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* Bump version: 1.0.9 → 1.0.10 [skip ci] * docs: update README.md [skip ci] * docs: update .all-contributorsrc [skip ci] * Bump version: 1.0.10 → 1.0.11 [skip ci] * Replace H with h inside pandas' floor function (#64) Thanks @0xFrama for this * Bump version: 1.0.11 → 1.0.12 [skip ci] * Added Contribution Guide (#65) * added contribution guide * added reference to coding style * Bump version: 1.0.12 → 1.0.13 [skip ci] * docs: add roshnaeem as a contributor for doc (#67) * docs: update README.md [skip ci] * docs: update .all-contributorsrc [skip ci] --------- Co-authored-by: allcontributors[bot] <46447321+allcontributors[bot]@users.noreply.github.com> * Test set analysis (#60) * test set analysis * added link to nbviewer in notebook * deleted checkpoints * Delete checkpoints * delete metadata.csv * using metadata from hugging face * remove unused import * Bump version: 1.0.13 → 1.0.14 [skip ci] * docs: add bikramb98 as a contributor for code (#68) * docs: update README.md [skip ci] * docs: update .all-contributorsrc [skip ci] --------- Co-authored-by: allcontributors[bot] <46447321+allcontributors[bot]@users.noreply.github.com> * fetches live Enphase data at the moment it is called (#66) * fetches live Enphase data at the moment it is called replace 'user_enphase_api_key' and 'user_enphase_user_id' with the actual Enphase API key and user ID. The make_pv_data function now fetches live data from the Enphase API and combines it with the existing fake PV data This "may" not be from the time of interference, do i add make use of timestamps to enable it? * Added Flag indicating whether to use live Enphase data or not Now the user will have an option whether to use live enphase data or the default data * Updated site object to accomodate is_inverter option + created /inverters/enphase.py file * added environment variables * Bump version: 1.0.14 → 1.0.15 [skip ci] * added init.py in invertors directory * fixed the import of enphase_data --------- Co-authored-by: BumpVersion Action <bumpversion@github-actions> Co-authored-by: allcontributors[bot] <46447321+allcontributors[bot]@users.noreply.github.com> Co-authored-by: Peter Dudfield <[email protected]> Co-authored-by: Francesco <[email protected]> Co-authored-by: Bikram Baruah <[email protected]> Co-authored-by: Aryan Bhosale <[email protected]>
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# User needs to add their Enphase API details | ||
ENPHASE_API_KEY = 'user_enphase_api_key' | ||
ENPHASE_USER_ID = 'user_enphase_user_id' |
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.env |
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# Contribution Guide | ||
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## Welcome | ||
Welcome to Open Climate Fix project! Open Climate Fix fosters an inclusive open-source community, welcoming participation from everyone. We value all forms of contributions, whether to our codebase or documentation, and we appreciate your support. | ||
Before you begin, make sure to go through the [README.md](https://github.com/openclimatefix/Open-Source-Quartz-Solar-Forecast/blob/main/README.md) file of project to understand the project. | ||
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## Environment Setup | ||
`Open-Source-Quartz-Solar-Forecast` project is developed with Python, that supports our open-source PV forecast model's computational needs. To set up and contribute to the project, Python version 3 is required. | ||
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### Clone the Repository | ||
Follow the following steps to setup the project on your machine. | ||
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1. Fork the [Open-Source-Quartz-Solar-Forecast repository](https://github.com/openclimatefix/Open-Source-Quartz-Solar-Forecast) by clicking on the ‘Fork’ button. This creates a copy of the code under your GitHub user account. Your fork will have your own GitHub username. | ||
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2. Clone your fork of the project by running the following command: | ||
``` | ||
git clone https://github.com/<Your GitHub handle>/Open-Source-Quartz-Solar-Forecast.git | ||
``` | ||
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3. Navigate to the directory. | ||
``` | ||
cd Open-Source-Quartz-Solar-Forecast | ||
``` | ||
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4. Start contributing!!! | ||
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## How to Contribute | ||
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For contributing to Open Climate Fix project, we recommend following these detailed steps. | ||
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### Step 1: Find an Issue to Work On | ||
