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Presented by: Tommy Carpenter Computer science University of Waterloo

Presented by: Tommy Carpenter Computer science University of Waterloo. Outline. The grid has real problems t hat smart grids can solve These problems are intrinsic and difficult s o progress has been slow Three areas where changes are imminent are solar , storage , and sensing

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Presented by: Tommy Carpenter Computer science University of Waterloo

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  1. Presented by: Tommy Carpenter Computer science University of Waterloo

  2. Outline • The grid has real problems • that smart grids can solve • These problems are intrinsic and difficult • so progress has been slow • Three areas where changes are imminent are solar, storage, and sensing • examples of our work in these areas

  3. The Grid

  4. …is old Post-war infrastructure is reachigEOL

  5. …inefficient US DOE: http://www.southeastchptap.org/cleanenergy/chp/

  6. …poorly measured

  7. …poorly controlled • Electrons are notaddressable Perception Reality

  8. …dirty (mostly)

  9. …without storage (mostly) Needed capacity http://ieso-public.sharepoint.com/

  10. Smart grid

  11. Current grid Smart grid • Renewables/low carbon • Storage rich • Sensing rich • Control rich • Efficient • Decentralized High carbon footprint Little to no storage Poorly measured Poorly controlled Inefficient Centralized

  12. …but Consumers & Utilities lack incentives Savings of 10%: $5-10/month Utilities make $$ regardless

  13. hence slow progress: -Demand response: onlytime of use pricing -Grid storage: tiny -Smart buildings and homes: demo stage -Microgrids: rare -Electric vehicles: early mainstream -Security and privacy: mostly missing

  14. Three inflection points • Solar • Storage • Sensing (and control)

  15. Storage research, investment growth Global investment to reach $122 Billion by 2021 – Pike Research Some grid storage Largest change: EVs LiON Declining. $600 down to <$200

  16. Sensing & Control Grid Home Pervasive Michigan Micro Mote

  17. Our Contributions

  18. Insight: Grid-Net Isomorphism Grid Internet Variable bit-rate source Bits Buffer Communication link Tier 1 ISP Tier 2/3 ISP Congestion control Renewable Source Electrons Storage Transmission line Transmission network Distribution network Demand response

  19. SSS: Solar, Storage, Sensing

  20. Sensing: auto thermal comfort (Spotlite) • Uses ML to learn comfort levels, occupancy patterns • Pre-heat prior to occupancy periods, lower heat afterwards • Cooling

  21. Sensing: preserving data privacy -Certification and Validation App Store -Data collection -Data access control -Application framework App API VEE -Integrating cloud storage -High density hosting Host Each user’s data is stored and processed (by apps) in user-owned virtual execution environments, enabling: Gateway Data ownership Data privacy Data applications

  22. Sensing + Storage: distributed charging - Goal: fairly allocate resources during congestion periods - Our work: distributed, model free and real time via congestion signals - Prior work: centralized, perfect network knowledge, day ahead, • 1 EV = 5 homes • Creates hotspots • Real-time AIMD control of EV charging rate • Solution is both fair and efficient

  23. Solar + Storage: Solar EV Charging • Base case (no solar): try meeting all charging deadlines • - If infeasible; perform fair allocation • Integrate solar to reduce emissions while ensuring same (or greater) utility

  24. Solar + Storage: ROI, EROEI of Solar Systems w/ Storage -Advanced modeling of stochastic inputs, comprehensive battery model

  25. Storage: EV ecosystem & adoption modeling

  26. Storage: EV Sentiment Analysis • EV Ops gauged using: • Field Trials: Expensive = usually short, not many participants • Surveys: Hard to target • But lots of opinions buried in discussion forums!

  27. Storage: EV Sentiment Analysis

  28. Storage (EVs): Vehicle Access networks for EV owners • - Range Anxiety: long trips not possible yet. Prohibitive to owners • without another car. • - EV owners sometimes need access to ICEVs • - Solution: operate some form of multi pool network (a carshare) • - Can be integrated into dealership, operated by gov, • community nonprofit, etc. • - Regardless of business model, sizing/managing the fleet is hard

  29. Storage (EVs): Vehicle Access networks for EV owners Challenge: Ensure maintained over time Demand patterns constantly changing, non-stationary, arbitrary

  30. Sensing + storage + solar: WeBike • A fleet of 25-30 ebikes on campus • Tons of sensors, data collection • Bikes now being deployed!

  31. Why study eBikes?

  32. Conclusions • - We are networking and smart grid researchers exploiting similarities between the net and grid • - Currently working in 3 main areas: • Solar • Storage (EVs) • Sensing/Control

  33. Extra Slides

  34. Sensing: TOU pricing analysis Current

  35. Sensing: TOU pricing analysis Current

  36. Sensing: TOU pricing analysis Current Proposed

  37. Solar + Storage: Cost-Efficient Energy Storage

  38. Smart grid vision Source: European technology platform: Smart Grids

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