JModelica error in transfer_optimization_problem(…)JModelica refuses to load libhsl.soPython/Pyomo error within JModelicaUse JModelica in Spyder/PythonAdding additional libraries to MODELICAPATH in JModelicajmodelica optimization has runtime errorCannot run JModelica demos on WindowsIs it possible to suppress the output of the JModelica solver?Cannot install JModelica on UbubtuEvent info JModelica simulationJModelica on Ubuntu 18.04

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JModelica error in transfer_optimization_problem(…)


JModelica refuses to load libhsl.soPython/Pyomo error within JModelicaUse JModelica in Spyder/PythonAdding additional libraries to MODELICAPATH in JModelicajmodelica optimization has runtime errorCannot run JModelica demos on WindowsIs it possible to suppress the output of the JModelica solver?Cannot install JModelica on UbubtuEvent info JModelica simulationJModelica on Ubuntu 18.04






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0















I have a Modelica model and I want to use JModelica with CasADi to solve a parameter estimation problem. I have my model in .mo files and my optimization problem in a .mop file and when I try to use the python function transfer_optimization_problem(...) I get an error



Error in flattened model:
The DAE system has 125 equations and 121 free variables.


I understand that the system is overdetermined but I have no idea where to start to solve it and I can't find any logs that pins down the problem.



How do I know where to either introduce more free variables or remove equations?



It works if I use a simpler model and the model itself is possible to simulate by translating it to a fmu.



The optimization specification:



optimization lab_sun_wind_optimization(startTime=0, finalTime=1.16000e+07)

extends lab_sun_wind(
R(free=true, min=0.1, max=1.0),
winAr(free=true, min=0.01, max=0.05),
coeffV2Dt(free=true, min=0.0001, max=0.0005)
);

end lab_sun_wind_optimization;


The model:



model lab_sun_wind

import BuildingLib.Buildings;

// Parameters
parameter Real R = 1.0;
parameter Real winAr = 0.02;
parameter Real coeffV2Dt = 0.0002;

// Components
Buildings.SimpleAdapTypeLabSunWind b(R=R, winAr=winAr, coeffV2Dt=coeffV2Dt);

// Inputs
connector RealInput = input Real;
RealInput dtt;
RealInput dirRad;
RealInput sunAz;
RealInput sunH;
RealInput diffRad;
RealInput windSpeed;
RealInput ventHigh;
RealInput elPer;
RealInput sp;

equation
connect(dtt, b.buildingInp.dtt);
connect(dirRad, b.buildingInp.dirRad);
connect(sunAz, b.buildingInp.sunAz);
connect(sunH, b.buildingInp.sunH);
connect(diffRad, b.buildingInp.diffRad);
connect(windSpeed, b.buildingInp.windSpeed);
connect(ventHigh, b.buildingInp.ventHigh);
connect(elPer, b.buildingInp.elPer);
connect(sp, b.buildingInp.sp);

end lab_sun_wind;


I can't show how Buildings.SimpleAdapTypeLabSunWind looks like since it is company code.










share|improve this question






























    0















    I have a Modelica model and I want to use JModelica with CasADi to solve a parameter estimation problem. I have my model in .mo files and my optimization problem in a .mop file and when I try to use the python function transfer_optimization_problem(...) I get an error



    Error in flattened model:
    The DAE system has 125 equations and 121 free variables.


    I understand that the system is overdetermined but I have no idea where to start to solve it and I can't find any logs that pins down the problem.



    How do I know where to either introduce more free variables or remove equations?



    It works if I use a simpler model and the model itself is possible to simulate by translating it to a fmu.



    The optimization specification:



    optimization lab_sun_wind_optimization(startTime=0, finalTime=1.16000e+07)

    extends lab_sun_wind(
    R(free=true, min=0.1, max=1.0),
    winAr(free=true, min=0.01, max=0.05),
    coeffV2Dt(free=true, min=0.0001, max=0.0005)
    );

    end lab_sun_wind_optimization;


    The model:



    model lab_sun_wind

    import BuildingLib.Buildings;

    // Parameters
    parameter Real R = 1.0;
    parameter Real winAr = 0.02;
    parameter Real coeffV2Dt = 0.0002;

    // Components
    Buildings.SimpleAdapTypeLabSunWind b(R=R, winAr=winAr, coeffV2Dt=coeffV2Dt);

    // Inputs
    connector RealInput = input Real;
    RealInput dtt;
    RealInput dirRad;
    RealInput sunAz;
    RealInput sunH;
    RealInput diffRad;
    RealInput windSpeed;
    RealInput ventHigh;
    RealInput elPer;
    RealInput sp;

    equation
    connect(dtt, b.buildingInp.dtt);
    connect(dirRad, b.buildingInp.dirRad);
    connect(sunAz, b.buildingInp.sunAz);
    connect(sunH, b.buildingInp.sunH);
    connect(diffRad, b.buildingInp.diffRad);
    connect(windSpeed, b.buildingInp.windSpeed);
    connect(ventHigh, b.buildingInp.ventHigh);
    connect(elPer, b.buildingInp.elPer);
    connect(sp, b.buildingInp.sp);

    end lab_sun_wind;


    I can't show how Buildings.SimpleAdapTypeLabSunWind looks like since it is company code.










    share|improve this question


























      0












      0








      0








      I have a Modelica model and I want to use JModelica with CasADi to solve a parameter estimation problem. I have my model in .mo files and my optimization problem in a .mop file and when I try to use the python function transfer_optimization_problem(...) I get an error



      Error in flattened model:
      The DAE system has 125 equations and 121 free variables.


