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WP1.2 Coordination Meeting July 15, 2020
Meeting Report WP1.2 ‘Modelica library for MPC’
Subject: WP1.2
Date: 15-07-2020
Location: Skype for Business
Minutes taken by: Lieve Helsen (KU Leuven)
Approved
4 models selected to start MPC testing
merged to the master – READY! (Dave)
merged to the master in IDEAS – READY! (Filip & Javier), BOPTEST case almost ready.
In pull request, update needed for zone identifiers, no progress (Javier).
Managed to compile the model with JModelica, simulation with JModelica does not run (action Iago/Javier). Have a look at the solvers used. Javier will point to the branch with the latter developments in the associated issue, so other can have a look into that.
bulk is ready, just a few comments that still need to be figured out, can be merged on the short term (Javier/Filip).
Tao is processing the feedback from Dave. Pull request will be sent to Dave in short term.
Sen sent a new version to Iago. Iago starts a detailed review.
Yeonjin finalized preliminary building models and starts now comparison with measured data to calibrate some parameters. Ready for review by end of 2020 (Konstantin).
Emulators overview:
Choice between TMYx (1946-2018) and TMY3 (1973-2005) weather files. We have a data reader for TMY3 in IBPSA. Both will be compared in the representative days/weeks selection (action PNNL - Yan). No update.
Dave is working on a new version in Docker container that uses Python 3 and PyFMI (which can be installed easily), no JModelica-compiled image needed anymore:
- Unit tests are passing for BOPTEST Docker container utilizing Python 3.
- What is more difficult is the update of the parser that creates a new FMU (uses JModelica, which uses Python 2). Dave is working on this, the process works with Linux, not yet with Windows.
to be used for grey and black box model identification (training data that differ from test data). No further progress (Dave). To be discussed in breakout session.
Autoregressive model based on measurements and Q-Q mapping have been tried. Behaviour of the standard deviation has been studied. The error is too large for extreme temperatures. To be continued (Jesus/Aritz).
Too early for contest now, targeted for 2022.
No update.
Harald brought up issue 213: Method of handling event updates by introducing a sampler with modified sample period. Solution: event update function is available in pyfmi or compile the model as co-simulation FMU. Dave suggests to do the latter, see conclusion in issue 213. Filip suggests that we model as much as possible in Modelica and look for the best solution for each case. Specifically for the hysteresis block we could reformulate the model block. The easiest way to fix is adding a filter on the input.
Broaden the user space (e.g. to Machine Learning people). How to reach these people? Jan: make a first suggestion. Cfr OpenAIGym, to be presented. This will be included in the program of plenary session of the next IBPSA Project 1 (on-line) meeting in October 2020.
a. Javier & Lieve submitted an abstract for BS2021: Reinforced Model Predictive Control for Building Energy Management.
b. Filip, Damien & Lieve submitted an abstract for BS2021: Automated workflows for optimal design and control of buildings using Modelica.
c. Konstantin, Toa & Krzysztof submitted an abstract for BS2021 with focus on parallel computation.
d. Dave thinks about a journal paper on BOPTEST.
i. Spreadsheet for internal reporting of BOPTEST test cases
ii. Public reporting (limited information, end-user agreement)
iii. MPC competition: how to set up?
iv. How to deal with uncertainties: forecast of weather, loads, occupants?
v. How to generate weather data for training grey/black box models?
vi. Workshop introducing BOP-TEST at BS2021 (September 2021), as a follow-up of paper at BS2019 in Rome, incl. inspiration towards use cases such as: training building operators, assist teaching ...
vii. How can data be used in MPC?