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IET Smart Metering April 2012
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IET Smart Metering April 2012

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Talk about how to turn Smart Meter data into value for the consumer and the various types of retailer. By using Smart Data Engines, by using high-resolution data fed into Analytics.

Talk about how to turn Smart Meter data into value for the consumer and the various types of retailer. By using Smart Data Engines, by using high-resolution data fed into Analytics.

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  • 1. alertme creating smart homesPilgrim Beart, AlertMe18th April 2012 February 2012IET 5th Annual Smart Metering Conference
  • 2. Introducing AlertMe• Platform for the Smart Home / Connected Home – In-home devices – Gateway – Cloud services – A variety of UI’s• Complete with out-of-the-box applications: – Smart Monitoring – Smart Energy – Smart Heating – Smart Data
  • 3. TodayFrom Smart Data to Consumer Value• What data will be available from Smart Meter, who owns it, and who can access it?• What kinds of value can be derived from that data? Value to whom?• New services and business
  • 4. The Value of Data• General market trend is from products to services• Data is the lifeblood of any service• “New economy” companies easily deal with: – Databases of millions of customers – Millions of hits/day• “Old economy” companies struggle with: – A patchwork of legacy IT systems & processes
  • 5. UK Smart Meters deserve the name
  • 6. Data available on SMHAN (1)• Basic Consumption – Electricity • Day/Week/Month Cumulative Consumption & Cost • Instantaneous Active Import Power, 10sec - and 1s? • Microgen – Gas • Day/Week/Month Cumulative Consumption & Cost • (30 min update because of battery-life)• HH interval data for 13 months• Messaging
  • 7. Data available on SMHAN (2)• Tariff & Supplier – Electricity Tariff Supplier & Name – Current and next tariff – Tariff Rate Matrix – Billing period info (start time/date and duration) – Block thresholds & PPUs • Volume-based stepped pricing. Green/standing charge. – ?No power-based pricing?• Change of Tenancy/Change of Supplier• Prepayment/Debt – Inc. Emergency Credit – Aggregate Debt (3 types & 2 recovery methods!)• System Management - Power Quality?
  • 8. Who “owns” the data?…is a meaningless question!• Security and Privacy (different things) – Who can access what data, under what conditions?• Via the WAN & DCC (minimal data, not live) – Your Utility (in principle just enough for billing) – DNO’s (though ideally would like live view) – 3rd-parties nominated by consumer (e.g. switching services?)• Via the home (inc. high-res live data) – The consumer – Third-party services consumer nominates – Consumer Gateway can push hi-res data into Cloud via broadband. Govt not minded to regulate this, but there should be some “best practice” guidelines to ensure consumers understand what they are doing.
  • 9. ValueThink of 3 stages: Data -> Information -> Valuee.g. Data = Tariff & consumption so far this month Information = Predicted bill at end of the month Value = Household budgeting, Avoiding disconnection
  • 10. Value from SM Data• VIS - visibility • PRIVACY - change of owner• COST - translated into £ • MESSAGE - from utility• CO2 - translated • SMSOK - system working• EARN - microgen• PRICESIGNAL - ToU, CPP • TIME - reference• COMP - comparative norms • READINGS - to check bill• PREDICT - budgetting• SWITCH - tariff / supplier• PREPAY - and credit/debt• DISCONNECT (source: CEDIG data dictionary)
  • 11. Value from SM Data - Analytics(all enabled by 1-second data) Examples • ITEMISE • “Washing at 30°C would save you £34/year” • WARN • “Boiling only a cupful of water in your kettle would save you £12/year” • MAINT • “25% of your bill is spent on ‘baseload.’ Click for tips on what might be causing this and how to address it” • HEAT • “Your fridge is consuming more than last year – perhaps the seals have gone. A new fridge would pay • ASSIST for itself in 3 years” • “You’ve left the house but your fridge door is open • AUDIT (or your iron/over/hair curlers are still on)” • “Mum didn’t get up this morning” • AUTOAPP • “More of your bill is spent on heating than in similar homes.” • OPTIM • Ensure EV charged by 8am at minimal cost • Optimising heating patterns around occupancy
  • 12. 30 minute data OK for balancing grid
