Transcript AEP Virtual Power Plant SG Demo Grid Interop 11-18

American Electric Power (AEP)
Virtual Power Plant Simulator (VPPS)
Tom Jones, Manger – Corporate Technology Development
American Electric Power
Grid-InterOp 2009
Denver, CO
Nov 17-19, 2009
Virtual Power Plant Simulator (VPPS)
–
VPPS Foundational System South Bend,
Indiana
AMI / AMR
10,000 Smart Meters
• Mesh Network Communications
• End-use Tariffs
• End-use Controls (Thermostat)
Dolan Technology Center - Laboratory
Test Bed for Modeling Real Resources
• Renewables (PV, Wind)
• Demand Response
• Storage
VPPS
• Distributed Generation
AEP Smart Grid Demo Topology
–
Changes to Existing Architecture
Utility Operations
Customer Premise
Advanced Monitoring,
Communications & Control
Energy
Storage
“High Demand Period”
“Delay wash 2 hours?”
“Please respond Yes or No”
Customer
Portal or Meter
Advanced
Monitoring,
Communications
& Control
LG Electronics
PHEV
Distribution
Operations
Adapted from EPRI source image
Distribution Secondary and End-Use
Changes to Existing Architecture
2. Capacitor Automation
a. Monitor status
b. Monitor VAr req’ts
c. Control to optimize VAr supply
.
Station
Feeder Circuit Breaker
C
Station
Communications
NC
Capacitors
NO
NO
Switches
Switches
NO
Capacitors
PHEV
NC
NO
C
C
Station
Station
NO
AMI
Energy Storage/DER
4. Demand Response and Distributed Energy Resources
a. Monitor and control end-use devices
b. Monitor and control DER systems and devices
c. Integrate into power system optimization
Station
3. Automated Meter Infrastructure
a. Outage notification
b. Automatic meter reading
c. Monitor voltage and load
d. Gateway to Home Area Network
Distribution Primary System
C
Changes to Existing Architecture
The Integrated Power System
≈
~
≈
~
Control
Point
Residential
Storage
≈
≈
≈
Monitoring &
Optimization
Center
≈
≈
NO/NC
Commercial
Fuel Cell
~
≈
≈
≈
Regional
Aggregation/
Control
≈
Solar
≈
Wind
Industrial
Interface Implications to Legacy Systems
–
The Virtual Power Plant Simulator
• Models “Load” as Controllable within bounds:
Real and Reactive Power
• Looks beyond the station to the end-use and customer
• Considers load as a “resource”, including distributed
energy resources, that could be controlled to relieve
system constraints
• Considers the distribution system as a potential resource
for contingency planning
Considerations for Emerging/Changing Requirements
Tariff
Flat Rate
Real Time Pricing
Demand
No Control
Critical Load Only
Storage
Daily Cycle
Instant Response
PHEV
On-Peak Charge
On-Peak Discharge
Fossil DG
Backup Only
On-Peak Supply
Solar
Wind
Fuel Cell
Cloudy
Sunny
Calm
Windy
Min Base Supply
Max Base Supply
External
Backup Only
Full Demand Supply
Month
24.57
Optimize for Cost
Optimize for Efficiency
Internal Power
Output
$
(e.g. Cost)
Year
Energy
Deficiency
Supply
Demand
Surplus Energy
Daily Time Cycle
The Smart Grid “Control Panel”
Improved Benefits from Architecture Changes
–
•
•
•
•
Optimizes resource allocation across power system
Harmonizes grid operation from end-use to RTO
Enables adoption of renewable and distributed resources
Permits real time optimization of system under current
operational opportunities and constraints
– System constraints
– Market value
– Environmental constraints
• Simulation prior to mass deployment reduces investment
and operational risk
Overall Project Lessons Learned
–
• Vision of Smart Grid as a Virtual Power Plant appears
technically achievable
• Operational requirements and impacts need to be
understood and optimized
• Economics and system benefits need to be understood
and quantified to optimize resource allocation
• Alignment of vision and public policy is needed to
effectively capture societal benefits
• Collaboration between industry, academia, and
government is required
• The EPRI/AEP Virtual Power Plant Simulator (e.g.
OpenDSS platform) Smart Grid Project permits stepwise
evaluation of the various systems and components of a
smart grid, including cross-impact analysis
Thank You! Q&A
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