基于离散时间频率增益传感器的P级至M级PMU模型的实现（Matlab代码实现）

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📋📋📋本文目录如下：🎁🎁🎁
目录
💥1 概述
📚2 运行结果
🎉3 参考文献
🌈4 Matlab代码实现

💥1 概述

低复杂度高精度P级到M级渐进式PMU模型，由Krzysztof Duda和Tomasz P. Zieliński设计。

基于离散时间频率增益传感器（DTFGT）和正弦斜率滤波器的P级至M级渐进式PMU模型的实现，以及在IEC/IEEE 60255-118-1标准动态调制测试中的应用。

📚2 运行结果

部分代码：

figure,

subplot(1,2,1), hold on

plot(fm, err_TVE_dF)

legend(text_legend_const,'Location','southeast')

xlabel('F_i_n (Hz)'), ylabel('TVE (%) for straightforward A and \phi estimation')

title(text_title)

set(gca,'YScale','log'),

axis tight, box on, grid on

subplot(1,2,2), hold on

plot(fm, err_TVE_dF_LS, '-')

legend(text_legend_const,'Location','southeast')

xlabel('F_i_n (Hz) '), ylabel('TVE (%) for LS based A and \phi estimation')

title(text_title)

set(gca,'YScale','log'),

axis tight, box on, grid on

figure,

subplot(1,2,1), hold on

plot(fm, err_Om_dF, '-')

legend(text_legend_const,'Location','southeast')

xlabel('F_i_n (Hz)'), ylabel('FE (Hz)'), title(text_title)

set(gca,'YScale','log'),

axis tight, box on, grid on

subplot(1,2,2), hold on

plot(fm, err_Rocof_dF_LS, '-')

legend(text_legend_const,'Location','southeast')

xlabel('F_i_n (Hz)'), ylabel('RFE (Hz/s)'), title(text_title)

set(gca,'YScale','log'),

axis tight, box on, grid on

end

%###########################################################

function [Phasor, PhasorLS, Omr, ROCOFr] = PMU(x, P, N0, F0)

% PMU implementation with a cascade of rectangular filters

% and the Discrete-Time Frequency-Gain Transducer (DTFGT)

% with the sine-shape slope filter

% x - sinusoidal signal x=A*cos(Om*n+p)

% P - number of rectangular filters in the prefilter cascade

% Phasor - estimated complex phasor reported at nominal frequency with straightforward amplitude and phase estimation

% PhasorLS - estimated complex phasor reported at nominal frequency with LS based amplitude and phase estimation

% Omr - estimated frequency in radians reported at nominal frequency

% ROCOFr - estimated ROCOF in radians per second reported at nominal frequency

Nx = length(x);

Fs = N0*F0; %Hz

t = (0:Nx-1)/Fs;

y = x.*exp(-1i*2*pi*F0*t); % down-shifted sinusoidal signal x=A*cos(Om*n+p), Om=2*pi*f0/fs

%% for LS solution

ND2 = N0/2-1; % only one nominal period, although it could be more for longer cascade

ND1 = -N0/2;

%% sin frequency slope h = [1/2 0 -1/2];

w0= pi/(N0/2);

L = N0/4;

h = [1/2 zeros(1,L-1) 0 zeros(1,L-1) -1/2];

%%

tr = 1:N0:Nx; % reporting times

Phasor = zeros(length(tr), P);

PhasorLS = zeros(length(tr), P);

Omr = zeros(length(tr), P);

ROCOFr = zeros(length(tr), P);

r0 = ones(1,N0)/N0; rp = 1;

for ind=1:P

🎉3 参考文献

部分理论来源于网络，如有侵权请联系删除。

[1]Krzysztof Duda (2023). P2M_PMU

🌈4 Matlab代码实现