Overview
There are many variables (wind speed, air density, etc.) that determine the average yearly energy produced by a wind turbine. This example demonstrates a way of determining energy production through the use of a simple Monte Carlo simulation.
Description
This VI uses a simple Monte Carlo 'Transfer Function' to determine 1000 'outcomes' (i.e. estimates of yearly energy production). The average of these outcomes / estimates is then used to predict the average yearly energy production (with a ~50% confidence interval) of a wind turbine.
The basis of the Monte Carlo simulation is that it's input variables are not constants. In fact, many variables follow a Gaussian distribution (or in the case of wind speed, a Weibull distribution). In addition, variables may be coupled together. For instance, many wind turbines do not have a constant system efficiency over the operating wind speed range. In other words, as the wind speed increases or decreases, so will the turbine's system efficiency. Since these input variables vary and since they may be coupled, taking an average of these inputs and calculating an 'average' energy output may often times lead to incorrect predictions (or, in this case, poor estimates of real-world energy production). The Monte Carlo simulation approach is a great technique for accomodating these input variabilities and often times predicts a much more realistic average estimate.
Steps to Implement or Execute Code
- Download the attached LLB.
- Open the top level VI in the LLB.
- Enter in the parameters for the wind turbine you want to simulate and the parameters for the environment for which it will be operated in.
- Click the Run arrow.
Requirements
Software
LabVIEW 12 or higher (Full or Professional Development System)
