معرفی شرکت ها

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

A python package to generate "en-masse" chronics for loads and productions (thermal, renewable)

ویژگی	مقدار
سیستم عامل	-
نام فایل	Chronix2Grid-1.1.0.post1
نام	Chronix2Grid
نسخه کتابخانه	1.1.0.post1
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Mario Jothy, Nicolas Megel, Vincent Renault, Benjamin Donnot
ایمیل نویسنده	mario.jothy@artelys.com
آدرس صفحه اصلی	https://github.com/BDonnot/ChroniX2Grid
آدرس اینترنتی	https://pypi.org/project/Chronix2Grid/
مجوز	Mozilla Public License 2.0 (MPL 2.0)

# ChroniX2Grid - The Extensive PowerGrid Time-serie Generator Chronix2Grid is a python package, providing a command-line application as well, that allows to generate synthetic but realistic consumption, renewable production, electricity loss (dissipation) and economic dispatched productions chronics given a power grid. Reference data that you provide will serve to calibrate the parameters so that the synthetic data reproduce some realistic criteria (KPIs) from the reference data. * [1 Chronix2Grid at a glance](#glance) * [2 Installation](#installation) * [3 Getting Started](#getting-started) * [4 The command-line interface](#the-command-line-interface) * [5 Configuration](#configuration) * [6 Running the test suite](#running-the-test-suite) See the documentation at https://chronix2grid.readthedocs.io/en/latest/ ## Chronix2Grid at a glance ![Chronix2grid_inputs](pictures/ChroniX2Grid_inputs.png "Chronix2Grid Inputs") ![Chronix2grid_outputs](pictures/ChroniX2Grid_ouputs.png "Chronix2Grid Ouputs") ## Installation ### Requirements: * Python >= 3.6 #### (Optional, recommended) Step 1: Create a virtual environment ```commandline pip3 install -U virtualenv python3 -m virtualenv venv_chronix2grid ``` #### Step 2 (first option): Install from pypi ```commandline source venv_chronix2grid/bin/activate pip install Chronix2Grid ``` #### Step 2 (second option): Install from source ```commandline source venv_chronix2grid/bin/activate git clone https://github.com/mjothy/ChroniX2Grid.git cd ChroniX2Grid/ pip install -U . ``` ### Additional install required for dispatch A backend for dispatch has been implemented with PyPSA ```commandline pip install pypsa==0.17.0 ``` You might need to install cbc solver as well that pypsa will call: https://projects.coin-or.org/Cbc ## Getting Started Four notebooks are provided to get you started with this package: * **getting_started_cli.ipynb** guide you through the use of chronix2grid cli * **getting_started_api.ipynb** is a more detailed notebook that presents chronix2grid api and showcases several ways to analyze the chronics produced * **running_chronics_grid2op.ipynb** is a notebook giving an example of how generated chronics can further be used to create power grid scenarios and run them analyze the chronics produced * **RenewableNinja_Solar_WInd_KPI_format.ipynb** is an example on how to retrieve Solar and Wind reference chronics from the [renewable ninja](https://www.renewables.ninja/) api. There will be use to compare the KPI's with the generated chronics. Additionally, a data starting kit is provided to run an example in the folder ```commandline getting_started/example ``` The output folder corresponds to the following run of chronix2grid : ```commandline chronix2grid --mode LRTK --ignore-warnings --weeks 8 --n_scenarios 1 --start-date 2012-01-01 --by-n-weeks 4 ``` NB: * Default input data from package will be used if no --input-data and --case is provided * Output will be written in the working directory in a folder output/ To provide --input-data and --output-folder folders and specify --case grid case, you would run this kind of command (make sure to change ChroniX2Grid_path with you own path) : ```commandline chronix2grid --mode RLTK --output-folder ChroniX2Grid_path/getting_started/example/output --input-folder ChroniX2Grid_path/getting_started/example/input --ignore-warnings --weeks 8 --case case118_l2rpn_wcci --n_scenarios 1 --start-date 2012-01-01 --by-n-weeks 4 ``` ### WARNING In order to limit the size of the output and the running time for this example, chronics are only generated for 8 weeks. This implicates that some kpis that defined on a whole year will not be exploitable for this example. ## The command-line interface ```commandline Usage: chronix2grid [OPTIONS] Options: --case TEXT case folder to base generation on --start-date TEXT Start date to generate chronics --weeks INTEGER Number of weeks to generate --by-n-weeks INTEGER Size of the output chunks in weeks --n_scenarios INTEGER Number of scenarios to generate --mode TEXT Steps to execute : L(K) for loads only (and KPI); R(K) for renewables (and KPI) only; LRT (K) for load, renewable and thermic generation (and KPI); LRDT(TK) for load, renewable, loss (dissipation) generation (and thermic and KPI) --input-folder TEXT Directory to read input files from. --output-folder TEXT Directory to store output files. --seed-for-loads TEXT Input seed to ensure reproducibility of loads generation --seed-for-res TEXT Input seed to ensure reproducibility of renewables generation --seed-for-dispatch TEXT Input seed to ensure reproducibility of dispatch --ignore-warnings Ignore the warnings related to the existence of data files in the chosen output directory. --scenario_name TEXT subname to add to the generated scenario output folder, as Scenario_subname_i --nb_core INTEGER number of cores to parallelize the number of scenarios --help Show this message and exit. ``` ## Launch mode 4 generation submodules and a KPI module are available * L - load generation * R - wind and solar production generation * D - loss generation a priori, that will be used for dispatch and potentially corrected afterwards * T - thermic and hydro production generation thanks to an economic dispatch (simplified optimal power flow simulation) * K - KPI generation in order to compare synthetic (generated) chronics to reference (real-life) chronics The figure below shows how these submodules can be launched together with --mode/-m argument. Note that D and T submodules can't be launched without previous L and R modules, and that KPIs can always been computed ![Launch_mode](pictures/Launch_mode.png "Launch mode") ## Configuration ### Chronic generation detailed configuration Detailed configuration is made through thematic json files. For instance you will use in the current implementation of Chronix2grid: * **params.json** for general generation configuration (generation timestep, noise for forecast chronics) * **params_load.json** for load generation * **params_res.json** for solar and wind generation. You will use paramsGAN.json in case you are using the backend with Generative Adversarial Networks * **params_loss.json** for a priori loss generation * **params_opf.json** for dispatch and a posteriori loss simulation Below is an example of **params.json** which will launch a 5 minutes time step generation, applying a gaussian noise to forecast chronics with a standard deviation of 0.01 ```json { "dt": 5, "planned_std": "0.01" } ``` Below is an example of **params_load.json** that provides parameters to correlated generation algorithm. ```json { "Lx": 1000, "Ly": 1000, "dx_corr": 250, "dy_corr": 250, "temperature_corr": 400, "std_temperature_noise": 0.06 } ``` You'll find all the details on the parameters used in these json files in the [documentation about implemented models](https://chronix2grid.readthedocs.io/en/latest/DESCRIPTION.html) ### KPI configuration Some general parameters have to be set in *INPUT_FOLDER/kpi/paramsKPI.json* - **comparison**: name of benchmark folder to use for KPI reference chronics. For example, benchmark *France* has been implemented with eco2mix and renewable ninja data - **timestep**: timestep for KPI computation. For example, renewable ninja data requires minimum timestep of 60min - **night_hours**: dictionary to provide night hours for each season of year - **seasons**: dictionary to provide months in each season of year ## Model interface All generation submodules (LRDT) have a modular backend. You can develop your own load, renewable, loss and dispatch model using as input: * Your json parameters * Possible pattern files, or trained neural networks * Grid demand and generator characteristics in csv ## Citing ``` @misc{chronix2grid, author = {A. Marot, N. Megel, V. Renault, M. Jothy }, title = {{ChroniX2Grid - The Extensive PowerGrid Time-serie Generator}}, year = {2020}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/BDonnot/ChroniX2Grid}}, } ``` ## Running the test suite To launch the unit test suite: ```commandline pipenv run python -m pytest tests/unit_tests/ [--verbose -p no:warnings] ``` To launch integration tests: ```commandline pipenv run python -m pytest tests/integration_tests/ [--verbose -p no:warnings] ``` To launch the Command Line Interface (CLI) test (only if you installed chronix2grid package from Pypi) ```commandline pipenv run python -m pytest tests/cli_tests/ ``` You can also analyse the coverage of the tests with coverage and generate an html report: ```commandline pip install coverage coverage run --source=./chronix2grid -m unittest discover coverage html ``` This will generate a htmlcov folder containing a static web site with the analysis. Open index.html in a browser to analyse it.

نحوه نصب

نصب پکیج whl Chronix2Grid-1.1.0.post1:

pip install Chronix2Grid-1.1.0.post1.whl

نصب پکیج tar.gz Chronix2Grid-1.1.0.post1:

pip install Chronix2Grid-1.1.0.post1.tar.gz