Transcript Power Flow and Harmonic Solution Modes

Distribution System
Analysis for Smart Grid
Roger C. Dugan
Sr. Technical Executive, EPRI
Webcast
Feb 8, 2011
EPRI Power Systems Modeling/Analysis Group
• Resource group -- systems modeling, simulation, analysis
• Consulting services from generation to end-use
• Resource support for R&D collaborative efforts
–
–
–
–
–
Transmission planning
Operations
Distribution planning and operations
Substation design
Power quality
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
2
The Smart Grid
• SG is different things to different people
– Communications and control
• Typically not represented in DSA (at present)
– Distributed Resources
• Generation, Storage, Demand Response
– Test Feeders WG has done large induction
machines
– Monitoring
– Protection
– Energy Efficiency
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
3
Smart Grid Features
• Distributed Resources
– Generation
– Renewable Generation
• Variable sources
– Energy Storage
– Demand Response
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
4
Smart Grid Features, cont’d
• Communications and Control
– AMI deployed throughout the system
– High-speed communications to Metering and Controls
– State Estimation
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
5
Impact of SG on Distribution System Analysis?
• What DSA framework is needed to support all features of
the SG?
• Will there be a need for DSA if everything is monitored
thoroughly?
• What could we do if we know more about the system?
• How will merging of planning, monitoring and DSE
change DSA tools?
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
6
Role of Distribution System Analysis
• Distribution state estimation
• Emergency reconfiguration
– Account for missing data, failed comm
• EPRI vision
– Planning and DMS will converge into one set of tools
(Real time and planning will merge)
• Continued need for DSA tools
– Different form and more capabilities
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
7
Advanced Simulation Platform -- OpenDSS
• Open source of EPRI’s Distribution System
Simulator (DSS)
– developed in 1997
– open sourced in 2008 to collaborate
with other research projects
• OpenDSS designed to capture
– Time-specific benefits and
– Location-specific benefits
• Needed for analysis of
– DG/renewables
– energy efficiency
– PHEV/EV
– non-typical loadshapes
• Differentiating features
– full multiphase model
– numerous solution modes
– “dynamic” power flow
– system controls
– flexible load models
Download for free from
http://sourceforge.net/projects/electricdss
OPENSG-SIMSWG
Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
8
Computing Annual Losses
Peak load losses are not necessarily indicative of annual losses
Year 5 Losses: total 2413 MWh
70
25000
60
20000
Load, MW
50
15000
40
kWh
10000
30
5000
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
9
Oct
Apr
Jan
21
0
Jul
0
17
Hour
10
13
9
5
1
20
Month
Overall Model Concept
Inf . Bus
(Voltage, Angle)
Power Deliv ery
Sy stem
Comm
Msg Queue 1
Power Conv ersion
Element
("Black Box")
Control
Center
Comm
Msg Queue 2
Control
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
10
Supporting Renewables
Solar PV Simulation 1-hr Intervals
What is the Capacity Gain?
5
5
Without PV
With PV
Difference
4
Peak is not reduced
3
3
2
2
1
1
0
0
-1
-1
OPENSG-SIMSWG Feb 2011
2 Weeks
© 2011 Electric Power Research Institute, Inc. All rights reserved.
12
Difference, MW
MW
4
Can DMS Enable Increased Capacity?
5
Shorter Duration
Of Peak
Without PV
With PV
Difference
4
3
3
2
2
1
1
0
0
-1
-1
OPENSG-SIMSWG Feb 2011
2 Weeks
© 2011 Electric Power Research Institute, Inc. All rights reserved.
13
Difference, MW
MW
4
5
Cloud Transients: 1-sec Interval
1-Sec Solar PV Output Shape with Cloud Transients
1
Per Unit of Maximum
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
500
1000
1500
2000
2500
3000
Time,s
Impact on Feeder Voltage
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
14
Solar Ramping
Basic Solar Ramp Function
Voltage Pushed over limit on recovery
Regulators compensate for drop
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
15
Regulator Response for
Series of Cloud Transients
Regulator Operations
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
16
“Headroom” for PV
Voltage Profile for 40% Load
Use DMS to Regulate Lower to
Allow More “Headroom” for DG
Voltage Profile for 100% Load
More efficient, too??
