PV_self_consumption_client
Authors: Sébastien Gardoll, IPSL, CNRS / Sorbonne Université Olivier Boucher, IPSL, CNRS / Sorbonne Université
(c) 2024
Interface to call API PV_self_consumption_client for optimising solar PV self-consumption under constraints. Note that the license only applies to this interface and not to the API itself.
Installation
Option 1: Conda
- Install miniconda;
- Create a new conda environment;
- Install the project dependencies.
Skip 1. if you already have a miniconda/anaconda distribution installed (which conda doesn't return an error).
Install miniconda
While installing, Miniconda asks you to initialize itself. If you choose to do so, it will add some instructions to your ~/.bashrc (shell configuration). Carefully choose the path of the Miniconda installation directory, as conda environment take some space and inodes. The following example is meant for Linux x86_64.
curl -sSL https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh > Miniconda3-latest-Linux-x86_64.sh
chmod +x Miniconda3-latest-Linux-x86_64.sh
./Miniconda3-latest-Linux-x86_64.sh
Conda environment creation
Let's create a conda environment called pvsc:
conda create -y -n pvsc 'python=3.12.*'
Install client
First activate the environment (as usual), then install the client with pip:
conda activate pvsc
pip install -U pv_self_consumption_api_client
Run client
In any directory:
pvsc -h
Option 2: PDM
PDM associates a Python virtual environmnent (venv) with a project described by a pyproject file.
Dependencies installation
Setup the project environment with PDM:
git clone https://github.com/OB-IPSL/PV_self_consumption_client.git
cd PV_self_consumption_client
pdm install
Run client
While in PV_self_consumption_client directory:
pdm pvsc -h
Getting started
Note: Add pdm command before pvsc while in the source directory if you installed the client with pdm (option 2).
Generate example input files
pvsc example -p > params.yml
pvsc example -d > demand.csv
The example input files can be modified for your own usages.
Run optimization
Compute optimization then output in and also generate plots (-m option):
pvsc optimize -m params.yml demand.csv
How to contribute
Install linters
You must follow the pdm install instructions. Then:
pdm install -dG dev
pdm run pre-commit install
Submit pull request
Contribution is possible thank to the PR submission.
Metadata
Release files for PV_self-consumption_api_client 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pv_self_consumption_api_client-0.1.5.tar.gz | 16.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pv_self_consumption_api_client-0.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.1 kB
Release files / pv_self_consumption_api_client-0.1.5.tar.gz
| Download URL | pv_self_consumption_api_client-0.1.5.tar.gz |
|---|---|
| Size | 16.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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pdm/2.19.2 CPython/3.13.0 Darwin/23.6.0
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Release files / pv_self_consumption_api_client-0.1.5-py3-none-any.whl
| Download URL | pv_self_consumption_api_client-0.1.5-py3-none-any.whl |
|---|---|
| Size | 17.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
pdm/2.19.2 CPython/3.13.0 Darwin/23.6.0
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