Residential Solar Pre-Cooling Tool (RESPCT)

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RESPCT is an online web application that enables you simulate solar pre-cooling for a range of exsiting buildings in Australian building stock.

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pre-cooling and solar pre-cooling background

Pre-cooling means running the air conditioning (AC) before peak periods, and reducing the indoor temperautre below the temperature that is usaully set by occupants. The reduction of indoor temperature then reduces the temperature of thermal mass in the building, and the cooled down thermal mass results in lower cooling demand later in the day.

If the surplus PV generation from the rooftop PV system is used to pre-cool the building instead of the imported electricity from the grid, it is defined as solar pre-cooling. to learn more about pre-cooling and solar pre-cooling please refer to the following papers:

• Demand response via pre-cooling and solar pre-cooling: A review
• Consumer cost savings, improved thermal comfort, and reduced peak air conditioning demand through pre-cooling in Australian housing

Overview of the tool

RESPCT is an online web application that allows you simulate pre-cooling and solar pre-cooling for a range of existing buildings in Australian building stock. It has a database of the thermal behavior of the available buildings that allows you simulate the AC demand, indoor temperature, electricity cost, and the thermal discomfort index.

Summary page and statistics

The tool has two tabs. Be selecting the Solar pre-cooling potential in Australia at the top left, the user can see a range of statistics about the current building in Australia, and their solar pre-cooling potential.

How to use the simulation tool

By clicking on Simulation tool tab in the top left, the simulation tool appears. The user need to answer to a few questions.

Create thermal model

The first step is to create the thermal model of the building. The user can choose the location, star rating, construction weight, dwelling type, and floor area.

Define occupied periods

There are fields for the user to enter their typical occupancy patterns. It is done easily be selecting the occupied periods in the checkbox.

Define ideal indoor temperature

The preferred indoor temperature during occupied hours and acceptable deviation from the ideal temperature is done under the Ideal indoor temperature button.

Tariff structure

There is a database of the available tariffs in Australia, from which the user can choose.

Air conditioning excluded demand

There is a database of AC excluded net demand profiles from around 450 Australian households. The user can choose the demand profile that is similar to their consumption. The result of solar pre-cooling is sensitive to the demand profile, and you can try different demand profiles to understand the effect of changing the behaviour on the potential savings.

Air condition and PV system

PV generation and the amount of surplus PV generation after meeting households demand must be available for simulating solar pre-cooling. For simulating the performance of the rooftop PV system, the user needs to enter the rated capacity of the PV system, and the orientaion of the panels.

Adding the created case study

After entering all the information, the user must choose a name for the case study, and click on Add the case study. The user can add as many case studies as they want. For example, two case that are similar from all aspects but they have different star rating. This helps the user understand how much the solar pre-cooling potential changes if they renovate their building and implement some energy efficient measures. It is also possible to delete all the case studies by clicking on Clean all case studies.

Running the simulation

The last step is to run the solar pre-cooling simulation by clicking on Run solar pre-cooling.

Visualization of the reuslts

The user can choose different figures from the dropdown to visualize the result of solar pre-cooling. The avaialable figures are AC demand, monthly cost savings, thermal discomfort reduction, and surplus PV generation.

Useful links

Nothing helps as much as examples.

• This is a great guide that provides a brief overview of all the tools we use in this template.
• All of the tooling is based on UNSW CEEM Python Package Template

Documentation

Quick start

Check out the Documentation to understand the algorithms and datasets used in RESPCT, and for guide on to use RESPCT.

Basic

Updating repo info

Poetry

Poetry is used for dependency management, dependency resolution and can also be used as a build tool.