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
17
Steady-State Voltage
Y
Device Locations / Voltage
• Maximum change in voltage
PV
• PV at increased penetration until limit
exceeded
• Use of volt/var control accommodates
added PV before violations occur
Substation
189000.00
188000.00
187000.00
Primary
BusPV
Voltages
Base Case
20%
10%
15%
20%
with
PV -VVC
Voltage Change
1.075
186000.00
0.02
V(1)
V(2)
deltaV(1)
deltaV(1)
V(3)
deltaV(2)
deltaV(2)
deltaV(3)
deltaV(3)
1.05
per-unit
per-unit voltage
voltage
0.015
185000.00
Baseline – No PV
10% PV
1.025
0.01
1
Analysis results from other
feeders indicate 25%-100%
more PV can be
accommodated using VVC
0.005
0.975
0.950
00
0.5
0.5
11
1.5 1.5
2
2
2.5
2.5
3
3
3.5
3.5 4
4
4.5
4.5
5
distance from substation (mi)
distance
from substation (mi)
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
18
15%
638000 PV
640000
X
20% PV
20% PV and VVC
642000
DV
Primary Voltage Response with Volt/Var
Control
12 kV Voltage
1.05
20% PV
1.025
1
V (pu)
20% PV w/ volt-var control
0.975
0.95
Baseline – No PV
0.925
0.9
0
4
8
12
Hour
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
19
16
20
Storage
Generic Storage Element Model
(OpenDSS Model)
Idle | Discharge | Charge
% Eff. Charge/Discharge
kW, kvar
Other Key
Properties
Idling Losses
% Reserve
kWhRated
kWhStored
%Stored
kWRated
kWh
STORED
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
21
etc.
Controlling Storage from DMS
Time + Discharge rate
Peak Shaving
Load Following
Loadshape
Discharge Mode
Charge Mode
kW Target
Discharge Time
Total Fleet kW Capacity
Total Fleet kWh
et. al.
Substation controller/DMS
Comm Link
V, I
Substation
Storage “Fleet”
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
22
Simple Substation Peak Shaving
Load Shapes With and Without Storage
Mode=Peak Shave, Target=8000 kW, Storage=75 kWh
Charge=2:00 @ 30%
10000
80
9000
70
8000
60
7000
50
kW
6000
5000
40
4000
30
3000
20
2000
10
1000
0
0
50
100
150
200
Hours
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
23
250
0
300
Base kW
Net kW
kWh Stored
Attempting Peak Shave Every Day
Load Shapes With and Without Storage
Mode=Load Follow, Time=14:00, Storage=25 kWh
Charge=2:00 @ 30%
About
Right
30
10000
9000
25
8000
7000
20
kW
6000
5000
15
4000
10
3000
2000
5
Too Early
1000
0
0
50
100
150
200
Hours
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
24
250
0
300
Base kW
Net kW
kWh Stored
Accounting for Storage Losses
Load Shapes With and Without Storage
Mode=Time + fixed rate, Time=14:00 @ 25% Storage=25 kWh
Charge=2:00 @ 30%
10000
30
9000
25
8000
7000
20
kW
6000
5000
15
4000
10
3000
2000
5
Charging
1000
DIscharging
0
200
210
220
230
240
Hours
Charging energy > Discharging energy (compare areas)
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
25
0
250
Base kW
Net kW
kWh Stored
Key Distribution Modeling Capabilities
for Smart Grid
• Distributed generation
modeling
• Time series simulations
• Efficiency studies
• Meshed networks
• Large systems
• Parallel computing
• Distribution state
estimation
• Protective relay simulation
• AMI Load data
• Modeling controllers
• Modeling comm
• Work flow integration
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
26
Key Challenges
• Merging Planning and Real-Time Analysis
• Very Large System Models
• Systems Communications Simulations
• Large Volume of AMI Data
• AMI-based Decision Making
• Time Series Simulations
• Distribution State Estimation
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
27
Key Challenges, Cont’d
• Detailed LV Modeling
• Including multiple feeders, transmission
• DG Integration and Protection
• Generator and Inverter Models
• Meshed (Looped) Network Systems
• Regulatory Time Pressures
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
28
Reference
• R.C. Dugan, R. F. Arritt, T. E. McDermott, S. M. Brahma,
K. P. Schneider, “Distribution System Analysis To Support
the Smart Grid”, presented at 2010 IEEE PES General
Meeting, Minneapolis, MN
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
29
Together…Shaping the Future of Electricity
OPENSG-SIMSWG Feb 2011
© 2011 Electric Power Research Institute, Inc. All rights reserved.
30