IBPSA Project 1 - BOPTEST

Building Optimization Performance Tests

Visit the BOPTEST Home Page for more information about the project, software, and documentation.

This repository contains code for the Building Optimization Performance Test framework (BOPTEST) that is being developed as part of the IBPSA Project 2 and was previously developed as part of the IBPSA Project 1.

Structure

• /testcases contains test cases, including docs, models, and configuration settings.
• /examples contains code for interacting with a test case and running example tests with simple controllers. Those controllers are implemented in Python (3.9) and Julia (Version 1.0.3).
• /parsing contains code for a script that parses a Modelica model using signal exchange blocks and outputs a wrapper FMU and KPI json.
• /testing contains code for unit and functional testing of this software. See the README there for more information about running these tests.
• /data contains code for generating and managing data associated with test cases. This includes boundary conditions, such as weather, schedules, and energy prices, as well as a map of test case FMU outputs needed to calculate KPIs.
• /forecast contains code for returning boundary condition forecast, such as weather, schedules, and energy prices.
• /kpis contains code for calculating key performance indicators.
• /docs contains design documentation and delivered workshop content.
• /baselines contains scripts and data for baselining KPIs for test cases with their embedded control.
• /bacnet contains code for a bacnet interface.

Quick-Start to Deploy a Test Case

1. Download this repository.
2. Install Docker and Docker Compose.
3. To build and deploy a test case, use the following commands within the root directory of the extracted software:

• Linux or macOS: $ TESTCASE=<testcase_name> docker-compose up
• Windows PowerShell: > ($env:TESTCASE="<testcase_name>") -and (docker-compose up)
• A couple notes:
  • Replace <testcase_name> with the name of the test case you wish to deploy. Test case names can be found in the "testcases" directory or on the "Test Cases" web page.
  • The first time this command is run, the image boptest_base will be built. This takes about a minute. Subsequent usage will use the already-built image and deploy much faster.
  • If you update your BOPTEST repository, use the command docker rmi boptest_base to remove the image so it can be re-built with the updated repository upon next deployment.
  • TESTCASE is simply an environment variable. Consistent with use of docker-compose, you may also edit the value of this variable in the .env file and then use docker-compose up.

4. In a separate process, use the test case API defined below to interact with the test case using your test controller. Alternatively, view and run an example test controller as described below.
5. Shutdown the test case by the command docker-compose down executed in the root directory of this repository

Run an example test controller:

• For Python-based example controllers:

  • Optionally, add the directory path to the root of this repository to the PYTHONPATH environment variable. Use export PYTHONPATH=$(pwd):$PYTHONPATH. Note: The Python example updates the PYTHONPATH just in time.
  • Build and deploy testcase1. Then, in a separate terminal, use $ cd examples/python/ && python testcase1.py to test a simple proportional feedback controller on this test case over a two-day period.
  • Build and deploy testcase1. Then, in a separate terminal, use $ cd examples/python/ && python testcase1_scenario.py to test a simple proportional feedback controller on this test case over a test period defined using the /scenario API.
  • Build and deploy testcase2. Then, in a separate terminal, use $ cd examples/python/ && python testcase2.py to test a simple supervisory controller on this test case over a two-day period.

• For Julia-based example controllers:

  • Build and deploy testcase1. Then, in a separate terminal, use $ cd examples/julia && make build Script=testcase1 && make run Script=testcase1 to test a simple proportional feedback controller on this test case over a two-day period. Note that the Julia-based controller is run in a separate Docker container.
  • Build and deploy testcase2. Then, in a separate terminal, use $ cd examples/julia && make build Script=testcase2 && make run Script=testcase2 to test a simple supervisory controller on this test case over a two-day period. Note that the Julia-based controller is run in a separate Docker container.
  • Once either test is done, use $ make remove-image Script=testcase1 or $ make remove-image Script=testcase2 to removes containers, networks, volumes, and images associated with these Julia-based examples.

Test Case RESTful API

• To interact with a deployed test case, use the API defined in the table below by sending RESTful requests to: http://127.0.0.1:5000/<request>
• The API will return a JSON in the form {"status":<status_code_int>, "message":<message_str>, "payload":<relevant_return_data>}. Status codes in "status" are integers: 200 for successful with or without warning, 400 for bad input error, or 500 for internal error. Data returned in "payload" is the data of interest relvant to the specific API request, while the string in "message" will report any warnings or error messages to help debug encountered problems.

