = | 2,110 | 26.76 | 3,883 | 29.55 | 4,420 | 33.63 |

To enable your technical team to optimize the selection of the equipment manufacturer (cost per kW, fixed and variable O&M, WTG power curve) and site selection (wind velocity profile given location and wind mast elevation), the following sets of excel models would be most helpful in your technical and economic analysis:

1) DETERMINISTIC or PROBABILISTIC model that includes MONTE CARLO SIMULATION for equity and project returns (IRR, NPV and PAYBACK), net income after tax discounted at pre-tax WACC, pre-tax WACC, and electricity tariff (feed-in-tariff). A histogram may also be prepared by the MONTE CARLO simulation.

Here are two demo models for onshore wind and offshore wind farms:

ADV Wind Onshore Model3a_MCS-copy – Monte Carlo Simulation

14.62 MW Configuration |
Monte Carlo Simulation inputs |
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0 |
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Plant Variables |
11,612 | Deterministic | ||

Current Value | Value | Min | Max | |

Electricity Tariff | 5.207 | 5.335 | 90.00% | 110.00% |

Plant Availability Factor | 38.04% | 36.90% | 90.00% | 110.00% |

Fuel Heating Value | ||||

Debt Ratio | 70% | 70% | 90.00% | 110.00% |

Plant Capacity per Unit | 1.46 | 1.50 | 90.00% | 110.00% |

O&M Cost (Opex) – variable O&M | 5.20 | 4.85 | 90.00% | 110.00% |

O&M Cost (Opex) – fixed O&M | 15.41 | 16.28 | 90.00% | 110.00% |

O&M Cost (Opex) – fixed G&A | 205.86 | 200.00 | 90.00% | 110.00% |

Cost of Fuel | ||||

Plant Heat Rate | ||||

Exchange Rate | 39.68 | 43.00 | 90.00% | 110.00% |

Capital Cost (Capex) | 1,041.72 | 997.36 | 90.00% | 110.00% |

Stochastic Model |
Net Profit |
pre-Tax |
Feed-in |
|||

Equity Returns |
After Tax |
WACC |
Tariff |
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press ctrl + W to run |
NPV |
IRR |
PAYBACK |
Million PhP |
% |
PhP/kWh |

1,000 | (120,040) | 13.00% | 10.55 | 628 | 10.45% | 5.388 |

Mean | 2,992 | 16.58% | 8.92 | 751 | 11.42% | 5.082 |

Standard error | 3,248 | 0.09% | 0.05 | 4 | 0.03% | 0.009 |

Median | -2,466 | 16.34% | 9.13 | 752 | 11.31% | 5.084 |

Standard deviation | 102,704 | 2.90% | 1.55 | 116 | 1.01% | 0.296 |

Variance | 10,548,145,085 | 0.08% | 2.40 | 13,364 | 0.01% | 0.088 |

Skewness | 0.292 | 0.418 | -0.339 | 0.011 | 0.562 | 0.015 |

Kurtosis | 2.864 | 2.969 | 2.434 | 2.680 | 3.093 | 1.780 |

Expected value = | 2,992 | 16.58% | 8.92 | 751 | 11.42% | 5.082 |

The standard deviation*1.96 = | 201,300 | 5.68% | 3.04 | 227 | 1.97% | 0.581 |

95% of all outcomes, max = | 204,292 | 22.26% | 11.96 | 977 | 13.39% | 5.662 |

95% of all outcomes, min = | -198,308 | 10.90% | 5.88 | 524 | 9.45% | 4.501 |

ADV Wind Offshore Model3a_MCS-copy – Monte Carlo Simulation

28.1 MW Configuration |
Monte Carlo Simulation inputs |
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0 |
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Plant Variables |
(83,767) | Deterministic | ||

