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

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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

• Website
• @nhoening on Twitter
• LinkedIn

Picks

• Tobias
  • She-Hulk
• Nicholas
  • Kleo on Netflix
  • Altair

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.
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Links

• FlexMeasures:
  • Github
  • Linux Energy Foundation
  • Mailing List
  • Twitter
• EyeQuant
• Energy Management System
• OpenEMS
• ICT == Information and Communications Technology
• HomeAssistant
  • Podcast Episode
• FlexMeasures HomeAssistant Plugin
• Universal Smart Energy Framework
• PostgreSQL
  • Data Engineering Podcast Episode
• TimescaleDB
  • Data Engineering Podcast Episode
• OpenWeatherMap
• Timely-Beliefs library
• Flask
• Click
• Pyomo
• scikit-learn
• sktime
• LF Energy
• Flake8
• MyPy
  • Podcast Episode
• Black
• Arima Model
• Random Forest

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