Begin by exploring the issues listed on the project's GitHub [issues](https://github.com/openclimatefix/Open-Source-Quartz-Solar-Forecast/issues) page. If you're new to the project, look for issues tagged with `good first issue`, these are specifically selected to be more accessible for newcomers. Selecting an issue that aligns with your interests or expertise is a great way to contribute effectively. | ||
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### Step 2: Communicate Your Interest | ||
Before diving into coding, it's a good practice to comment on the issue you're interested in. This lets the maintainers know you're working on it and prevents duplicate efforts. It's also an excellent opportunity to ask any clarifying questions and discuss your approach. | ||
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### Step 3: Create a New Branch | ||
For every new contribution, create a branch in your local repository. A branch is a way to keep your changes seprate from the main part of the project called `main`. This branch should be based off the main project's latest main branch. Naming your branch with a convention like `feature/your-feature-name` or `fix/issue-description` can help identify its purpose. | ||
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### Step 4: Open a Pull Request (PR) | ||
Once you're satisfied with your contribution, push your branch to your fork on GitHub and open a pull request against the original Open Climate Fix repository. In your pull request description, reference the issue you're addressing and provide a summary of your changes. Providing screenshots or output snippets can be particularly helpful for visual changes or user interface improvements. | ||
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### Step 5: Request a Review | ||
After submitting your pull request, you can request a review from the project maintainers or specific contributors by mentioning them in your PR comments. Once your pull request is approved, a project maintainer will merge it into the main branch. | ||
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> Don't forget to keep your local repository and fork updated with the main project to ease future contributions. | ||
## Code Style | ||
For checking our coding style, please refer to [coding_style.md](https://github.com/openclimatefix/.github/blob/main/coding_style.md). |
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## Test set analysis | ||
The test set contains the data used for testing the solar forecast models developed. It contains 2500 data points, with `pv_id` and `timestamps` of when the data was collected. Upon analysing the dataset, the following observations were made: | ||
1. The data is pretty evenly distrbuted throughout the year, with the highest number of data points from the month of May (256 data points) | ||
2. Looking at distribution by hour of the day, the highest number of data points is from 19:00 hrs (132 data points), and the least from 00:00 hrs (87 data points) | ||
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By analysing the metadata, available at [Hugging Face](https://huggingface.co/datasets/openclimatefix/uk_pv), along with the test set, it can be observed that: | ||
1. Most of the data in the test set has a tilt angle of 30-34 degrees | ||
2. The maximum kwp is 4.0 & the minmum kwp is 2.25 in the test set. | ||
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A detailed anaysis of the test set can be found at quartz_solar_forecast/dataset/dataset_analysis/test_set_analysis.ipynb |
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import requests | ||
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def get_enphase_data(enphase_user_id: str, enphase_api_key: str) -> float: | ||
""" | ||
Get live PV generation data from Enphase API | ||
:param enphase_user_id: User ID for Enphase API | ||
:param enphase_api_key: API Key for Enphase API | ||
:return: Live PV generation in Watt-hours, assumes to be a floating-point number | ||
""" | ||
url = f'https://api.enphaseenergy.com/api/v2/systems/{enphase_user_id}/summary' | ||
headers = {'Authorization': f'Bearer {enphase_api_key}'} | ||
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response = requests.get(url, headers=headers) | ||
data = response.json() | ||
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# Extracting live generation data assuming it's in Watt-hours | ||
live_generation_wh = data['current_power']['power'] | ||
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return live_generation_wh |
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setup( | ||
name="quartz_solar_forecast", | ||
version="1.0.9", | ||
version="1.0.15", | ||
license="MIT", | ||
author="Peter Dudfield", | ||
author_email="[email protected]", | ||
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