Example RESTful interaction:

• Receive a list of available measurement names and their metadata: $ curl http://127.0.0.1:5000/measurements
• Receive a forecast of boundary condition data: $ curl http://127.0.0.1:5000/forecast
• Advance simulation of test case 2 with new heating and cooling temperature setpoints: $ curl http://127.0.0.1:5000/advance -d '{"oveTSetRooHea_u":293.15,"oveTSetRooHea_activate":1, "oveTSetRooCoo_activate":1,"oveTSetRooCoo_u":298.15}' -H "Content-Type: application/json". Leave an empty json to advance the simulation using the setpoints embedded in the model.

Interaction	Request
Advance simulation with control input and receive measurements.	POST advance with optional arguments <input_name_u>:<value>, and corresponding <input_name_activate>:<0 or 1>, where 1 enables value overwrite and 0 disables (0 is default)
Initialize simulation to a start time using a warmup period in seconds. Also resets point data history and KPI calculations.	PUT initialize with required arguments start_time=<value>, warmup_period=<value>
Receive communication step in seconds.	GET step
Set communication step in seconds.	PUT step with required argument step=<value>
Receive sensor signal point names (y) and metadata.	GET measurements
Receive control signal point names (u) and metadata.	GET inputs
Receive test result data for the given point names between the start and final time in seconds.	PUT results with required arguments point_names=<list of strings>, start_time=<value>, final_time=<value>
Receive test KPIs.	GET kpi
Receive test case name.	GET name
Receive boundary condition forecast from current communication step for the given point names for the horizon and at the interval in seconds.	PUT forecast with required arguments point_names=<list of strings>, horizon=<value>, interval=<value>
Receive boundary condition forecast available point names and metadata.	GET forecast_points
Receive current test scenario.	GET scenario
Set test scenario. Setting the argument time_period performs an initialization with predefined start time and warmup period and will only simulate for predefined duration.	PUT scenario with optional arguments electricity_price=<string>, time_period=<string>. See README in /testcases for options and test case documentation for details.
Receive BOPTEST version.	GET version
Submit KPIs, other test information, and optional string tags (up to 10) to online dashboard. Requires a formal test scenario to be completed, initialized using the PUT scenario API.	POST submit with required argument api_key=<string> and optional arguments tag#=<string> where # is an integer between 1 and 10. The API key can be obtained from the user account registered with the online dashboard.

Development

Community development is welcome through reporting issues and/or making pull requests. If making a pull request, make sure an issue is opened first, name the development branch according to the convention issue<issue#>_<descriptor>, and cite in the pull request which issue is being addressed.

This repository uses pre-commit to ensure that the files meet standard formatting conventions (such as line spacing, layout, etc). Presently only a handful of checks are enabled and will expanded in the near future. To run pre-commit first install pre-commit into your Python version using pip pip install pre-commit. Pre-commit can either be manually by calling pre-commit run --all-files from within the BOPTEST checkout directory, or you can install pre-commit to be run automatically as a hook on all commits by calling pre-commit install in the root directory of the BOPTEST GitHub checkout.

Additional Software

Deployment as a Web-Service

BOPTEST is delpoyed as a web-service using BOPTEST-Service. See the related section in the user guide for getting started.

OpenAI-Gym Environment

An OpenAI-Gym environment for BOPTEST is implemented in ibpsa/project1-boptest-gym. See the documentation there for getting started.

BACnet Interface

A BACnet interface for BOPTEST is implemented in the /bacnet directory of this repository. See the /bacnet/README.md there for getting started.

Results Dashboard

A proposed BOPTEST home page and dashboard for creating accounts and sharing results is published here https://xd.adobe.com/view/0e0c63d4-3916-40a9-5e5c-cc03f853f40a-783d/.

Use Cases and Development Requirements

See the wiki for use cases and development requirements.

Publications

To cite, please use:

D. Blum, J. Arroyo, S. Huang, J. Drgona, F. Jorissen, H.T. Walnum, Y. Chen, K. Benne, D. Vrabie, M. Wetter, and L. Helsen. (2021). "Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings." Journal of Building Performance Simulation, 14(5), 586-610.

Additional publications:

See the Publications page.