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ARPA-E Electricity Research Programs
Tim HeidelProgram Director
Advanced Research Projects Agency – Energy (ARPA-E)
U.S. Department of Energy
PSERC Summer Workshop
July 15, 2015
The ARPA-E Mission
1
Ensure America’s
• National Security
• Economic Security
• Energy Security
• Technological Competiveness
Catalyze and support the development of
transformational, disruptive energy technologies
Reduce Imports
Reduce Emissions
Improve Efficiency
GENI
REACT
BEETIT
METALS
AMPED
GRIDS
HEATS
Solar ADEPT
FOCUS
ARID
MOSAIC
GENSETS
REBELS
ADEPT
SWITCHES
A portfolio enabling a secure, affordable, and sustainable electricity future.
NODES
GRID DATA
3
U.S. Carbon Emissions (2013): 5,390 MMT
4
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Wind
Solar/PV
Geothermal
Nuclear
Hydro
Natural Gas
Petroleum
Coal
Biomass
Biomass
Coal
Oil
Nat. Gas
Source: EIA
U.S. Primary Energy Consumption
5
0
20
40
60
80
100
120
Wind
Solar/PV
Geothermal
Nuclear
Hydro
Natural Gas
Petroleum
Coal
Biomass
U.S. Primary Energy Consumption (Quads)
July 16, 2015 6
U.S. Electricity Consumption
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
1949
1953
19
57
1961
1965
1969
1973
19
77
1981
1985
1989
1993
19
97
2001
2005
2009
2013
Solar/PV
Wind
Geothermal
Waste
Wood
Nuclear
Petroleum
Natural Gas
Conventional Hydro
Coal
7Source: National Solar Radiation Database, NREL
Variability & Uncertainty
Emerging Power System Challenges
8
– Increasing wind and solar
generation
– Decentralization of generation
– Aging infrastructure
– Changing demand profiles
– Increasing natural gas generation
– Cybersecurity threats
‣ All of these challenges require
greater power system flexibility.
Evolution of Grid Requirements
GRID
Modernization
Affordable
Safe
Accessible
Reliable
Clean
Secure
Resilient
Flexible
Federal Power Act
1930s
Blackouts
1960s
Oil Embargo,
Environmental concerns
1970s
9/11
Stuxnet
2000s
Hurricanes
Katrina, Sandy
Polar Vortex
2010s
Increasing Dynamics
and Uncertainty
2020s
Source: Adapted from DOE Grid Tech Team
10
Responsive Demands
- Scheduling large loads (eg. industrial loads)
- Mobilize large numbers of small assets
Power Flow Controllers
- AC Power Flow Controllers
- High Voltage DC Systems
Energy Storage Optimization
- Scheduling energy flows
- Coordination of diverse storage assets
Transmission Topology Optimization
- Optimal line switching
- Corrective switching actions
‣ Advances in power electronics, computational technologies, and
mathematics offer new opportunities for optimizing grid power flows.
New Potential Sources of Network Flexibility
Project Categories
GoalsDuration 2012-2015
Projects 15
Total
Investment$39 Million
GENI ProgramGreen Electricity Network Integration
• Enable 40% variable generation penetration
• > 10x reduction in power flow control hardware (target < $0.04/W)
• > 4x reduction in HVDC terminal/line cost relative to state-of-the-art
• Power Flow Controllers
• Power flow controllers for meshed AC grids.
• Multi-terminal HVDC network technologies.
• Grid Optimization
• Optimization of power grid operation; incorporation of uncertainty into operations; distributed control and increasing customer optimization.
12
Power Flow Control White Space
• High costs and reliability problems are often cited against the widespread
installation and use of power flow control devices.
• New hardware innovations that can substantially reduce the cost of
power flow control devices are needed
• Fractionally rated converters (limited power device ratings).
Modular designs (increases manufacturability).
Series connected equipment with fail normal designs (gradual degradation).
Historically, power flow control devices have typically been manually
dispatched to correct local problems.
• New software advances that exploit new developments in
optimization and computational technologies are needed to enable
the real time coordinated, optimized dispatch of many power flow
control devices.
Power Flow Controllers
13
Inverter
Based Variable
Series Voltage
Injection
Power
Flow
Control
Toolkit
AC
Embedded
HVDC Links
Transformer
Based
HVDC Line
LCC/VSC
HVDC
Back-to-
Back
Multi-Terminal
HVDC
Variable Series
Reactance
Insertion
Xc
XL
Topology Control
(Line Switching)
Advances in Power Electronics (Components and Circuits)*
Fast, Reliable, Ubiquitous Communications
* ARPA-E’s ADEPT, Solar ADEPT, and SWITCHES programs
are funding some of these advances.
