Here is the work flow:
1.Read the CSV data in MATLAB with the "t" and "i(t)" column header as a table
x = readtable("https://www.mathworks.com/matlabcentral/answers/uploaded_files/1537480/data.csv", "VariableNamingRule", "preserve")
2. Calculate the FFT
Plot the data
figure
plot(x.t, x.("i(t)"))
Since your data is not uniformly sampled, we need an interpolation
ts = diff(x.t(1:2)); % sampling time based on 1st two points (adjust this if necessary)
t = x.t(1):ts:x.t(end); % uniform time points
t0 = x.t;
y0 = x.("i(t)");
% t0 need to be unique
[tu, ia] = unique(t0);
yu = y0(ia);
y = interp1(tu, yu, t); % interplate the data
hold on
plot(t, y);
legend("original", "interp")
3. Determine the fundamental frequency and compute THD for the current signal.
p = 20*log10(abs(fft(y))); % log scale in dB
figure
f = (0:length(p)-1)/ts;
plot(f, p);
xlim(f([1 50])); % zoom in first 0 50 bins
% find the peak
[pmax, imax] = max(p);
hold on
plot(f(imax), p(imax), 'r*')
% Harmonic freq
f(imax)
4. Calculate the Displacement Power Factor (DPF) and Distortion Power Factor (DPFd).
Try out the rest with the definition of THD, DPF and DPFd
