Transactive Residential Electricity Supply
Annabelle Pratt Principal Engineer Power Systems Engineering Center
NREL is a national laboratory of the ...
Annabelle Pratt Principal Engineer Power Systems Engineering Center
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.
Homes matter ~125 million single-family homes in the US ≈ 37% of the electricity load
Residential loads are changing Combine energy efficiency and renewable energy generation
Typical Home
Energy Efficient Home
0
6
Reduced load
Power flow from building to grid
12
18
24
ZNE Home
PV
Use of storage will bring further changes
Significant ramp late afternoon as PV output reduces
Home Automation
Source: http://www.smarthome.com/
Home Energy Management Systems •
More intelligence included in products – – – – –
Focused around thermostat, often hub for other devices “easy to use automation, location-based optimization, intelligent learning“ “energy algorithms ... minimizes homeowner energy consumption“ “optimized demand response ... cool each home prior to the DR event“ “home simulation model ... deliver highly accurate predictions of households‘ energy consumption“ – “an algorithm that takes into account ... preferences of the occupants, ... and the weather ... dynamically adjusts the target temperature throughout the event. ... achieves significant load reduction without impacting user comfort“ – “coordinated by a home gateway that controls the battery, water heater and inverter to maximize solar PV generation and self-consumption“
•
Significant academic research activity – different optimization formulations – stochastic/robust techniques
•
Challenges – return on investment and high reliability
B. Daryanian and L. Norford, “Minimum-cost control of HVAC systems under real time prices,” 1994.
Home Energy Management System (HEMS) • Co-optimization objectives: • • • • •
•
Cost Discomfort Total consumption Peak consumption Carbon emissions Grid export
• Model Predictive Control • Stochastic
Simulation Tools • Co-simulate grid, buildings, markets, controls Integrated Energy System Model
Price Responsive Demand: high-pen HEMS
Modeled ~500 houses on feeder with time-of-use pricing and HEMS optimizing thermostat setpoints for cost & comfort • Impact on occupant comfort • Impact on grid: peak load, voltage
Cost Discomfort Total consumption Peak consumption Carbon emissions Grid export
• Model Predictive Control • Stochastic • Transactive-ready: 1. React to a price signal 2. Return information, e.g., a power forecast back to a central controller 3. Automatically act on behalf of the homeowner
Aggregator/DMS interfaced with HEMS Power Profile
Supervisory level aggregator/DMS
Setpoints Room temperature and HVAC power
Electricity Price
Smart Home Test Bed Analog signals
EnergyPlus (simulates smart home)
HEMS hardware
PV Simulator
HIL Control computer
Power
Comms
Optimization/Co ntrol HEMS IESM cosimulation tool
Weather data
Smart Home PCC
Environmental chamber control
Smart home hardware in laboratory
AC Power Real-Time Amplifier Simulator
GridLAB-D: Feeder with many houses
Simulation on Peregrine
Accelerate and reduce cost of testing by combining large-scale software simulation with hardware evaluation of a small set of representative systems
Initial Smart Home Test Bed Results • Simulation: 13 node IEEE test feeder with 20 homes • One home : air conditioner and thermostat hardware • Currently adding hardware: o controlled: EVSE, water heater o not controlled: PV, fridge, stove, washer/dryer, lights
For Internal Navigant Use Only
In summary • Residential loads impactful and changing: Energy efficiency & distributed generation o Home automation – increased adoption o Sophisticated HEMS – under development o
• Simulation tools should reflect changing assets o