1. Install poetry
   • Edit the project info in pyproject.toml, or delete it and use poetry init to start from scratch (if you are proceeding to the next few sections, it is best not to delete the existig pyproject.toml)
   • You can add dependencies in the pyproject.toml or use the command line:
     • You can add a core dependency via poetry add, e.g. poetry add pandas
     • You can add dependencies to a group (adding to a group is optional) using poetry add pytest --group test
     • You can install the dependencies from poetry.lock, including optional groups, using poetry install --with=test
     • You can update dependencies and create a poetry.lock file using poetry update
   • Run scripts with poetry run, or jsut spawn a shell in the poetry virtual environment using poetry shell and then run your code
   • Commit pyproject.toml and poetry.lock to version control

Testing

1. To install testing dependencies, use poetry install --with=test
2. Put your tests in tests/
3. Run your tests by running pytest in the project directory
4. Test coverage will be in tests/htmlcov/index.html

Intermediate

Linters, Auto-formatting and pre-commit

Because code shouldn't look awful. We will be using isort (import sorting), flake8 (python linter) and black (an autoformatter) via pre-commit.

pre-commit streamlines creating pre-commit hooks, which are run prior to a commit being accepted by git (locally). This way, your code won't be committed if there are style issues (some of which will be automatically addressed by black or isort, after which you must stage any further changes).

1. Install the style packages using poetry install --with=style
2. (Optional) Configure any additional pre-commit hooks in the YAML
3. Run pre-commit install to install the hooks
4. To run manually, you can run pre-commit run -a. Alternatively, these hooks will run as you try and commit changes
5. (Optional) Install black extensions that auto-format on save in your favourite IDE

Automated testing and publishing to PyPI

Both of these can be achieved via GitHub Actions.

Note that some testing config is specified in the pyproject.toml.

1. The workflow is located here. It is commented to give you an understanding of what it does
   1. Automatically runs linting and autoformatting as above
   2. If that passes, then runs your code tests across Mac and Ubuntu for a couple of Python versions
   3. If a GitHub release is created based on a Git tag, it will build the package and upload to PyPI
      • To get this to work, you will need to add your PyPI username and password as GitHub secrets
2. Uncomment the lines specified. This should allow the workflow to run on a push, pull-request or when manually triggered. Note that publishing to PyPI is only triggered on a release
3. Activate the workflow. Do this by navigating to the Actions tab, selecting ... and activating it.

Advanced

If you've made it this far, well done. Prepare for the most tricky bit: documentation

This section is a WIP. We will add to it as we come across good resources.

Documentation

Documentation is located in the docs folder.

This project uses:

1. Sphinx to generate documentation. Sphinx is based on reStructuredText.
   • We use several Sphinx extensions that make using Sphinx easier
     • autodoc which will help you automatically generate the documentation from the docstrings in your code
     • napoleon which lets you write docstrings in your code using NumPy or Google style docstrings (as opposed to reStructuredText)
   • Sphinx is configured in conf.py
2. MyST, a parser which optionally lets you write your documentation using Markdown. If you know Markdown, this can reduce, but not eliminate, the need for reStructuredText.
3. readthedocs to host our documentation online. You'll need to link RtD to your repo (see here). Settings can be configured in the YAML

Gotcha: clearing your browser cache

If you make changes to your docs, successfully build it locally (see below) or on RtD and then see that no change has been made, your browser may be caching the old version of the docs. Clear your browser cache and then try again.

Building locally

First, install the packages required for buildings docs using poetry install --with=docs

You can test whether your documentation builds locally by using the commands offered by the Makefile. To do this, change directory to docs and run make to see build options. The easiest option is make html.

Sphinx tutorials

There is a fair bit to learn to be able to write docs. Even if you use MyST, you will need to learn about roles and directives.

Here are some tutorials:

• A tutorial prepared for PyCon 2021
• The official Sphinx tutorial

Examples

Tool Config

• flake8 is configured by .flake8
• pytest, isort and mypy (not included) can be configured in the pyproject.toml
• See relevant sections above for config for pre-commit, read-the-docs and Sphinx

Contributing

Interested in contributing? Check out the contributing guidelines, which also includes steps to install your_package for development.

Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

RESPCT was created by Shayan Naderi. It is licensed under the terms of the MIT.

Credits

This template was created using cookiecutter, the py-pkgs-cookiecutter template and using Marwan Debbiche's excellent walkthrough