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1 1 Smart Grid, Smart Metering and Cybersecurity Prof David Wallom Energy and Environmental ICT Group

Smart Grid, Smart Metering and Cybersecurity

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Page 1: Smart Grid, Smart Metering and Cybersecurity

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Smart Grid, Smart Metering and CybersecurityProf David Wallom

Energy and Environmental ICT Group

Page 2: Smart Grid, Smart Metering and Cybersecurity

UK Electricity network

Page 3: Smart Grid, Smart Metering and Cybersecurity

Smart Grid

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HPC Engine and Storage

Next Generation Infrastructure

The Smart Grid

High Speed Communications System

Service Restoration

Voltage Control

Condition Monitorin

g/Data Mining

Distribution

System State

Estimation

Distribution Management System

Smarter Distribution

• Distribution System State Estimation

• Service Restoration Algorithms

• Condition Monitoring

• Voltage Control

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myTrustedCloud

• Network topographical detail is exchanged between Distribution and Transmission operators• Network changes infrequent and normally minor

• Regulator requirement for availability of single overall network map with NationalGrid

• Currently an email is sent from DNO -> TNO…

• Introduction of widespread distributed generation will change the requirements• Network changes could be significant and frequent [within minutes or even real-time]

• What systems can we use to share data securely for critical national infrastructure?

• Cloud computing as a paradigm is extremely attractive for activities which have variable loads• Considerable security concerns for the use of shared resources

• Trusted computing allows the use of hardware based security mechanisms to measure and guarantee system state to a user

• Prove that a mix of Cloud & Trusted Computing provide a system with the security and privacy guarantees that serious safety critical industries such as energy will find attractive enough to make use of?

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Investigating domestic load profiles

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DIET – Data Insights against Energy Theft

• ~£400M in theft per year• £8 - £20 per property per year• Smart Metering only commercially

viable by reducing human interaction.

• 300k meters per day, commercial customers

• 48 half-hour kWh readings per day• Details of 200 confirmed theft

events provided by partners ‘on demand’

• Training set of 1/1000 cases

• Scale to near real-time for 50M meters

• ~50k potential theft triggers per day

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Conclusions

• Moving to ‘Smarter Grid’ will be a gradual rather than big bang process– Making the Distribution Network Smart is the first step

– Realising all the new and possibly different use cases for smart grid data usage is an evolving process

• Communication between partners will greatly increase with new network utilisation usecases

• Cryptographically secure Cloud computing is ideally placed to support sharing of information between the many and varied stakeholders within Smart Grid

• The clustering analytics done on domestic and non-domestic data has also opened opportunities with other functions that are necessary to make smart Grid and smart metering a success.