princeton university and the smart grid, chp, and district
TRANSCRIPT
Princeton University and the Princeton University and the
Smart Grid, CHP, and Smart Grid, CHP, and
District EnergyDistrict Energy
Thomas NyquistDirector of Facilities Engineering
Princeton University
Michael WebsterCIO & CEO
Icetec Corporation
Executive SummaryExecutive Summary
In 2003, the State of New Jersey moved to real-time pricing in the electric
market for high tension service. Princeton reacted by adopting the following
smart grid strategies:
Changed its plant production strategies for power, steam, and chilled water to
be market price driven. Saves 10%-15% of annual energy costs.
Princeton reduced its electric load on the grid during the grid’s peak demand
periods, thus reducing stress on the grid and lowering Princeton demand costs.
Princeton essentially stores electric power by using power at night to produce
large quantities of chilled water for use in the day.
Currently, evaluating how to use dispatch strategies to minimize carbon dioxide
emissions. Need real-time emissions data from the grid operator.
Smart GridSmart Grid
According to the United States Department of Energy’s Modern Grid Initiative report - a modern smart grid must:
(Smart Grid items in colored font are incorporated into Princeton’s Economic Dispatch, CHP, and District Energy Systems.)
• Be able to heal itself
1 - Motivate consumers to actively participate in operations of the grid and Enable
electricity markets to flourish.
2 - Resist attack and Provide higher quality power that will save money wasted from
outages.
3 - Accommodate all generation and storage options
4 - Run more efficiently
CHP and Chilled Water Plant Schematic
District Energy at Princeton UniversityBuildings on District Steam Shown in Red
District Energy at Princeton UniversityBuildings on District Chilled Water Shown in Dark Blue
1 “Motivate consumers to actively participate in
operations of the grid” and “Enable electricity markets to flourish”
Predictive electric pricing allows the plant operators to dispatch equipment based upon electric price, fuel price, business rules for equipment operation, and predicted load.
Generally – we buy power and consume more power when there is excessive power on the grid and we make power and consume less power when the system is stressed and the cost of power is high.
1A Plant Equipment Dispatch in Real Time Market
ICETEC
PJM Electric Price
NYMEX gas, diesel,
biodiesel prices
Current Campus
Loads
Weather Prediction
Production
Equipment
Efficiency &
Availability
“Business Rules”
Generate/Buy/Mix
Preferred Chiller &
Boiler Selections
Preferred Fuel
Selections
ICAP &
Transmission
Warnings
Operating Display
& Historical
Trends
Live feedback
to Icetec
Operator
Action
Biodiesel REC value
& CO2 value
1B Real Time Price Signals
Impossible to run a plant and follow this price
signal – need predictive pricing model
1C Integrated Smart Dispatch
+
=
Load modeling Market Volatility Modeling
Interactive Adaptive Dispatch
1D Load and Price Prediction
1E Plant Dispatch ScreenshotSimple Instructions to Plant
Operators
1F Cogen Dispatch
5 minute System Electric Price (green)
Cogen Output (red)
Hourly System Electric Price (blue)
Electric price rises &
turbine output goes up
1G Dispatch Benefits in Real Time Market
• Buy large amounts of electricity and turn down our generator when the price of grid power is low.
• Self generate to save energy costs when grid price is high.
• Saves $2.5M - $3.5M in energy costs.
2 Resist attack and Provide higher quality power that will save money wasted from outages
As applied to Princeton:
• CHP allows us to run significant portions of the campus should the grid go down.
• CHP reduces effects of utility power quality problems.
• Computerized dispatch system does not control our equipment – operators do. This insulates the plant from computer viruses.
3 Accommodate all generation and storage options
• CHP since 1996
• Chilled water storage
since 2006
• Backpressure turbines
installed in 2009*
• Solar PV to be completed in 2009
* First use of back pressure turbines dates back to the 19th century.
VIX values for TES Dispatch ExampleVIX values for TES Dispatch ExampleGreen line indicates power prices
Red line indicates Volatility Index Value
3A Electric Price Prediction
3B Optimal TES Dispatch in Real Time Electric Market
3C Dispatch Effects on CampusElectric Power Use
Green line indicates power prices
Red line indicates Campus Load
Campus Load for TES Dispatch ExampleCampus Load for TES Dispatch Example
3D Storage and Generation Benefits
• Reduces campus and grid electrical demand
• TES provides immediate capacity when a
chiller trips offline.
• TES saves $700K in annual energy costs.
4 Run more efficiently
• Princeton demand on major substation is zero when grid is at maximum (stressed) load. Reduces future transmission and power plant needs
• Reduces need for expensive generation during peak periods. If used on larger scale, this operation will reduce electric costs on the grid by keeping the most expensive generation off-line.
4A Power Grid Benefit
Princeton Demand
Grid demand
4B Demand Reduction Strategies
• Gas Turbine in CHP plant run at full capacity
• Chilled Water Storage Tank discharged within 4 ours. All electric motor driven chillers and related equipment are turned off. Steam turbine drive chillers run at full capacity.
• Reduced campus lighting.
• HVAC systems at reduced capacity.
• Local building chillers off.
4C Light Dimming Systems
Light systems can dimmed or be turned off because:
• Space is lit by daylight
• Space is over lit
• No occupancy
• Demand control due to high electric grid
loads and costs
• Occupant choice
4D Annual Generation(RPM/ICAP) & Transmission Savings
• RPM $390,000
• Transmission $110,000
Conclusions
• District energy , CHP, and chilled water storage have significant benefits to the utility grid and can be operated with most “smart grid” functions.
• Predictive electric pricing allows for optimization of assets and load in the real-time electric market to the benefit of the grid and the owner.
• Real time carbon dioxide emissions from the grid (if known) could be used to minimize a district energy systems carbon footprint by affecting the equipment dispatch schedules.
Contact InformationContact Information
Thomas Nyquist
Director of Facilities Engineering
Princeton University
MacMillan Building
Princeton NJ, 08543
609 -258-5472
www.princeton.edu
Michael Webster
CEO
Icetec Corporation