Risk-limiting Dispatch of Power Systems with Renewable Generation
Future Trends for Power SystemsA Short Course to Honor Prof. David Hill
Sydney, Oct 12, 2009
Felix WuPhilip Wong Wilson Wong Professor in Electrical EngineeringUniversity of Hong Kong
Outline
• Operation of conventional power systems• Worst-case dispatch
• Future grid• Drivers• Renewables and demand response increase uncertainty• Smart grid increases information and control
• Risk-limiting Dispatch• Risk measures: RaR, CRaR• Some preliminary results
J. Bialek, P. Varaiya, F. F. Wu, J. Zhong, “Smart Operation of Smart Grid,”Proceedings of the IEEE, 2010.
Real-time Control of Power Systems
Generation Substation Distribution ConsumersTransmission
Encoder / Decoder
StateMonitor
ControlDriver
MeasuringDevice
Com
mun
icat
ions
Dev
ice
Power Station
SCADA Remote Terminal
S y s te mS e r v e r
A l te r n a t eS y s te mS e r v e r
C o m m u n ic a t io n sG a te w a y
A l te r n a t eC o m m u n ic a t io n s
G a te w a y
F a i l o v e rL o g ic
D is p a tc h e r sW ith
W o r k s t a t i o n s
D u a l R e d u n d a n tS y s te m N e tw o r k
Brid
ge to
Cor
pora
te L
AN
A d v a n c e dA p p l ic a t io n s
S e r v e r
EMS Control Center
Mostly no real-time control andrely instead on manual control
Power System Analysis
1 ms 1 cycle 1 sec 1 min 10 min 1 hr 1 day 1 mo 1 yr
Protection
Mid/long-term dynamicsTransient stability
Frequency dynamics
Small disturbance stability
Load flow
Generation adequacy
Reliability Economics
Off-line
On-line
Operation of Conventional Electric Grid
Limited visibility beyond substation
Limited visibility in short period (within minute/ second range)
Worst-case Dispatch
Constraints» Power balance» Operating limits» (N-1) Contingencies
Objective» Max social welfare
Uncertainty» Load demand» Forced outage of equipment
AdjustmentEmergency» Load shedding
Day-ahead Market
Scheduling
Balancing Market
Adjustment EmergencyOperatingtime
An Inconvenient Truth
Change Has Come
Global climate change Greenhouse gases CO2 from fossil fuel energy sources
CO2 Concentration
290300310320330340350360370380
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Europe Renewable Commitment
EU Renewable target: 20% by 2020
Spain: 20% now 30% by 2010
UK: 10% now Denmark: 21% now30% by 2020
Germany: 14% now27% by 2020
Renewables Portfolio Standards
State Goal
☼ PA: 18%** by 2020
☼ NJ: 22.5% by 2021
CT: 23% by 2020
WI: requirement varies by utility; 10% by 2015 goal
IA: 105 MW
MN: 25% by 2025(Xcel: 30% by 2020)
TX: 5,880 MW by 2015
☼ AZ: 15% by 2025
CA: 20% by 2010
☼ *NV: 20% by 2015
ME: 30% by 200010% by 2017 - new RE
State RPSSolar hot water eligible
☼ Minimum solar or customer-sited RE requirement* Increased credit for solar or customer-sited RE** Includes separate tier of non-renewable “alternative” energy resources
HI: 20% by 2020
RI: 16% by 2020
☼ CO: 20% by 2020 (IOUs)*10% by 2020 (co-ops & large munis)
☼ DC: 20% by 2020
DSIRE: www.dsireusa.org March 2009
☼ NY: 24% by 2013
MT: 15% by 2015
IL: 25% by 2025
VT: (1) RE meets any increase in retail sales by 2012;
(2) 20% RE & CHP by 2017
☼ MD: 20% by 2022
☼ NH: 23.8% in 2025
OR: 25% by 2025 (large utilities)5% - 10% by 2025 (smaller utilities)
*VA: 12% by 2022
☼ *DE: 20% by 2019
☼ NM: 20% by 2020 (IOUs)10% by 2020 (co-ops)
☼ NC: 12.5% by 2021 (IOUs)10% by 2018 (co-ops & munis)
ND: 10% by 2015
SD: 10% by 2015
*UT: 20% by 2025☼ OH: 25%** by 2025
*MI: 10% + 1,100 MW by 2015
☼ MA: 15% by 2020+ 1% annual increase(Class I Renewables)
☼ MO: 15% by 2021
*WA: 15% by 2020
28 states have an RPS;
5 states have an RE goal
US Renewables
p
P{g
>x}
Renewable Generation Uncertainty
Rated capacity = 1500kWx20Capacity distributionAverage capacity = 14,000kWGenerator reliable capacity
» With prob p, the capacity of the generator will be at least A(p)
Reliable capacity (reliable capacity ~ thermal)
=3,000kW
n = 1n = 20
thermal
( ) max{ { } }A p x P g x p= ≥ ≥
{ }P g x≥
30,000
24,000
18,000
6,000
12,000
Stochastic Resources
Using conventional worst-case dispatch, an extra reserve requirement of a wind generator is 90% of its installed capacity.
Demand response is not considered in reserve calculation.Stochastic resources are not being fairly treated.
