Typhoon HIL Forum - Recent questions in Helper

PSO optimization technique how to adapt this code properly for execution in the Typhoon HIL C-block.

Sat, 27 Sep 2025 13:29:01 +0000

Dear Typhoon HIL Team,

I am working on a research project titled “Photovoltaic MPPT Performance Adaptability to Partial Shading Resilience and Load Variations with PSO.” In MATLAB/Simulink, I have implemented and validated the PSO-based MPPT algorithm using a C-function block, and I now wish to port this into Typhoon HIL Control Center for hardware-in-the-loop testing and real-time verification.

My MATLAB code (attached below) takes PV voltage and current (Vpv, Ipv) as inputs and generates the duty cycle (D_out) as output. It uses persistent variables for swarm initialization, particle updates, personal/global best tracking, and smoothing of the duty cycle output.

I would like guidance on:

Code Structure: How to adapt my MATLAB C-function for Typhoon HIL’s C-block (syntax, supported functions, use of init() and step()).
Inputs/Outputs: Correct way to declare Vpv, Ipv as inputs and D_out as output, and how to connect the duty cycle output to PWM blocks.
Implementation Steps: The procedure to load and compile this code in the Schematic Editor, handle unsupported functions (e.g., rand, linspace), and properly manage persistent variables.
Verification: Best practices to confirm that the Typhoon C-block produces results consistent with MATLAB under partial shading and load variation tests.

My main goal is to compare MATLAB simulations with Typhoon HIL results under identical conditions for benchmarking MPPT performance. Any step-by-step instructions, references, or example templates would be greatly appreciated.

Thank you for your support.

Below, I have provided a detailed explanation of the MATLAB C-function block along with the points where I am seeking clarification:

1. Code Structure

In MATLAB, my MPPT logic is encapsulated in a C-function block with persistent variables for maintaining PSO states such as swarm positions, velocities, particle bests, and global best. Below is the complete implementation:

%% ------------------ PSO Parameters ------------------

persistent swarm iter stepCounter P_hist D_out_prev

% PSO constants

N = 30; % number of particles

maxIter = 300; % max iterations

c1 = 1.8; % cognitive factor

c2 = 1.8; % social factor

w_max = 0.9; % max inertia

w_min = 0.4; % min inertia

D_min = 0.05; % min duty cycle

D_max = 0.95; % max duty cycle

% Moving average for stability

avgWindow = 7;

updatePeriod = 1; % update every step

perturbMagnitude = 0.02; % small perturbation

%% ------------------ Initialization ------------------

if isempty(swarm)

D_sweep = linspace(D_min, D_max, N);

swarm.x = D_sweep; % particle positions (duty cycles)

swarm.v = zeros(1,N); % particle velocities

swarm.pBest = D_sweep; % personal bests

swarm.pBestVal = -inf(1,N); % personal best power

swarm.gBest = D_min; % global best duty cycle

swarm.gBestVal = -inf; % global best power

swarm.k = 1; % current particle index

iter = 1;

stepCounter = 0;

P_hist = zeros(1, avgWindow);

D_out_prev = swarm.gBest;

D_out = swarm.gBest;

return;

end

%% ------------------ Slow Update ------------------

stepCounter = stepCounter + 1;

if stepCounter < updatePeriod

D_out = D_out_prev;

return;

else

stepCounter = 0;

end

%% ------------------ Moving Average Power ------------------

P_hist = [P_hist(2:end), Vpv*Ipv];

P = mean(P_hist);

%% ------------------ Update Personal Best ------------------

if P > swarm.pBestVal(swarm.k)

swarm.pBest(swarm.k) = swarm.x(swarm.k);

swarm.pBestVal(swarm.k) = P;

end

%% ------------------ PSO Update ------------------

w = w_max - (w_max - w_min)*(iter/maxIter);

r1 = rand; r2 = rand;

swarm.v(swarm.k) = w*swarm.v(swarm.k) ...

+ c1*r1*(swarm.pBest(swarm.k)-swarm.x(swarm.k)) ...