Grid Optimization Whitespace
‣ Existing grid optimization tools do not explicitly account for
variability and uncertainty
‣ Emerging need/opportunity to coordinate larger numbers of
distributed resources
‣ Recent advances enable more robust, reliable optimization of the
electricity grid despite:
• The limits of state estimation (finite numbers of sensors, limited models)
• Incomplete and imperfect information flow (due to latency of communications)
• Constrained computational resources for dynamic decision support (power
flow optimization is mathematically (NP) hard)
• Inherent uncertainties in price/market mediated transactions
• Physical constraints to control (cost, performance, and reliability of power
electronics).
14
Grid Optimization Opportunities
15
AC-Optimal
Power Flow
Stochastic
Optimization
Distributed
Optimization
Forecasting &
Dispatch of
Demand
Transmission
Switching
Energy
Storage
Optimization
Fast dynamic
stability
calculations
Grid
Optimization
Toolkit
Advanced Computing Architectures & Cloud Computing Infrastructure
New Optimization Methods & Advanced Solvers
GENI Portfolio
16
HVDC
EPR Cable
HVDC Multi-terminal
Network Converters
DC Breaker
HVDC Hardware
Power Flow Control Hardware
Cloud Computing
& Big Data
Topology Control
(Line Switching)
Distributed Series
Reactor
Magnetic Amplifier
Economic Optimization Contingency Management
Demand Response
Resilient Cloud /
Data Replication
Compact Dynamic
Phase Angle Regulator
Transformerless UPFC
Power System Optimization
Stochastic
Unit Commitment
Distributed Grid
Optimization (Prosumers)
Energy Storage
OptimizationAC-OPF
GENI Program Participants
17
Texas Engineering
Experiment Station
Lead Organizations
Subs/Team Members
CRA
GE
CIT
Varentec
Smart
Wire
AutoGrid
Univ of CA, Berkeley
Arizona
State Univ
Grid Protection
Alliance
Applied
Communication
Sciences
PJM
Boston UnivNortheastern
Tufts
Polaris Systems
OptimizationParagon Decision Technology
NCSU
SCE
Waukesha
Electric
Systems
MSU
BoeingInnoventor
New Potato
Technologies
Columbia Univ
Georgia
Institute of
Tech
RPI
MSU
LBNL
LLNL
ORNL
SNLGeneral
Atomics
CMU
Cornell
University of
Washington
Iowa St
Alstom
EPRITVA
Univ of CA,
Davis
WSU
UT-
Knoxville
ISO NE
OSI Soft
18
‣ Functions as a current limiter
to divert current from
overloaded lines to
underutilized ones
‣ Increases line impedance on
demand by injecting the
magnetizing inductance of a
Single-Turn Transformer
Distributed Series Reactors
‣ Two modes of operation:
– Autonomous (set point)
operation
– Two way communications
enabled for greater control
and line monitoring
19
TVA DSR Array Installation: October 15-20, 2012 99 Units
Field Testing Ongoing
Compact Dynamic Phase Angle Regulators
20
‣ Fractionally-rated converters (AC switches/ LC
filters).
‣ ‘Fail-normal’ bypass switch preserves system
reliability.
‣ 3-phase CD-PAR operation verified at 13 kV 1
MVA.
‣ Field test at Southern Company this year
‣ Target: $20-30/kVA of power controlled
‣ Modeling dynamic and steady-state impact of
CD-PAR at both distribution and transmission
Two-way wireless communication
Ain
Bin
Cin
Aout
Bout
Cout
+ +
Controller
Bypass Switch
13 kV isolated power supply
Gate drivers
Gateway PC
Fractionally rated power converter
13 kV Auto-transformer
Isolation Switch
Isolation Switch
No-bulk DC storage
21
Medium Voltage Mesh Power Flow Test Bed
5-Bus,12 kV meshed power flow test
bed built at NEETRAC .
22
Prototype (1-Phase) 7.5 MVA CVSR
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
0 200 400 600
AC
Win
din
g R
eac
tan
ce (
Ω)
DC “Control” Current (A)
Factory Test Results
ac 1500A
ac 1000A
ac 750A
ac 500A
ac 250A
Magnetic Amplifier for
Power Flow Control
• Inserts a controlled variable inductance
• Power electronics isolated from the HV
line
• Low power converter controls the high
voltage ac inductance
• Standard transformer manufacturing
methods
Transformer-less Unified Power Flow Controller
23
‣ Cascaded multi-level inverters (CMIs)
to eliminate transformers
– Modular, scalable design
– Low cost ($0.04/VA)
– Lightweight (1000 lbs/MVA)
– High efficiency (>99%)
– Fast dynamic response (<5 ms)
‣ Project goals:
Assemble and test 100 CMI sub-
modules
Prototype a 2-MVA CMI UPFC
Pilot test/demonstration of the
proposed UPFC on MSU’s
campus.
