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AI in Energy
The document discusses how EDF Energy's R&D UK Centre is leveraging AI to transform the energy system, focusing on innovative applications like predictive maintenance and customer service automation. It highlights the complexities of the modern energy system, which incorporates renewable technologies and smart homes, and the ongoing challenges faced by legacy organizations in adopting AI. The conclusion emphasizes that while AI is a powerful tool for managing this complexity, it is not a panacea and requires careful implementation.
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AI in Energy
- 1. EDF Energy R&DUK Centre Transforming the energy system with AI David Ferguson, Head of Digital Innovation
- 2. The rules ofdigital innovation Move fast and break things. Unless you are breaking stuff, you are not moving fast enough. “ ”- Mark Zuckerberg, Facebook
- 3. Move fast andbreak things?
- 4. The old energysystem
- 5. The new energysystem
- 6. The new energysystem… it’s really complex! 1 million homes with solar panels 1 million homes with smart thermostats
- 7. Energy innovation isnot coming from the old energy sector New tech + new ways of working
- 8. 80 5 Teams People 40Phd students15 NationalitiesBudget Nuclear Renewables Smart Customers Digital Innovation Open Innovation Brighton Manchester London £40m Conventions or contracts with EDF Energy Business Units or EDF Group100% 26% 10% Public fundingCorporate activities Funding 3 Locations EDF Energy R&D UK Centre
- 9. Image: Wired - AndrewNg, Baidu, 2016 AI will transform many industries. But it’s not magic. “ ” Let’s not get carried away just yet
- 10. What is it?Use cases for EDF Energy Generation ● Condition monitoring ● Predictive maintenance ● Digital replicas ● Operational support ● Autonomous robotic devices Customers ● Customer service ● Energy use analytics ● Home automation ● Optimisation and trading Grids and networks ● Predictive maintenance ● Demand-side response ● Trading Support functions ● Supply chain optimisation ● Legal services Reasoning Knowledge Planning Learning Natural Language Understanding Perception How could AI apply to EDF Energy?
- 11. Early R&D R&D UKCentre
- 12. Digital replicas: labelrecognition in power stations Images: EDF 30,000 labels 500 bn pixels 4 person-months per building 10 buildings per year
- 13. Digits zone cropping Preprocessing(B&W and cleaning) Digits recognition: 02615.0 Customer service: optical character recognition
- 14. Energy use analytics:Virtual Data Lab
- 15. Customer service: chatbotsand voice
- 16. Our vision R&D UKCentre
- 17. Real-time condition monitoring Two usecases for AI for EDF Energy The intelligent home
- 18. Real-time condition monitoring AI inpower stations 1 - Explain 2 - Predict 3 - Prescribe 4 - Automate
- 19. Real-time condition monitoring AI forresidential customers The intelligent home 1 - Show me 2 - Help me 3 - Do it for me
- 20. The challenges ofturning vision into reality R&D UK Centre
- 21. Delivering the promiseof AI in a ‘legacy’ company Challenges Generic Specific to legacy orgs. Skills Ethics Privacy Security Data Connectivity Roll out ‘The day job’
- 22. Conclusions The energysystem is complex and is changing AI is not magic It will help manage the new, complex system Our approach: start with small, difficult problems Legacy companies have a significant disadvantage
- 23.