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