Tools for performing common tasks on solar PV data signals
Project description
solar-data-tools
Latest Release |
|
License |
|
Build Status |
|
Code Quality |
|
Publications |
|
PyPI Downloads |
|
Conda Downloads |
|
Test-Coverage |
|
Tools for performing common tasks on solar PV data signals. These tasks include finding clear days in a data set, common data transforms, and fixing time stamp issues. These tools are designed to be automatic and require little if any input from the user. Libraries are included to help with data IO and plotting as well.
There is close integration between this repository and the Statistical Clear Sky repository, which provides a "clear sky model" of system output, given only measured power as an input.
See notebooks folder for examples.
Install & Setup
3 ways of setting up, either approach works:
1) Recommended: Set up conda
environment with provided .yml
file
We recommend setting up a fresh Python virtual environment in which to use solar-data-tools
. We recommend using the Conda package management system, and creating an environment with the environment configuration file named pvi-user.yml
, provided in the top level of this repository. This will install the statistical-clear-sky
package as well.
Creating the env:
$ conda env create -f pvi-user.yml
Starting the env:
$ conda activate pvi_user
Stopping the env
$ conda deactivate
Updating the env with latest
$ conda env update -f pvi-user.yml
Additional documentation on setting up the Conda environment is available here.
2) PIP Package
$ pip install solar-data-tools
Alternative: Clone repo from GitHub
Mimic the pip package by setting up locally.
$ pip install -e path/to/root/folder
3) Anaconda Package
$ conda install -c slacgismo solar-data-tools
Solvers
ECOS
By default, ECOS solver is used, which is supported by cvxpy because it is Open Source. However, it is found that Mosek solver is more stable. Thus, we encourage you to install it separately as below and obtain the license on your own.
MOSEK
MOSEK is a commercial software package. The included YAML file will install MOSEK for you, but you will still need to obtain a license. More information is available here:
Usage
Users will primarily interact with this software through the DataHandler
class.
from solardatatools import DataHandler
from solardatatools.dataio import get_pvdaq_data
pv_system_data = get_pvdaq_data(sysid=35, api_key='DEMO_KEY', year=[2011, 2012, 2013])
dh = DataHandler(pv_system_data)
dh.run_pipeline(power_col='dc_power')
If everything is working correctly, you should see something like the following
total time: 16.67 seconds
--------------------------------
Breakdown
--------------------------------
Preprocessing 6.52s
Cleaning 8.62s
Filtering/Summarizing 1.53s
Data quality 0.23s
Clear day detect 0.19s
Clipping detect 0.21s
Capacity change detect 0.91s
Contributors
Must enable pre-commit hook before pushing any contributions
pip install pre-commit
pre-commit install
Run pre-commit hook on all files
pre-commit run --all-files
Test Coverage
In order to view the current test coverage metrics, run:
coverage run --source solardatatools -m unittest discover && coverage html
open htmlcov/index.html
Versioning
We use Semantic Versioning for versioning. For the versions available, see the tags on this repository.
Authors
- Bennet Meyers - Initial work and Main research work - Bennet Meyers GitHub
See also the list of contributors who participated in this project.
License
This project is licensed under the BSD 2-Clause License - see the LICENSE file for details
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for solar_data_tools-1.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 34c4c47372924ced576b4afe84858ddb5ba7409f372bf49a533b31c4c747e376 |
|
MD5 | 7e7c3eb6862c9e1b1fdafafd406a03f3 |
|
BLAKE2b-256 | 87d40ba1b34120951e41a8743be8c93809db0f8ce4e6f0f127dc4f7e0a928536 |