Metadata-Version: 2.1
Name: gsee
Version: 0.2.1
Summary: GSEE: Global Solar Energy Estimator
Home-page: https://github.com/renewables-ninja/gsee
Author: Stefan Pfenninger
Author-email: stefan@pfenninger.org
License: UNKNOWN
Description: # GSEE: global solar energy estimator
        
        `GSEE` is a small solar energy simulation library designed for speed and ease of use. [Renewables.ninja](https://www.renewables.ninja/) PV data is generated with `GSEE`.
        
        ## Requirements
        
        Works only with Python 3. Required libraries:
        
        * [pyephem](http://rhodesmill.org/pyephem/)
        * [numpy](http://www.numpy.org/)
        * [pandas](http://pandas.pydata.org/)
        
        ## Installation
        
        Simply install with `pip`:
        
            pip install gsee
        
        The recommended way to get the required numpy and pandas libraries is to use the [Anaconda Python distribution](https://www.continuum.io/downloads).
        
        ## Functionality
        
        The following submodules are available:
        
        * __``pv``__: electric output from PV a panel
        * __``trigon``__: functions to calculate irradiance on an inclined plane
        * __``brl_model``__: an implementation of the BRL model, a method to derive the diffuse fraction of irradiance, based on Ridley et al. (2010)
        
        A model can be imported like this: ``import gsee.pv``
        
        A plant simulation model implements a model class (e.g. ``PVPlant``) with the relevant settings, and a ``run_model()`` function that take time series data (a pandas Series) and runs a default instance of the model class, but can also take a ``model`` argument to specify a custom-configured model instance.
        
        ## Examples
        
        ### Power output from a PV system with fixed panels
        
        In this example, ``data`` must be a pandas.DataFrame with columns ``global_horizontal`` (in kW/m2), ``diffuse_fraction``, and optionally a ``temperature`` column for ambient air temperature (in degrees Celsius).
        
        ```python
        result = gsee.pv.run_model(
            data,
            coords=(22.78, 5.51),  # Latitude and longitude
            tilt=30, # 30 degrees tilt angle
            azim=180,  # facing towards equator,
            tracking=0,  # fixed - no tracking
            capacity=1,  # 1kW
        )
        ```
        
        ### Aperture irradiance on a panel with 2-axis tracking
        
        ```python
        location = (22.78, 5.51)
        plane_irradiance = gsee.trigon.aperture_irradiance(
            data['direct_horizontal'], data['diffuse_horizontal'],
            location, tracking=2
        )
        ```
        
        ## Development
        
        To install the latest development version directly from GitHub:
        
            pip install -e git+https://github.com/renewables-ninja/gsee.git#egg=gsee
        
        ## Credits and contact
        
        Contact [Stefan Pfenninger](mailto:stefan.pfenninger@usys.ethz.ch) for questions about `GSEE`. `GSEE` is also a component of the [Renewables.ninja](https://www.renewables.ninja) project, developed by Stefan Pfenninger and Iain Staffell. Use the [contact page](https://www.renewables.ninja/about) there if you want more information about Renewables.ninja.
        
        ## Citation
        
        If you use `GSEE` or code derived from it in academic work, please cite:
        
        Stefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. *Energy* 114, pp. 1251-1265. [doi: 10.1016/j.energy.2016.08.060](https://doi.org/10.1016/j.energy.2016.08.060)
        
        ## License
        
        BSD-3-Clause
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