Transformer-less Unified Power Flow Controller
24
New Power System Programs in 2015
‣ NODES (Network Optimized Distributed Energy Systems)
– Reliably manage dynamic changes in the grid by leveraging flexible
load and Distributed Energy Resources’ (DERs) capability to provide
ancillary services to the electric grid at different time scales.
‣ GRID DATA (Generating Realistic Information for
Development of Distribution And Transmission Algorithms)
– Development of large-scale, realistic, validated, and open-access
electric power system network models (transmission and distribution)
that have the detail required for the successful development and
testing of transformational power system optimization and control
algorithms.
‣ OPEN 2015
– Transformational research in all areas of energy R&D, covering
transportation and stationary applications.
25
What happens after ARPA-E?
26
Energy Technology “Valleys of Death”
R&D Prototype Demonstration Commercialization
Investm
ent
Time
Valley of
Death #1:
Public
Funds
Valley of
Death #3:
Venture
Capital/
Private
Equity
Valley of
Death #2:
Follow-on
Development
Funds
27
Currently Seeking New Program Directors
ARPA-E is continually recruiting new Program Directors, who serve 3-year terms
‣ R&D experience; intellectual integrity, flexibility, and courage; technical breadth; commitment to energy; communication skills; leadership; and team management
‣ A passion to change our energy future
Please contact me If you are interested.
ROLES & RESPONSIBILITIES
Program development
‣ Perform technical deep dive soliciting input from multiple stakeholders in the R&D community
‣ Present & defend program concept in climate of constructive criticism
Active project management
‣ Actively manage portfolio projects from merit reviews through project completion
‣ Extensive “hands-on” work with awardees
Thought leadership
‣ Represent ARPA-E as a thought leader in the program area
ATTRIBUTES
29
www.arpa-e.energy.gov
Tim Heidel
Program Director
Advanced Research Projects Agency – Energy (ARPA-E)
U.S. Department of Energy
Highly Dispatchable, Distributed Demand Response
Objectives: • Develop scalable SaaS platform
(DROMS-RT) for optimization and
management of Demand Response
(DR) programs.
• Standard communications protocols
for real-time DR signaling.
• Utilize machine learning to forecast
and characterize customer response
to DR signals.
• Optimization of economic dispatch
with DR.
30
Potential Impact: • Enable Real-Time predictive analytics on data from grid customers & sensors.
• Provide 90% reduction in the cost of operating DR programs by eliminating up-
front IT infrastructure costs for utilities.
• Increase the overall efficiency of DR operations by 30-50%.
Project Accomplishments
‣ Developed scalable cloud-based
platform for managing and
analyzing big-data sets for
energy applications.
‣ Demonstrated highly parallel
machine learning engine capable
of processing >1M forecasts on a
rolling basis every 10 min.
‣ Deployed commercial DR
programs up to 70K customers.
31
Post ARPA-E Goal: “Energy Data Platform”: 10X Reduction in the Cost
and Time to Market of Developing New IT/OT Apps
Transmission Topology Control Algorithms (TCA)
Objectives:
• Develop fast optimization, contingency analysis
and stability evaluation algorithms to allow grid
operators to optimize transmission topology (line
switching) in real time.
Potential Impact:
• Significantly lower generation costs
• Provide additional controls to manage congestion.
• Enable higher levels of renewable generation.
Accomplishments:
• Developed detailed model of PJM historical
operating hours (data supplied by PJM)
• Developed tractable topology control algorithms
using sensitivity-based heuristics and a reduced
MIP formulation of the TC problem. Practical
solution times reached (below 5 minutes in PJM).
• Developed fast state estimation and transient
stability algorithms to support the TC decisions
Estimated TCA Benefits
‣ Hybrid historical-high renewables simulation cases for PJM
– One power flow snapshot per hour for three representative historical weeks in 2010 (one per season)
– Renewables data from PJM Renewable Integration Study: 30% Low Off-shore Best sites On-shore Scenario
‣ Renewable curtailments were reduced on average by 40%
33
31%
64%
84%
98%
99%
Renewable curtailment reductions with Topology
Control Algorithms (Winter Week)
$0M
$2M
$4M
$6M
$8M
Summer Winter Shoulder
Production Cost Savings
Remaining Cost of Congestion
Weekly Cost of Congestion and Savings‣ Production cost savings in PJM RT markets under 2010 conditions were estimated to be > $100 million/year
‣ Savings of over 50% of Cost of Congestion
(Based on simulation results for three historical weeks)
Production Cost Savings = production cost without TCA (full topology)
– production costs with TCA
Cost of Congestion = production cost with transmission constraints
– production costs without transmission constraints