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The Python Podcast.__init__

390 EpisodesProduced by Tobias MaceyWebsite

The podcast about Python and the people who make it great

49:16

Take Control Of Your Electrical Systems With The Open Source FlexMeasures Energy Management System

Summary

The generation, distribution, and consumption of energy is one of the most critical pieces of infrastructure for the modern world. With the rise of renewable energy there is an accompanying need for systems that can respond in real-time to the availability and demand for electricity. FlexMeasures is an open source energy management system that is designed to integrate a variety of inputs intelligently allocate energy resources to reduce waste in your home or grid. In this episode Nicolas Höning explains how the project is implemented, how it is being used in his startup Seita, and how you can try it out for your own energy needs.

Announcements
  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great!
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  • Your host as usual is Tobias Macey and today I’m interviewing Nicolas Höning about FlexMeasures, an open source project designed to manage energy resources dynamically to improve efficiency
Interview
  • Introductions
  • How did you get introduced to Python?
  • Can you describe what FlexMeasures is and the story behind it?
    • What are the primary goals/objectives of the project?
    • The energy sector is huge. Where can FlexMeasures be used?
  • Energy systems are typically governed by a marketplace system. What are the benefits that FlexMeasures can provide for each side of that market?
    • How do renewable sources of energy confuse/complicate the role that the different stakeholders represent?
    • What are the different points of interaction that producers/consumers might have with the FlexMeasures platform?
  • What are some examples of the types of decisions/recommendations that FlexMeasures might generate and how to they manifest in the energy systems?
    • What are the types of information that FlexMeasures relies on for driving those decisions?
  • Can you describe how FlexMeasures is implemented?
    • How have the design and goals of the system changed/evolved since you started working on it?
  • What are the interfaces that you provide for integrating with and extending the functionality of a FlexMeasures installation?
  • What are the operating scales that FlexMeasures is designed for?
  • What are the most interesting, innovative, or unexpected ways that you have seen FlexMeasures used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on FlexMeasures?
  • When is FlexMeasures the wrong choice?
  • What do you have planned for the future of FlexMeasures?
Keep In Touch Picks Closing Announcements
  • Thank you for listening! Don’t forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. The Machine Learning Podcast helps you go from idea to production with machine learning.
  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
  • If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@podcastinit.com) with your story.
  • To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Links

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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