Smart Grid R&D Program AOP Review - Energy

15 Pages·2012·1.03 MB·English

by  Paul Wang

2012 Smart Grid R&D Program
Peer Review Meeting

DE-OE0000549: Enhanced Distribution
Management System Capabilities Supporting
Distribution Network Distributed Energy
Resources
Tristan E. Glenwright
The Boeing Company
June 8, 2012

Copyright © 2012 Boeing. All rights reserved.
DE-OE0000549
Enhanced Distribution Management System Capabilities Supporting
Distribution Network Distributed Energy Resources
Objective
Market Operator
Scalable
1. Determine thresholds of Distribu ted Energy Resource (DER) Transmission
penetration in distribution grids that drive significant impacts to FSeaulfl tH Teoalleinragnt
Distribution Network
network stability and reliability Substations
Retail Energy Industrial
Suppliers
2. Validate ability of Boeing Distribution Management System Community
Microgrids
(BDMS) advanced controls to mitigate effects of increased DER Commercial /
Campus
and to leverage DER and DR for SAIDI and Load Factor Distribution Local Planning and Control Automated Islanding
Utility
improvement Enhanced
Forecast Fault Tolerant
Self Healing Grid Cyber
3. Demonstrate interoperability and secure communication Agents
Secure Legacy Interoperability ROepltiiambiilziattyi oannd Economic
between utility management systems, associated databases,
Dynamic Modeling and Forecasting Distributed
Intelligence
and distribution engineering modeling and analysis tools Metered
Loads
4. Advance the capability of distribution engineering modeling tools Enhanced
Forecast
Distributed Energy
to model smart grid operations Efficiency Resources
24
Life-cycle Funding
Technical Scope
Summary ($K)
• System Definition– Define Modeling and Simulation

architecture and scenarios, use cases, product
architecture and requirements; integrate and test system
Prior to FY12, FY13, Out-year(s)
functionality against initial Dynamic Grid Model (DGM) of
FY 12 authorized requested
ComEd footprint
297.8 2,596.7 2,118.8 564.0
• System Design – Refine system use case definition; test
BDMS against refined DGM in software environment;
simulate load factor and SAIDI impact to distribution grid
with increasing DER penetration; validate BDMS controls
behavior in live hardware environment
• System Demonstration – demonstrate BDMS benefits
against current-state and future-state distribution grid
December 2008
performance 2
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Significance and Impact
December 2008
3
Copyright © 2012 Boeing. All rights reserved.
Smart Grid R&D Cost & Performance Targets
Long-term Goals
BDMS
Self-healing Distribution Grid Integration of DER/DR/PEV BDMS supports
leverages DER for Improved Reliability for Improved System Efficiency this goal
to self-heal
(DER/DR)
distribution grid
2020 Targets 2020 Target
Demonstrating BDMS capabilities Demonstrating BDMS capabilities for fast
20% SAIDI reduction >98% reduction in outage 20% load-factor
against Dynamic Gridi nM disotrdibeutli oonf o utages time ovf orelqtuairgeed loreadgs ulation with high penimeptrorvaetmioennt
Distribution Network with increasing of renewables (PV) against Dynamic Grid
DER (including PV) Model of Distribution Network
Annual Performance Targets
2012 2013 2014 2015 2016
Demonstrate Demonstrate a smart Enable fast voltage Complete two Demonstrate
integration of microgrid at a regulation integrated combined use of fault
renewable and military base for technology to distribution detection, isolation,
distributed systems >98% reduction in support integration management and restoration
for 12% load factor outage time of of high penetration systems capable of technologies with
improvement on a critical loads of distribution-level reducing SAIDI by integrated distribution
distribution feeder PV for 15% load 5% management systems
circuit factor improvement to reduce SAIDI by 10%
on the
demonstration
feeder circuit December 2008
Copyright © 2012 Boeing. All rights reserved.
Smart Grid R&D Cost & Performance Targets
Notional graphs showing benefit of advanced controls as a function of DER penetration
1
w/o BDMS
with BDMS

r
o
I
t D
c
a I
A
F w/o BDMS
S

d
a
o
L
with BDMS
DER Penetration DER Penetration
• Project will analyze load factor and SAIDI improvement as a function of DER penetration for a
typical section of ComEd’s distribution network
• DER penetration below threshold level has little to no affect (current state)
• BDMS real-time controls enable a higher load factor as DER is increased
• BDMS will leverage DER to power stranded network segments, reducing outage durations
• Facility based microgrids with local generation and control will have reduced outage duration,
but may not be considered in SAIDI metric improvement (dashed red line)
December 2008
Copyright © 2012 Boeing. All rights reserved.
Technical Approach & Transformational R&D

