carleton university iot presentation
TRANSCRIPT
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Smart Homes in the Smart Grid
Thomas Kunz
Professor, Systems and Computer Engineering
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The Many Aspects of “Smart Grid”
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Energy Management in Smart Homes
Whole system involves three networks1. 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
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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
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Optimizing Energy Consumption
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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.)
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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]>
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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 =Energypt=Price
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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.
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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
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Home Networking
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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)
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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
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Security
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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
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One-way Authentication Protocol Evaluations
Security NOT only a protocol issue: on-air monitors to monitorfor bogus messages, outlier detection to detect obviously faultyinformation
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Simulation Framework
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Evaluating Policy Alternatives: A User-Centered Simulation Framework
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Simulator Validation
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Sample Study: Charging EVs over Night based on Threshold Price
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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, ……