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Carleton University IoT presentation

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  • Describe each block
    Explain a typical simulation run
  • Transcript

    • 1. Smart Homes in the Smart Grid Thomas Kunz Professor, Systems and Computer Engineering
    • 2. The Many Aspects of “Smart Grid”
    • 3. Energy Management in Smart Homes Whole system involves three networks 1. Utilities communicate ToD pricing info: here RBDS (one-way broadcast network) 2. Appliances and Smart Controller communicate over in-home networks: • HomePlug C&C: powerline in-home network • ZigBee: wireless in-home network
    • 4. Research Challenges/Issues , How to optimize energy consumption: home controller (centralized) or smart appliances (distributed) need to perform optimizations – Having residential users operate appliances manually will be less promising – Complexity of optimization problem? , Appliances and home controller need to communicate – Network alternatives – Improving existing network protocols , Utilities broadcast ToD price info – Subject to impersonation attacks – Can we authenticate messages in a one-way broadcast network? , Explore impact of design alternatives – For example: what impact will EVs have on residential energy consumption – Exploring new coordination mechanisms
    • 5. Optimizing Energy Consumption
    • 6. Optimizing Residential Energy Usage • Goal: wide-spread participation of users to reduce peak power consumptions and balance load • The potential for profit and the cost saving features of smart grids are excellent motivating factors • Needs automation to be really convenient • In smart grid – the user is considered as a ‘Prosumer’ because • The user produces energy (renewables, selling via microgrid, etc.) • The user consumes energy (appliances, buying from microgrid, etc.)
    • 7. Optimization Inputs: Energy Consumption , Energy consuming components: – Inelastic load cannot be delayed. – Elastic load can be delayed and its quantity depends on price of electricity. – The storage can be considered as an elastic load. – Selling energy to microgrid can be considered as load. Demand Microgrid <[e1,e2,...,et]> Storage <[e1,e2,...,et]> Elastic Load <[e1,e2,...,et]> Inelastic Load <[e1,e2,...,et]>
    • 8. Optimization Inputs: Energy Sources , Energy sources: – Utility is considered to have infinite supply and dynamic price. – Storage provides time varying supply. – Microgrid has different energy quantity with different price. – Renewables have different generation profile, price is considered as 0. Supply Utility <[∞, ∞,... ∞],[p1,p2,....,pt]> Storage <[e1,e2,...,et]> Microgrid <[e1,e2,...,et],[p1,p2,...,pt]> Renewables <[e1,e2,...,et]> et =Energy pt=Price
    • 9. Unified Optimization Model Problems , Both storage and microgrid can act as both load and energy source. , This reciprocal relationship makes it more complex to formulate an optimization problem , Unified Optimization: solve many issues at the same time: load scheduling, trading in the microgrid (both amount and price), storage charging, …. – Optimization problem not linear – Multiple households: multiple objective functions, pareto-optimal solutions – Solution time grows rapidly with number of households, planning horizon, number of appliances, etc.
    • 10. Proposed Optimization Model , Determine the user’s energy consumption and generation characteristics – Module 1: considers renewables and storage. , Buying components – Module 2: Considers utility, microgrid (buyer) and storage. , Selling Components – Module 3: Considers microgrid (seller) and storage. , Solve iteratively The Modular Optimization Model
    • 11. Home Networking
    • 12. Home Networking , Many choices: Wireless, Powerline, Wired…. , If mixed networking, which network protocols , Developed/modified existing network simulator (NS2) to support multiple interfaces/networking technologies, explored alternative routing protocols: – Flooding – AODV/ZigBee routing , Joint-path strategy , Backbone-based path strategy (packet forwarded firstly through the backbone) , Dual-path strategy (wireless path strategy plus backbone-based path strategy)
    • 13. Summary of Routing Insights , Combined network performance better than using a single network (powerline or wireless) , Flooding best network layer strategy when communicating information to ALL devices in the home , To communicate with a specific device, dual-path and backbone- based routing superior to joint-path routing in terms of PDR – Dual-path: lowest latency – Backbone-based routing: lowest energy costs
    • 14. Security
    • 15. Security Challenges , ToD messages broadcast in one-way RDBS network – what happens if intruder broadcasts fake messages – For example: broadcast low price during heat wave => AC units will kick in => grid load rises, potentially leading to overload , Network Security: – Confidentiality not important – Source authentication crucial , Common solutions not applicable in the absence of two-way communication – Certificates: complex verification algorithm, need occasional access to certificate authorities – Challenge-Response: less computationally complex, based on shared key, requires bi-directional communication
    • 16. One-way Authentication Protocol Evaluations Security NOT only a protocol issue: on-air monitors to monitor for bogus messages, outlier detection to detect obviously faulty information
    • 17. Simulation Framework
    • 18. Evaluating Policy Alternatives: A User-Centered Simulation Framework
    • 19. Simulator Validation
    • 20. Sample Study: Charging EVs over Night based on Threshold Price
    • 21. Conclusion , Lots of specific challenges, some solutions, typically we need to write papers to talk about them , Hard to do a complete “system” when in university – Real smart home data – Actual smart devices/appliances , Was offered an electric hot water tank once, not sure where to put it….  , Sometimes problems are those that we think are important, but may not be the most pressing issues in the real world , Collaborations with industry helpful, various ways to do this and get funding for it – MITACS, NSERC Engage, ……

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