Current Value | Value | Min | Max | |

Electricity Tariff | 14.167 | 13.276 | 90.00% | 110.00% |

Plant Availability Factor | 39.13% | 40.15% | 90.00% | 110.00% |

Fuel Heating Value | ||||

Debt Ratio | 70% | 70% | 90.00% | 110.00% |

Plant Capacity per Unit | 1.41 | 1.50 | 90.00% | 110.00% |

O&M Cost (Opex) – variable O&M | 7.04 | 7.48 | 90.00% | 110.00% |

O&M Cost (Opex) – fixed O&M | 53.08 | 58.65 | 90.00% | 110.00% |

O&M Cost (Opex) – fixed G&A | 26.24 | 25.00 | 90.00% | 110.00% |

Cost of Fuel | ||||

Plant Heat Rate | ||||

Exchange Rate | 41.29 | 43.00 | 90.00% | 110.00% |

Capital Cost (Capex) | 3,563.79 | 3,281.78 | 90.00% | 110.00% |

Stochastic Model |
Net Profit |
pre-Tax |
Feed-in |
|||

Equity Returns |
After Tax |
WACC |
Tariff |
|||

press ctrl + W to run |
NPV |
IRR |
PAYBACK |
Million PhP |
% |
PhP/kWh |

1,000 | (83,767) | 16.00% | 8.84 | 5,010 | 11.18% | 14.167 |

Mean | -2,405 | 16.51% | 8.73 | 5,203 | 11.35% | 12.950 |

Standard error | 15,883 | 0.08% | 0.05 | 21 | 0.03% | 0.024 |

Median | -39,697 | 16.24% | 8.96 | 5,201 | 11.26% | 12.969 |

Standard deviation | 502,278 | 2.50% | 1.56 | 661 | 0.86% | 0.749 |

Variance | 252,283,550,966 | 0.06% | 2.43 | 436,822 | 0.01% | 0.560 |

Skewness | 0.244 | 0.443 | -0.257 | -0.001 | 0.510 | 0.007 |

Kurtosis | 2.835 | 2.965 | 2.323 | 2.634 | 3.073 | 1.786 |

Expected value = | -2,405 | 16.51% | 8.73 | 5,203 | 11.35% | 12.950 |

The standard deviation*1.96 = | 984,466 | 4.90% | 3.05 | 1,295 | 1.69% | 1.467 |

95% of all outcomes, max = | 982,060 | 21.41% | 11.79 | 6,499 | 13.04% | 14.417 |

95% of all outcomes, min = | -986,871 | 11.61% | 5.68 | 3,908 | 9.65% | 11.483 |

2) WIND SIMULATOR (hourly simulation of wind speed for a given location using the wind velocity profile from wind resource tools such as 3-TIER or NREL, power curves to calculate wind turbine power output, annual MWH generation, annual capacity factor CF).

Alternatively, a 15-minute simulation may be prepared if the local transmission/grid operator would require a grid impact study (system impact study) to identify the system/grid requirements to be able to handle the variable power output of the wind turbines.

Wind Energy Resource Assessment Tool_3TIER Prediction – Copy

3) Wind Energy Resource Assessment Tool Anemometer Measurement Log (allows you to enter hourly anemometer readings of wind speed vs. time, and use power curves to calculate wind turbine power output, annual MWH generation, and capacity factor CF).

Using the average wind speed as correction factor, hourly wind speed readings of a similar location may be synthesized if a reference location with complete data is known and may be used to extrapolate the anemometer readings of another location with limited wind data with a known average speed.

Wind Energy Resource Assessment Tool_Anemometer Measurement – Copy

4) Wind Turbine Price List (the overnight capital cost of a number of known wind turbines to get a feel of the relative costs of the various wind turbine models, and given the power curves, helps you optimize the selection of model size (MW output) and equipment manufacturer (turbine model).

Wind Turbine Price List – Copy

5) Wind Turbine Power Curves with customized MONTE CARLO SIMULATION of wind speed, annual power output and annual capacity factor for the following WTG models:

- Bergey
- Bonus
- Carter
- Dewind
- Fuhrlaender
- Gamesa Eolica
- GE Wind
- Jacobs
- Jacobs-additions
- Lagerwey
- NEG Micon
- Nordex
- Norwin
- Repower
- Suzlon
- TMA
- Turbowinds Inland
- Vestas

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To purchase any project finance model with Wind turbine GeneratorTemplate, please email me

energydataexpert@gmail.com

Purchase any model for USD 800 for the complete package (wind project finance model, wind turbine power curves, wind simulator, wind turbine costs and MCS add-in program) and remit via PayPal (use my gmail account above) or via bank / wire transfer (BPI current account which I will email you once you confirm your order).

If you want it customized with your own specific data and additional rows and columns for income, expense and balance sheet accounts, add another USD 500 for 2-hours of additional work.

Cheers,

Energy technology selection expert

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