+ c2*r2*(swarm.gBest - swarm.x(swarm.k));

swarm.x(swarm.k) = swarm.x(swarm.k) + swarm.v(swarm.k);

%% ------------------ Clamp Duty Cycle ------------------

swarm.x(swarm.k) = max(min(swarm.x(swarm.k), D_max), D_min);

%% ------------------ Move to Next Particle ------------------

swarm.k = swarm.k + 1;

if swarm.k > N

swarm.k = 1;

iter = iter + 1;

% ------------------ Update Global Best after all particles ------------------

[bestP, idx] = max(swarm.pBestVal);

swarm.gBest = swarm.pBest(idx);

swarm.gBestVal = bestP;

% ------------------ Small Random Perturbation ------------------

if mod(iter,20)==0

swarm.x = swarm.x + perturbMagnitude*(rand(1,N)-0.5);

swarm.x = max(min(swarm.x, D_max), D_min);

end

%% ------------------ Reset if maxIter ------------------

if iter > maxIter

D_sweep = linspace(D_min,D_max,N);

swarm.x = D_sweep;

swarm.v = zeros(1,N);

swarm.pBest = D_sweep;

swarm.pBestVal = -inf(1,N);

swarm.gBest = D_min;

swarm.gBestVal = -inf;

iter = 1;

end

%% ------------------ Smooth Duty Cycle Output ------------------

alpha = 0.2; % smoothing factor

D_out = alpha*swarm.gBest + (1-alpha)*D_out_prev;

D_out_prev = D_out;

end

function D_out = PSO_MPPT_PV_Stable(Vpv, Ipv)

Unexpected Model Behavior with Induction Motor Parameters

Wed, 23 Jul 2025 08:29:14 +0000

While working on controlling a three-phase squirrel cage induction machine in Typhoon HIL, I encountered an unusual issue.

Initially, I copied the induction machine block from one of the example models and started testing my MPC-based control algorithm. I forgot to update the motor parameters in the machine block to match those used in the MPC model. Despite this mismatch, the system worked to give outputs- speed was tracked and all that

However, when I later updated the induction machine block with the correct motor parameters to match those used in the MPC control model (Rs, Ls, Lm, etc.), the control performance drastically degraded — torque dropped, and overall behavior became unstable.

This led me to realize that the control algorithm only works when there's a large mismatch between the motor parameters in the MPC and those in the machine block. I’m unsure whether this is due to a modeling assumption, numerical issue, or internal handling of the motor block.

I’d appreciate any insight into why this might be happening or if there’s something I’ve missed

Below are the major equations used in the mpc algorithm which conforms with theory

sigma=(1.0-(Lm*Lm)/(Ls*Lr));
kr=(Lm/Lr);
ks=(Lm/Ls);
r_sigma=Rs+Rr*(kr*kr);
t_sigma=(sigma*Ls)/(r_sigma);

temp1 = t_sigma / (Ts + t_sigma);
temp2 = Ts / (Ts + t_sigma) * (1.0 / r_sigma);

Fr_real = (Lr / Lm) * (Fs_real + ik_real) * (Lm - (Lr * Ls / Lm));
Fr_imag = (Lr / Lm) * (Fs_imag + ik_imag) * (Lm - (Lr * Ls / Lm));

Fs_real = Fs_real + Ts * (v_real[x_opt] - Rs * ik_real);
Fs_imag = Fs_imag + Ts * (v_imag[x_opt] - Rs * ik_imag);

Tp = (3.0 / 2.0) * P * (Fsp_real * Isp_imag - Fsp_imag * Isp_real);

Fsp_mag = sqrt(Fsp_real * Fsp_real + Fsp_imag * Fsp_imag);

Fsp_real = Fs_real + (Ts * v_o1_real) - Rs * Ts * Isp_real;
Fsp_imag = Fs_imag + (Ts * v_o1_imag) - Rs * Ts * Isp_imag;

Create a single-phase microgrid

Mon, 02 Jun 2025 05:40:11 +0000

Hello! I'm new to this software and I don't know how to use it.

