BlueM.MPC application: Difference between revisions

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[[File:Setup_BlueMMPC_englisch.png|thumb|BlueM.MPC modules]]
[[File:Setup_BlueMMPC_englisch.png|thumb|BlueM.MPC modules]]
[[File:Workflow_BlueMMPC_deutsch.png|thumb|BlueM.MPC workflow]]
[[File:Workflow_BlueMMPC_deutsch.png|thumb|BlueM.MPC workflow]]
BlueM.MPC is a modular software consisting of three modules. The supervising module '''BlueM.MPC''' coordinates work and data flow. Module '''SWMM5''' represents the process model which is used for the evaluation of the objective function that is required by the optimization module '''BlueM.Opt'''. Data exchange between modules is based on text files.
BlueM.MPC is a modular software consisting of three modules. The supervising module '''BlueM.MPC''' coordinates work and data flow. Module '''SWMM5''' represents the process model which is used for the evaluation of the objective function that is required by the optimization module '''[[BlueM.Opt]]'''. Data exchange between modules is based on text files.


==Dataset==
==Dataset==
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[[File:BlueMMPC_UserForm.png|thumb|BlueM.MPC GUI screenshot]]
[[File:BlueMMPC_UserForm.png|thumb|BlueM.MPC GUI screenshot]]


After starting the application '''MPC.exe''' a user form is opened. In this form all relevant information for the process control has to be filled in. After pressing the button ''Init BlueM.Opt'' the GUI of the optimizer '''BlueM.Opt''' is launched. The user selects an optimization algorithm and after setting the relevant optimization parameters the MPC simulation will start from there.
After starting the application '''MPC.exe''' a user form is opened. In this form all relevant information for the process control has to be filled in. After pressing the button ''Init BlueM.Opt'' the GUI of the optimizer '''[[BlueM.Opt]]''' is launched. The user selects an optimization algorithm and after setting the relevant optimization parameters the MPC simulation will start from there.


The following informations are required in the BlueM.MPC form:
The following informations are required in the BlueM.MPC form:
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* ''Output Folder.'' Path of the folder for results and log-files.
* ''Output Folder.'' Path of the folder for results and log-files.
* ''Start.'' Date and time of the start of the MPC simulations.
* ''Start.'' Date and time of the start of the MPC simulations.
* ''Stop.'' Datum und Uhrzeit des Endzeitpunkts für die modellprädiktive Steuerung.
* ''Stop.'' Date and time of the end of the MPC simulations.
* ''Control step.'' Größe des Steuerungszeitschritts in Minuten.
* ''Control step.'' Length of the control horizon in minutes.
* ''Evaluation horizon.'' Größe des Evaluierungshorizonts in Stunden.
* ''Evaluation horizon.'' Length of the evaluation horizon in hours.
* ''Forecast handling.'' Auswahl der Methode, mit der ermittelt wird, wie der Zeitdifferenz zwischen Vorhersagehorizont und Evaluierungshorizont umgegangen werden soll (siehe Abbildung 3.3). Der Benutzer kann derzeit zwischen drei Methoden wählen: (1) Alle Zuflusswerte zu Null setzen, (2) Mittelwerte des Vorhersagehorizonts ansetzen oder (3) den letzten Wert des Vorhersagehorizonts verwenden.
* ''Forecast handling.'' Selection of method, that determines how the time difference between the end of the forecast and the evaluation horizon is handled (see [[BlueMMPC_TimeHorizons]]). The user can choose between three methods:  
* ''Objective function threshold.'' Optionaler Wert, wenn Zielfunktionswerte gegen den Wert Null minimiert werden (z.B. bei der Minimierung der Entlastungsabflüsse), um die exzessiven Rechenzeiten bei den Simulationsstudien zu vermindern. Es kann ein Schwellwert eingegeben werden, mit dem der berechnete Zielfunktionswert des ersten Simulationslaufs verglichen wird. Ist der Zielfunktionswert kleiner als der Schwellwert, wird die Iteration nicht durchgeführt.
# Set all inflow values to zero.
# Set all inflow values to the average of the forecast horizon of the node.
# Use the last value of the forecast horizon.
* ''Objective function threshold.'' An optional value to speed up the simulation can be set in cases where objective functions values are minimized towards zero (which is for example the case when overflow volumes are minimized). The user defines a threshold value, which is compared in each control loop to the calculated objective function of the first simulation run. If the calculated value is smaller than the given threshold value, the iterative calculation of optimal control values is not necessary.

Revision as of 02:06, 20 December 2010

BlueM.MPC modules
BlueM.MPC workflow

BlueM.MPC is a modular software consisting of three modules. The supervising module BlueM.MPC coordinates work and data flow. Module SWMM5 represents the process model which is used for the evaluation of the objective function that is required by the optimization module BlueM.Opt. Data exchange between modules is based on text files.

Dataset

Application of BlueM.MPC requires seven input files:

Process control:

Optimization:

  • OPT-Datei: Definition of optimization parameters
  • ZIE-Datei: Definition of objective function
  • MOD-Datei: Localization / identification of optimzation parameters in inp

Process model:

Simulation

BlueM.MPC GUI screenshot

After starting the application MPC.exe a user form is opened. In this form all relevant information for the process control has to be filled in. After pressing the button Init BlueM.Opt the GUI of the optimizer BlueM.Opt is launched. The user selects an optimization algorithm and after setting the relevant optimization parameters the MPC simulation will start from there.

The following informations are required in the BlueM.MPC form:

  • Input File. Path and file name of the process model (INP-File).
  • Output Folder. Path of the folder for results and log-files.
  • Start. Date and time of the start of the MPC simulations.
  • Stop. Date and time of the end of the MPC simulations.
  • Control step. Length of the control horizon in minutes.
  • Evaluation horizon. Length of the evaluation horizon in hours.
  • Forecast handling. Selection of method, that determines how the time difference between the end of the forecast and the evaluation horizon is handled (see BlueMMPC_TimeHorizons). The user can choose between three methods:
  1. Set all inflow values to zero.
  2. Set all inflow values to the average of the forecast horizon of the node.
  3. Use the last value of the forecast horizon.
  • Objective function threshold. An optional value to speed up the simulation can be set in cases where objective functions values are minimized towards zero (which is for example the case when overflow volumes are minimized). The user defines a threshold value, which is compared in each control loop to the calculated objective function of the first simulation run. If the calculated value is smaller than the given threshold value, the iterative calculation of optimal control values is not necessary.
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