December 2008
6
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Conceptual Future View
DER
Market Operator
Scalable
Transmission
Self Healing
Distribution Network
Substations
Industrial
Retail Energy
Suppliers
Community
Microgrids
Commercial /
Campus
Distribution Local Planning and Control Automated Islanding
Utility
Enhanced
Forecast Fault Tolerant
Self Healing Grid Cyber
Agents
Reliability and Economic
Secure Legacy Interoperability Optimization
Dynamic Modeling and Forecasting Distributed
Intelligence
Metered
Loads
Enhanced
Forecast
Distributed Energy
7
Efficiency DReescoeumrcebs er 2008
Copyright © 2012 Boeing. All rights reserved.
Technical Approach
Boeing BDMS Manual Topology
Changes simulating
Simulated
Existing Grid DER outage situations
Distributed SCADA/OMS Simulation Model Interface
Systems Reliability Optimization
DER Data
(SCADA,O and Stability and Market
Control
MS, etc) Analysis Participation
Secure Distributed Operations Service Bus
Dynamic Meter Data
and Switch States
Role Based HMI Cyber Secure
Control Functions
Switch Changes
to Remote Assets
Dynamic Grid Model
(Power System “Stand-In”)
SCADA Operator OMS Operator DR Program Substation
Lead
Substation
Gateway IED Vreg/LTC
BF Control RTU Relays
Area Manager
Boeing BF SAM BF SAM BF SAM
BDMS BF SAM
Controllable Solar Conventional
Loads/BMS Inverter Distributed Cap Bank
Facility
Systems Control Generation
Microgrid
December 2008
Copyright © 2012 Boeing. All rights reserved.
Target Area Dynamic Grid Model
•Dynamic model of
section of ComEd 2-3
132 kV
SW_71 SW_72 SW_73
distribution network TRF-L TRF-C TRF-R
•Created from ComEd FDR-1 FDR-2 FDR-3 CB_TR71 FDR-4 FDR-5 CB_1-2 FDR-6 CB_2-3 FDR-7 CB_TR73FDR-8 FDR-9 CB_3-4FDR-10CB_TR72FDR-11 FDR-12CB_4-5FDR-13
12.5 kV
CB_1 CB_2 CB_3 CB_4 CB_5 CB_6 CB_7 CB_8 CB_9 CB_10 CB_11 CB_12 CB_13
GIS extract
475 CB_2J5
•60MW Peak CB_1H6
2J5
CB_1A5 587 11H.56 MVA 215 0.75 MVA
•One substation with 15
12A.05 MVA CB_1AB 105 605 653
Feeders (7 used for
CB_1K7 560 1AB
0.75 MVA 350 375 151 137 057
experiment) 1K7 491
2.5 MVA 088 311 558
•Enhanced with following CB_1RR6 064 C1UB4_ C1AB8_ C1BJ4_ CB_1W9 328 046 580
1R6 CB_3A9 CB_1N1 298
scalable DER: 1.0 MVA 1U4 1A8 1J4 1W9
442 M2V.5A M1V.5A M0.V7A5 M0.V7A5 13.A39 MVA 12N.51 MVA 189 294 585 CB_3A1 292
•Solar characterized CB_3R5 081 3A1
3.5 MW 3R5 361 322 059 0.75 MVA
by local 10MW 349 1.5 MVA CB_4CC 299 R 622 402
n.c. n.c.
n.o.
installation 4CC
n.o. n.o. 1.0 3.5 MW CB_3L4 410 568
MVA
•Residential Solar
n.o.
480 V 3L4
0.75
•Industrial site MVA
DGEN1 RBS MVE HVAC DGEN2 FLL TNL ZLS
0.6 0.4 0.5 0.6 0.6 0.005 0.4 0.15
Microgrid MVA MVA MVA MVA MVA MVA MVA MVA Added DER
Industrial Site HCL1 HGEN1 HEL1 HCL2 HGEN2 HEL2
0.7 1.2 0.3 0.7 1.2 0.3
MVA MVA MVA MVA MVA MVA
•Critical commercial Critical Commercial Site
site Microgrid December 2008
Copyright © 2012 Boeing. All rights reserved.
Technical Accomplishments

BDMS Tier 1 Schedule
5/22/12
2011 2012 2013 2014
Tasks
J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J
Contract Definitized Customer SRR CDR ORR / Final Demo
Program
DOE PM ‘Kick Off’ Approval to Proceed to Phase 2 Approval to Proceed to Phase 3
Milestones
Project Complete
Key Events Budget Period 1 Budget Period 2
Phase 1
BDMS System Definition
Phase 2
BDMS System Design
Phase 3
BDMS System Demonstration
Test Events BCP 1 BCP 2 BCP 3 HWIL 1 HWIL 2
December 2008
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Boeing Proprietary