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
, 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
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.)
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.
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.
<[∞, ∞,... ∞],[p1,p2,....,pt]>
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
, Unified Optimization: solve many issues at the same time: load
scheduling, trading in the microgrid (both amount and price), storage
– 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.
Proposed Optimization Model
, Determine the user’s energy
consumption and generation
– Module 1: considers renewables and
, 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
, 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
– AODV/ZigBee routing
, Joint-path strategy
, Backbone-based path strategy (packet forwarded firstly through the
, Dual-path strategy (wireless path strategy plus backbone-based path
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
, 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
– Challenge-Response: less computationally complex, based on shared key,
requires bi-directional communication
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
Sample Study: Charging EVs over Night based on
, 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, ……