Future Grid
Powersystem
components
Monitoring andControl
CommunicationInfrastructure
InformationManagement
Application
Wind
Solar
425
450
475
500
525
550
575
30 60 90 120 150 180 210 240
Time - seconds
Volta
ge -
kV
John Day Malin Summer L Slatt McNary
Grizzly reactor #2
Grizzly reactor #3
Ashe reactor
PMU
PHEV
CHP
Communication network
Data model standardizationDistributed data serviceSearch engine
Optical fiber/ wirelessCommunication network protocols
Embedded intelligent sensorsSensor network technology
Storage
Smart Homes
Wind, solar and other renewablesStorage
Future Grid
SCADADMSMicrogrid
Smart Generation
SmartSubstation
SmartDistribution
SmartHome
DAAMIDER
Demand responseIntelligent appliances
FACTSWAMSLine condition monitoring
Smart Transmission
Encoder / Decoder
StateMonitor
ControlDriver
MeasuringDevice
Com
mun
icat
ions
Dev
ice
Power Station
SCADA Remote Terminal
S y s te mS e r v e r
A l te r n a t eS y s te mS e r v e r
C o m m u n ic a t io n sG a te w a y
A l te r n a t eC o m m u n ic a t io n s
G a te w a y
F a i l o v e rL o g ic
D is p a tc h e r sW ith
W o r k s t a t i o n s
D u a l R e d u n d a n tS y s te m N e tw o r k
Brid
ge to
Cor
pora
te L
AN
A d v a n c e dA p p l ic a t io n s
S e r v e r
EMS Control CenterEMS AMI
Future Grid
More accurate information» Smart meters, sensors
More refined control» Battery storage» Demand response
Tighter feedback » Communication
Low emissioncentral plant
Micro-Grid
SubstationLoad
Virtual plant
Solar power
Wind power
storage
A New Operating Paradigm is Neededin the New Environment!
Operating Risk: Revisit
Worst-case dispatchOperating risk» Not meeting the constraints
Operating constraints» Power balance
» Operating limits
Uncertainty on faults and equipment failure leads to (N-1) criterion
Risk-limiting dispatchWorst-case dispatch results in inefficient utilization of renewable resources and demand responseFuture smart grid will provide more just-in-time informationA new operating paradigm by limiting the risk of not meeting operating constraints in a consistent manner.
( ( ), ) 0g t u =x
( ( ), ) 0h t u ≤x
Risk-limiting Dispatch
Scheduling» Decision : Generation» Max objective such that the risk of not meeting
operating constraints is less than (1-p*) based on available information at the time of scheduling.
Scheduling
max ( ( ), ) (e.g., social welfare)
. . Pr{ ( ( ), ) 0, ( ( ), ) 0 } *t T
f t u
s t g t u h t u pσ
σ
σ σ −= ≤ ≥
x
x x y
t Tσ−
Operatingtime
t
uσ
Risk-limiting Dispatch
Recourse» Decision : Generation, storage, demand response» Max objective such that the risk of not meeting
operating constraints is less than (1-p*) based on available information at the time of recourse.
Scheduling Recourse
max ( ( ), ) (e.g., social welfare)
. . Pr{ ( ( ), ) 0, ( ( ), ) 0 } *t T
f t u
s t g t u h t u pρ
ρ
ρ ρ −= ≤ ≥
x
x x y
t Tσ−
Operatingtime
t
uρ
t Tρ−
Risk-limiting Dispatch
Emergency » Decision : Generation, interruptible load» The operating constraints must be satisfied.
Scheduling Recourse
Pr{ ( ( ), ) 0, ( ( ), ) 0 } 1t Tg t u h t uεε ε −= ≤ =x x y
t Tσ−
Operatingtime
tt Tρ−
Emergency
t Tε−
uε
Optimal Dispatch
The overall optimization problem for system operation:
Suppose that the costs of generation for different periods (scheduling, recourse, emergency) are known, for a simpler model, the optimal dispatch has been derived in terms of nested conditional probabilities.We believe that the result can be generalized.
Scheduling Recourse
t Tσ−
Operatingtime
tt Tρ−
Emergency
t Tε−
max ( ( ), , , )
. . Pr{ ( ( ), ) 0, ( ( ), ) 0 } *
Pr{ ( ( ), ) 0, ( ( ), ) 0 } *
Pr{ ( ( ), ) 0, ( ( ), ) 0 } 1
t T
t T
t T
f t u u u
s t g t u h t u p
g t u h t u p
g t u h t u
σ
ρ
ε
σ ρ ε
σ σ
ρ ρ
ε ε
−
−
−
= ≤ ≥
= ≤ ≥
= ≤ =
x
x x y
x x y
x x y
Summary
Current operation paradigm» Based on worst-case dispatch is unfair to renewable sources and
demand response and will be hard pressed to realize full potentials of smart grid
Future grid» Distributed resources of renewable generation and demand
participation» Enabling technologies of Information and communication
technology, as well as power electronicsRisk-limiting dispatch of renewable resources» Risk-limiting dispatch is based on “just-in-time” risk assessment
Center for Electrical Energy SystemThe University of Hong Konghttp://www.eee.hku.hk/~cees
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