  • 13. Analytics needs 10 second data(and ideally 1 second)
  • 14. Industry’s view SMWAN Value Added SMHAN Services Smart Retention Meter IHD Up-sell Billing
  • 15. Smart MeterConsumer’s view IHD Savings Solar Comfort Panels Electric Me Conven Vehicle ience Peace Fashion of Mind
  • 16. Everything else now in the Cloud …why not your home? “The number of internet connected devices is set to explode in the next four years to over 15 billion, twice the worlds population” Suraj Shetty, Cisco VP global marketing, at its 5th annual trends forecast 1 June 2011
  • 17. Smart Data Engines(Using the ADELE - Alertme Domestic Energy Load Engine - as an example)A model, able to use whatever data is available:• Zero data (assume national averages)• Basic data (demographics or postcodes)• Low-res Energy data (quarterly/monthly reads)• Medium-res Energy data (Smart Meter HH)• High-res Energy data (10s via Consumer Gateway)• Temperature and per-appliance, if available• Other sources (e.g. customer-volunteered info)
  • 18. Smart Data Engines (2)Provides, uniquely for every customer:• Predicted bill (elec, gas)• Energy use profile over 24 hours• Bill break-down – Lighting, Cooking, Heating, Appliances, Hot Water,…• Normative and Injunctive Comparisons• Energy advice – helps consumers manage spend• Spots up-sell/cross-sell opportunities
  • 19. The Value of DataTo the Consumer:• Information and Insight• Control• Automation• Simplicity (esp. interoperability & low friction)• Peace of Mind• Savings (reduced consumption, switching)
  • 20. The Value of DataTo Retailers (of Energy and others):• New Services (brand presence, loyalty)• Higher added-value – Energy Services much higher margin vs. Energy Retail• Cross-sell, up-sell & e-commerce• Disintermediation (e.g. MVNO)• Bundling• One platform to unify the homeThis is not just a game utilities can play – E.g. retailers & telcos can too – Utilities risk Disintermediation & Commoditisation
  • 21. Data – the Ground Rules• Must be Permissive – It’s the consumer’s data – The consumer chooses to grant access – If it doesn’t benefit them - they won’t! – It’s a trade (like gMail)
  • 22. Conclusions1. Caveat: • Nothing final until SMETS 2 process complete (due Sep ‘12) • Mass rollout now only 2.5 years away: 5m homes/year2. Smart Meters are necessary • It’s just putting the cash register online3. …but not sufficient • Market needs to deliver products and services which use them4. Vital that Smart Meters: • Calculate once • Make it easy for consumers to allow third-party products and services to access their data and turn it into value • Support an open standard5. Energy services are being developed and launched right now • Using e.g. clip-on readers • Start preselecting your best customers, now!
  • 23. alertme creating smart homes pilgrim.beart@alertme.com alertme alertme alertme2nd floor Heddon House Thirty Station Road 123 10th Street149-151 Regent Street Cambridge San Francisco London W1B 4JD CB1 2RE CA 94103 +44 207 993 9500 +44 1223 361555 +1 415 409-9288
  • 24. BACKUP
  • 25. 1. In Home Display (live in the home) Translate Energy units into MoneyAesthetically pleasing(looks good in your kitchen) Comparative (consumption rising or falling?) Live “Speedometer” display Added-value features (Power, at a glance)
  • 26. 2. Offline (historical e.g. on bills)
  • 27. 3. Online (live, everywhere) You spent £200 heating an empty home last winter Intelligent heating gives 20% savings on your gas bill by only heating the home when you are there.
  • 28. Energy Monitoring – IHD or Online? Given the choice, which one would you choose? Option 1 - Display 40% Option 2 - Online 40% Depends 12% Neither 8%UK market survey by Critical Research, May 2011. Sample size; 1,224
  • 29. IHDs vs Online: StereotypesIHD Persona: Online Persona:• More likely to be 50+ • More likely to be ~30-year-old• More likely to be married • More likely to be male• More likely to be female • Has young children• Children have left home • Fully-employed• May be retired • Home mortgaged, or renting• Home mortgaged/paid off, probably hasn’t • Household income £2500/month moved for 15 years • Owns a Laptop and/or SmartPhone• Household income £1250/month • Uses computer at work to access internet• Owns a desktop Previous IHD experience: • People who’ve already had IHDs more likely to want Online • Especially those that have discarded their IHD
  • 30. The Value of Data (Smart Meters are just one of many new data sources)
  • 31. AlertMe Smart Data