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

March 29th, 2016 No Comments   Posted in wind energy and power

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. More »

Integrated Wind Prospecting, Wind Resource Assessment, Annual Power Generation and Capacity Factor, and Wind Project Finance Model with Monte Carlo Simulation

March 29th, 2016 No Comments   Posted in wind energy and power

Integrated Wind Prospecting, Wind Resource Assessment, Annual Power Generation and Capacity Factor, and Wind Project Finance Model with Monte Carlo Simulation

Yes, your energy technology expert has done it again.

Version 3 has been released that integrates all the steps needed in fully developing your wind energy project.

It combines the data entry of the wind velocity profile of the prospective wind farm site (from wind mast anemometer monitoring or from 3-TIER, NREL wind profile database), interpolation of daily and hourly wind speed (up to 15-minute pulse if needed by the TRANSCO / GRID operator), look-up tables for the various wind turbine generator manufacturers, calculation of annual power generation and capacity factor, overnight capital cost of wind turbine and its fixed and variable O&M costs, and project finance modeling (with option for both deterministic and stochastic modeling using Monte Carlo Simulation). More »

Integrated Wind Prospecting, Wind Resource Assessment, Annual Power Generation and Capacity Factor, and Wind Project Finance Model with Monte Carlo Simulation (Ver. 4)

February 11th, 2015 No Comments   Posted in wind energy and power

Integrated Wind Prospecting, Wind Resource Assessment, Annual Power Generation and Capacity Factor, and Wind Project Finance Model with Monte Carlo Simulation (Ver. 4)

Yes, your energy technology expert has done it again.

Version 4 has been released that integrates all the steps needed in fully developing your wind energy project.

It combines the data entry of the wind velocity profile of the prospective wind farm site (from wind mast anemometer monitoring or from 3-TIER, NREL wind profile database), interpolation of daily and hourly wind speed (even up to 15-minute pulse if needed by the TRANSCO / GRID operator), look-up tables for the various wind turbine generator manufacturers, calculation of annual power generation and capacity factor, overnight capital cost of wind turbine and its fixed and variable O&M costs, and project finance modeling (deterministic with option for both deterministic and stochastic modeling using Monte Carlo Simulation). More »

Stochastic (Probabilistic) Wind Turbine Simulator for Annual Power Output and Capacity Factor

February 4th, 2015 No Comments   Posted in wind energy and power

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. More »