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Example files for "Programming with MATLAB" Webinar

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Example files for "Programming with MATLAB" Webinar



Example files for "Programming with MATLAB" Webinar, first delivered October 3, 2013.

function windData = WindAnalysisFcn(filename)
%% Wind Turbine Data Analysis
% This demo analyzes wind data measured on a meteorological observation
% tower to see if the location is a good prospect for a wind turbine. Data
% is from three different wind sensors at 80m. Temperature is also recorded
% at 3m height.  Data is logged every hour.

% Copyright 2013 The MathWorks, Inc.

%% Handle No-Input Case
if nargin == 0
  % If user doesn't supply a file name, request one
  [fname, pname] = uigetfile('*.txt');
  filename = fullfile(pname, fname);
  % Check to make sure input is a string
  validateattributes(filename, {'char'}, {'row'})
  % Check to make sure file exists
  if ~exist(filename, 'file')
    error('File "%s" cannot be found', filename);

%% Read in Turbine Data from Text File

% Function autogenerated from import tool
[~, fname, ~] = fileparts(filename);
[time,velS1,velS2,velS3,tempS] = importWindDataFcn(filename);

%% Average Wind Speed for Different Sensors
velAvg = mean([velS1, velS2, velS3], 2);

%% Determine Icing Conditions
% Remove any readings effected by icing which results in extremely
% inaccurate values biased towards zero.  Icing conditions are when
% tavg < tIce and vavg < vIce.

tIce = 2;
vIce = 1;

% Comparing to the critical values
idxTIce = tempS < tIce;
idxVIce = velAvg < vIce;

idxIce = idxTIce & idxVIce ;

% Remove values related to icing
time(idxIce)   = [];
tempS(idxIce)  = [];
velAvg(idxIce) = [];

%% Distribution of Wind Speeds at Hub Height
% Use a weibull distribution to fit the distribution of wind speeds which
% is known to often give a good fit to wind speed distributions.

% Plotting a histogram of wind speeds
dv = 0.5;
vbins = 0:dv:ceil(max(velAvg));

% Plotting a histogram of wind speeds
figure; hist(velAvg, vbins);
xlabel('wind velocity (m/s)'); ylabel('count');
title(['Wind Speed Distribution from ', fname]);

% Calculate probability of wind speed range
nelements = hist(velAvg, vbins);
probvbins = nelements/sum(nelements);        % Probability of a given velocity range

%% Defining the Turbine Power Curve
% To calculate average turbine power and capacity factor, we need to make
% some assumptions regarding the wind turbine model and its power curve.
% We will assume a 1MW wind turbine and the following turbine power
% curve.

% Turbine power curve coefficents
prated = 1e6;     % wind turbine rated power (W)
vin = 2;          % cut-in speed (m/s)
vr = 14;          % rated output speed (m/s)
vout = 25;        % cut-out speed (m/s)

% Calculating power curve
powervbins = prated*(vbins.^2 - vin^2)/(vr^2 - vin^2);
powervbins(vbins <= vin) = 0;
powervbins(vbins > vout) = 0;
powervbins(vbins >= vr & vbins <= vout) = prated;

%% Calculating Average Turbine Power and Capacity Factor
% Capacity factor is ratio of the actual output of a turbine over a period
% of time and its potential output if it had operated at full capacity the
% entire time. Typical capacity factor range from 20-50% depending on
% location and wind turbine.

% Integrate power at given velocity * velocity probability distribution
% function over range of possible velocities

% Calculate average power by summing the products of vel probability and power
avgPower = sum(probvbins .* powervbins);    % (W)

% Calculating capacity factor (average power / rated power)
cf = avgPower / prated;

disp(['Assumed wind turbine rated power (MW): ', num2str(prated/1e6)]);
disp(['Averaged turbine power (kW): ', num2str(avgPower/1e3)]);
disp(['Capacity factor (%): ', num2str(cf*100)]);

%% Combine into a Structure
% We will combine the information into a structure for easy data
% management.     = time;
windData.temp     = tempS;
windData.vavg     = velAvg;
windData.avgPower = avgPower;       = cf;
windData.filename = fname;

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