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Solving Climate Change with Apache Kafka (Ed Conolly, OVO Energy) Kafka Summit London 2019

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Climate change is one of mankind’s greatest problems. We’ve made substantial steps forward to increase the amount of renewable generation on our power grids but we’re reaching a critical stage that determines our ability to make renewable energy truly ubiquitous. Power grids are built on the concept of equal supply and demand. In order to achieve this generation needs to be constant and demand predictable. As we move to more renewable sources we uncover substantial issues with the consistency and control with which we can generate energy. Currently this prevents us from truly 100% renewable grids. Using Kafka and IoT connected devices (wall mounted batteries, EVs, storage heaters) we’re building a distributed network of power storage in customers homes that drives down the cost of power for customers and unlocks the potential for a truly carbon free power grid.

In this talk I’ll discuss some of the issues we face trying to create 100% renewable grids and how Kafka helps our various systems process huge amounts of telemetry data from our connected devices, the grid and other systems to make decisions about when to charge, discharge or do nothing to thousands of connected assets. This talk covers Kafka concepts but focuses on climate change and how breakthroughs in technology can help us solve meaningful problems.

Veröffentlicht in: Technologie
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Solving Climate Change with Apache Kafka (Ed Conolly, OVO Energy) Kafka Summit London 2019

  1. 1. Ed Conolly - Group CTO tech.ovoenergy.com github.com/ovotech
  2. 2. 1 Million EVs 70% @ 7pmx x 22kW = 15 GW
  3. 3. ~ 3GW
  4. 4. 30 Million cars = 450 GW Whole UK = 80 GW
  5. 5. 1 2
  6. 6. 1
  7. 7. Off-Peak Generation �40 / MwH Distribution �1.41 / MwH Transmission �0.00 / MwH Generation �110 / MwH Distribution �140 / MwH Transmission �63 / MwH On-Peak
  8. 8. 2
  9. 9. �3 �2 �4 �5
  10. 10. {CustomerID: 123, Amount: 3} {CustomerID: 751, Amount: 2} {CustomerID: 123, Amount: 4} {CustomerID: 751, Amount: 5}
  11. 11. {CustomerID: 123, Amount: 3} {CustomerID: 123, Amount: 4} {CustomerID: 751, Amount: 2} {CustomerID: 751, Amount: 5}
  12. 12. PP 1 PP 3 PP 1 PP 3 PP 2 PP 2 PP 1
  13. 13. etc Control Engine Dispatcher
  14. 14. Our big data warehouse
  15. 15. Our big data warehouse
  16. 16. Our big data warehouse
  17. 17. Identity Team Comms
  18. 18. Lessons Learned

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