One of the biggest issues facing us is the availability of sustainable energy sources. As individuals and energy consumers it is often difficult to understand how we can make informed choices about energy use to reduce our impact on the environment. Electricity Map is a project that provides up to date and historical information about the balance of how the energy we are using is being produced. In this episode Olivier Corradi discusses his motivation for creating Electricity Map, how it is built, and his goals for the project and his other work at Tomorrow Co.
- Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
- When you’re ready to launch your next app you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 200Gbit network, all controlled by a brand new API you’ve got everything you need to scale up. Go to podcastinit.com/linode to get a $20 credit and launch a new server in under a minute.
- Finding a bug in production is never a fun experience, especially when your users find it first. Airbrake error monitoring ensures that you will always be the first to know so you can deploy a fix before anyone is impacted. With open source agents for Python 2 and 3 it’s easy to get started, and the automatic aggregations, contextual information, and deployment tracking ensure that you don’t waste time pinpointing what went wrong. Go to podcastinit.com/airbrake today to sign up and get your first 30 days free, and 50% off 3 months of the Startup plan.
- To get worry-free releases download GoCD, the open source continous delivery server built by Thoughworks. You can use their pipeline modeling and value stream map to build, control and monitor every step from commit to deployment in one place. And with their new Kubernetes integration it’s even easier to deploy and scale your build agents. Go to podcastinit.com/gocd to learn more about their professional support services and enterprise add-ons.
- Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
- Your host as usual is Tobias Macey and today I’m interviewing Olivier Corradi about Electricity Map and using Python to analyze data of global power generation
- How did you get introduced to Python?
- What was your motivation for creating Electricity Map?
- How can an average person use or benefit from the information that is available in the map?
- What sources are you using to gather the information about how electricity is generated and distributed in various geographic regions?
- Is there any standard format in which this data is produced?
- What are the biggest difficulties associated with collecting and consuming this data?
- How much confidence do you have in the accuracy of the data sources?
- Is there any penalty for misrepresenting the fuel consumption or waste generation for a given plant?
- Can you describe the architecture of the system and how it has evolved?
- What are some of the most interesting uses of the data in your database and API that you are aware of?
- How do you measure the impact or effectiveness of the information that you provide through the different interfaces to the data that you have aggregated?
- How have you built a community around the project?
- How has the community helped in building and growing Electricity Map?
- What are some of the most unexpected things that you have learned in the process of building Electricity Map?
- What are your plans for the future of Electricity Map?
Keep In Touch
- Electricity Map
- Machine Learning
- Climate Change
- Fossil Fuels
- Carbon Intensity
- Greenhouse Gas Equivalencies Calculations
- Open Data
- Electricity Map Project Source
- Marginal Carbon Intensity
- Electricity Map Forecast API
- IPCC (Intergovernmental Panel on Climate Change
- Spatiotemporal Data
- Matrix Inversion
- Tomorrow Co.