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Bard Microhydropower Calculator

A map-based application for estimating the power potential of microhydropower installations.

This was built as a demonstration project for Bard College and Current Hydro LLC. The project was funded by NYSERDA.

What It Does

The Microhydropower Calculator helps estimate the power generation potential of a micro-hydroelectric turbine installation. It guides you through these steps:

1. Identify a location for microhydropower, and get information about the terrain

Use the map and available data layers to identify a spot suitable for a potential microhydropower installation. Dam locations (New York State only) and national hydrographic data from US Geological Survey (USGS) are available as map layers. Switch the basemap between several available imagery and topographic styles from Esri and Mapbox to get a better sense of the terrain.

Once you've found a stream or weir, you diagram the location of the installation on the map with the draw tool. The calculator will automatically estimate head (elevation change) and delineate the contributing area using available topographic data.

The underlying elevation data driving the calculations is provided by the USGS through web services hosted by ESRI. Where available in New York state, head calculations will rely first on high resolution elevation data services hosted by the NY State GIS Program Office, and fall back to coarser USGS elevation data if needed.

2. Set calculation parameters

You can input calculation coefficients and other assumptions used in the calculation (sensible defaults are provided).

Optionally, you can also override the head and area estimates derived from map in Step 1.

3. See the power potential of a microhydropower installation

View the analysis results, including total kilowatt hours and estimated revenue generation.

More information

The calculator logic is described in the calculator's About section; you can see that same documentation here.

Architecture Overview

The Bard Microhydropower Calculator is built with Python-Flask, Leaflet, Esri-Leaflet, Bootstrap, and jQuery. Data and Geoprocessing services are from the Esri Living Atlas in ArcGIS Online (AGOL).

Python Flask provides a server-side framework for assembling the web application from templates and assets. Since this is a single page app, it doesn't have much to do in that regard. Rather, its role is primarily to serve as a proxy for authenticating into secured Esri ArcGIS Online (AGOL) resources. It retrieves an AGOL authentication token on page load and returns it to the client side code (javascript), where it is used to make calls to elevation and other data services from Esri.

On the front-end:

  • Bootstrap and jQuery provides the stack for the mobile-adaptive layout
  • Leaflet is used for the map
  • Esri-Leaflet helps utilize Esri services in conjunction with the Leaflet map

Front-end business logic is written in javascript with only jQuery. Javascript and CSS compliation and bundling is being handled by GulpJS and Browserify.

Development

Configuration (config.py)

The application requires a few global configuration variables to be set, mainly to enable access to 3rd-party Esri and Mapbox services. Required services include:

ArcGIS Application Registration

  • Esri Application ID
  • Esri Application Secret

Get these by registering an application at https://developers.arcgis.com

Mapbox Token

  • Token

Get this by generating a token from https://www.mapbox.com

Development Quickstart

(for editing HTML and Python only).

To develop this, you must have installed:

  • Python 3.4+, and you can call python and pip or (python -m pip) from the command line
  • Node/NPM and you can call node and npm from the command line
  • GulpJS installed (available via npm)
  • git installed, also available from the command line.

1. Clone the repository

git clone https://github.com/civicmapper/bard-hydropower
cd bard-hydropower

2. Initialize a Python virtual environment and install Python dependencies with Python pipenv

If you don't have pipenv (and you won't with an out-of-the-box python installation)

pip install pipenv

Then:

pipenv install

...to install dependencies, and then:

3. Run a basic development server

pipenv shell python run.py

Navigate to http://localhost:5000 to see the site.

This is sufficient for modifying html in the app/templates/ folder, or changing any of the python scripts. However, it only serves up pre-compiled client-side code stored under app/static/; it does not run the client-side build tasks, so you won't see edits made to code in src if you only develop using this method.

You can kill this development server by pressing ctrl-c in the command line.

Client-Side Development

for editing JS, CSS, HTML, and python.

(assuming you've installed Python dependencies above)

1. Install javascript dependencies

In the repository root:

npm install

This will download and install a whole lot of javascript in a node_modules folder.

2. Run a browser-synced development server

gulp watch

This does a bunch of things:

  • it compiles and bundles js files from the src and node_modules directory, and puts them in the the app/static directory (where the application wants them to be)
  • it does the same with css files
  • it copies assets from certain js modules to the app/static/assets directory,
  • it fires up the Python-Flask application and its development web server for you (runs pipenv shell python run.py)
  • it opens up your default browser and loads the page.

3. Develop and see changes as they happen

With #2 complete, when you change code in the src folder, the browser will either:

  • live reload (inserting your changes into the page)
  • refresh automatically (if it needs to reload an entire script or asset again)

Build

Use gulp build from the command line to compile source code and copy assets in the app folder. Once built, only the app folder (and its contents) and application.py script are required for running the web application in production.

Make sure your config.py DEBUG parameter is set to False for production!

Deployment

There are many ways to deploy this application. Some options:

PythonAnywhere

PythonAnywhere provides a great place for deploying a Flask applications like this. Follow this guide for deployment.

Deployment to AWS Elastic Beanstalk

Follow this guide for deployment to AWS EBS.

As of this writing, AWS Elastic Beanstalk supports Python 3.4.

Credits

Application by Christian Gass @ CivicMapper.