      I understand that the system is overdetermined but I have no idea where to start to solve it and I can't find any logs that pins down the problem.



      How do I know where to either introduce more free variables or remove equations?



      It works if I use a simpler model and the model itself is possible to simulate by translating it to a fmu.



      The optimization specification:



      optimization lab_sun_wind_optimization(startTime=0, finalTime=1.16000e+07)

      extends lab_sun_wind(
      R(free=true, min=0.1, max=1.0),
      winAr(free=true, min=0.01, max=0.05),
      coeffV2Dt(free=true, min=0.0001, max=0.0005)
      );

      end lab_sun_wind_optimization;


      The model:



      model lab_sun_wind

      import BuildingLib.Buildings;

      // Parameters
      parameter Real R = 1.0;
      parameter Real winAr = 0.02;
      parameter Real coeffV2Dt = 0.0002;

      // Components
      Buildings.SimpleAdapTypeLabSunWind b(R=R, winAr=winAr, coeffV2Dt=coeffV2Dt);

      // Inputs
      connector RealInput = input Real;
      RealInput dtt;
      RealInput dirRad;
      RealInput sunAz;
      RealInput sunH;
      RealInput diffRad;
      RealInput windSpeed;
      RealInput ventHigh;
      RealInput elPer;
      RealInput sp;

      equation
      connect(dtt, b.buildingInp.dtt);
      connect(dirRad, b.buildingInp.dirRad);
      connect(sunAz, b.buildingInp.sunAz);
      connect(sunH, b.buildingInp.sunH);
      connect(diffRad, b.buildingInp.diffRad);
      connect(windSpeed, b.buildingInp.windSpeed);
      connect(ventHigh, b.buildingInp.ventHigh);
      connect(elPer, b.buildingInp.elPer);
      connect(sp, b.buildingInp.sp);

      end lab_sun_wind;


      I can't show how Buildings.SimpleAdapTypeLabSunWind looks like since it is company code.










      share|improve this question














      I have a Modelica model and I want to use JModelica with CasADi to solve a parameter estimation problem. I have my model in .mo files and my optimization problem in a .mop file and when I try to use the python function transfer_optimization_problem(...) I get an error



      Error in flattened model:
      The DAE system has 125 equations and 121 free variables.


      I understand that the system is overdetermined but I have no idea where to start to solve it and I can't find any logs that pins down the problem.



      How do I know where to either introduce more free variables or remove equations?



      It works if I use a simpler model and the model itself is possible to simulate by translating it to a fmu.



      The optimization specification:



      optimization lab_sun_wind_optimization(startTime=0, finalTime=1.16000e+07)

      extends lab_sun_wind(
      R(free=true, min=0.1, max=1.0),
      winAr(free=true, min=0.01, max=0.05),
      coeffV2Dt(free=true, min=0.0001, max=0.0005)
      );

      end lab_sun_wind_optimization;


      The model:



      model lab_sun_wind

      import BuildingLib.Buildings;

      // Parameters
      parameter Real R = 1.0;
      parameter Real winAr = 0.02;
      parameter Real coeffV2Dt = 0.0002;

      // Components
      Buildings.SimpleAdapTypeLabSunWind b(R=R, winAr=winAr, coeffV2Dt=coeffV2Dt);

      // Inputs
      connector RealInput = input Real;
      RealInput dtt;
      RealInput dirRad;
      RealInput sunAz;
      RealInput sunH;
      RealInput diffRad;
      RealInput windSpeed;
      RealInput ventHigh;
      RealInput elPer;
      RealInput sp;

      equation
      connect(dtt, b.buildingInp.dtt);
      connect(dirRad, b.buildingInp.dirRad);
      connect(sunAz, b.buildingInp.sunAz);
      connect(sunH, b.buildingInp.sunH);
      connect(diffRad, b.buildingInp.diffRad);
      connect(windSpeed, b.buildingInp.windSpeed);
      connect(ventHigh, b.buildingInp.ventHigh);
      connect(elPer, b.buildingInp.elPer);
      connect(sp, b.buildingInp.sp);

      end lab_sun_wind;


      I can't show how Buildings.SimpleAdapTypeLabSunWind looks like since it is company code.







      jmodelica






      share|improve this question













      share|improve this question











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      asked Mar 27 at 7:24









      Andreas SamuelssonAndreas Samuelsson

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