I need to develop a single-phase microgrid that includes the following elements: the utility distribution grid (Grid), a household - consumer (Variable Load), a photovoltaic system (PV Power Plant), and an energy storage system for the electricity produced by the PV system (Battery ESS). In Typhoon HIL, I must demonstrate that the photovoltaic panels on the house generate electricity when solar irradiance is present, and the surplus energy that the house does not consume should be stored in the battery system. When the PV panels stop generating electricity, the house should be powered from the stored battery energy. The idea is that I need to replicate these processes in Typhoon HIL for an exam. Please help me with detailed guidance on how to implement these processes. I do not understand how to use the Python code as shown here: https://ticket.typhoon-hil.com/kb/faq.php?id=110. I also don't understand what my professor wants with the Modbus client in HIL SCADA; why is it necessary?

Could you help me, please? I tried to watch all the videos from HIL for Microgrids and Communication Protocols courses, but they are to general.

Thank you!

DC microgrid

Wed, 21 May 2025 10:19:51 +0000

Please, i am going to design low voltage DC microgrid with PV battery storage system with wind and diesel in main grid connected mode and islanded mode i need some support. i made this system by mtalab but here look more hard

Can you make some help for me ?do you have any model example for low voltage DC microgrid

Issue with PV Panels Generic not responding to Irradiation profile

Wed, 02 Apr 2025 10:58:54 +0000

Hi everyone,

I am trying to implement an irradiation profile from a .txt file for the PV Panels Generic block using the macro variable in HIL SCADA. I followed the exact same approach as in the WindSpeed example, using the same code structure but with my own references. I am not getting any errors, and in the SCADA input, I can see that the irradiation variable changes according to my text file. However, the output power of the panel does not change. It seems like the input is not being received.

Has anyone encountered this issue before? Any suggestions on what might be going wrong?

Thanks in advance!

IEC61850 MMS server: stop simulation not disconnecting/stopping iec61850 mms server

Thu, 27 Mar 2025 07:12:40 +0000

I'm using example schematic of IEC61850 MMS server & with following script im able to connect the server & client & communicate points data but even after stopping the simulation the server & client are connected & communicating

here is a few line of code that connect client & server but does not disconnect them

        hil.load_model(file=cpd, vhil_device=False)

        hil.start_simulation() # client & server are connected here

        hil.wait_sec(30)

        hil.stop_simulation() # even after stopping simulation client & server are connected here

       print(is_simulation_running()) #prints False i.e simulation is not running

am I missing out on something which might close the server?

Symbolic Calculation in C funtion

Fri, 07 Feb 2025 08:58:22 +0000

Hello everyone
How to perform symbolic calculation using C-funtion in typhoon?

Solving a system of quadratic equation

Thu, 06 Feb 2025 06:23:02 +0000

Hello every overyone

I am trying to solve this system of quadratic equations in typhoon hil

% Va = 3, Vb = 2, Vc = 3

syms xb yb xc yc real

% Mise en equations

eq1 = (xb - Va)^2 + yb^2 == (Va - xc)^2 + yc^2; % Vab = Vac

eq2 = (xb - Va)^2 + yb^2 == (xb - xc)^2 + (yc - yb)^2; % Vab = Vbc

eq3 = xb^2 + yb^2 == Vb_mot^2;

eq4 = xc^2 + yc^2 == Vc^2;

% resolution

eqns = [eq1,eq2,eq3,eq4]; % regroupement des equations

vars = [xb yb xc yc]; % variables

sol = solve(eqns,vars); % resolution des equations

% % % % calcul des angles requis pour reequilibrer les tensions

theta_ab = double(max((atan2d(sol.yb,sol.xb)))); % angle entre a et b

theta_ac = double(max((atan2d(sol.yc,sol.xc)))); % angle entre a et c

theta_bc = 360-(theta_ab + theta_ac); % angle entew b et c

Unable to Initialize Analog Signals VHIL

Wed, 04 Dec 2024 17:51:18 +0000

Hello,

I am currently trying to run on the VHIL a model containing a FMU imported from a third party modelling environment.

When compiling and reloading the .tse model from the schematic editor into the HIL SCADA, the following error is reported in the message log: "Unable to initialize Analog Signals!".

Inside the model I am trying to compile, only SCADA input/output are present besides the FMU.

What could be the issue?

Thank you,

Luca

What will I be helping with?

Mon, 04 Nov 2024 16:36:40 +0000