hydropower variability in the western u.s.: consequences and opportunities

Hydropower Variability in the Western U.S.: Consequences and Opportunities

Nathalie Voisin, Alan Hamlet, Phil Graham, Dennis P. Lettenmaier

UW Water Resources GroupCivil and Environmental Engineering

University of WashingtonApril 7, 2005

Background

Climate is predictable: Increasingly predictable up to 6 months (or more) in advance West coast U.S. climate more predictable than other regions, due to

strong ocean influence California and the Pacific Northwest are out of phase for some climate

events such as El Nino Southern Oscillation (ENSO)

Energy Demand is predictable: California has regular peaks in winter and summer while energy

consumption in the Pacific Northwest (PNW) has a strong winter peak

Question: How can climate predictions be used to manage West Coast energy transfers more efficiently?

In previous episodes …

Episodes I to III: Litterature review i) Precipitation, temperature and streamflow predictability based on climate (ENSO and PDO):extensive list

ii) Hydropower and Climate variability:Hamlet and Lettenmaier 1999, Cayan et al 2003

iii) Retrospective Analysis 1950-2000:Maurer et al 2002

iv) California summer temperature predictability :Alfaro et al 2005

Outline

Episode IV, A New Hopemeteorological data

hydrologic modelreservoir modelsenergy demand model

Episode V, VIC strikes backStreamflow and climate

Hydropower and climateElectricity demand and climate

Episode VI, return to modelingconstraintsbenefits and climatepotential for more benefit

A New Hope

Meteorological data Hydrologic Model Reservoir Models Energy Demand Model

The procedure in brief

Reservoir ModelColSim / CVMod

Monthly Natural Streamflow

Hydropower

Hydrologic ModelVIC

+ Routing Model + Bias Correction

Pre-processing(gridding, climatic trend, etc)

Temperature, Precipitation and wind observations

Meteorological Data

Station Data sources : National Climatic Data Center (NCDC)

Extended time series from 1916 to 2003

Forcing data sets gridded to the 1/8 degree

Adjustment of forcing data sets for orographic effects based on PRISM (Parameter-elevation Regressions on Independent Slopes Model ) approach (Daly and colleagues at Oregon State University)

Adjustment to reflect long-term trends that are present in the carefully quality controlled Hydroclimatic Network (HCN) and a similar network for the Canadian portion of the Pacific Northwest (PNW) region (Hamlet and Lettenmaier 2004)

Hydrologic Model: VIC (1/2)

1/ Water Balance 2/ Runoff Routing

Hydrological Model: VIC (2/3)

Simulated Flow = RedObserved = Black

Hydrological Model: VIC (2/3)

Simulated Flow = RedObserved = Black

Reservoir Models: CVMod and ColSim

Represent physical properties of the reservoir systems and their operation Assume fixed level of development Monthly time step

Monthly Natural Streamflow

Water Demand Flood Control, Energy Demand

CALIFORNIACVMod

(Van Rheenen et al 2004)

PACIFIC NORTHWESTColSim

(Hamlet and Lettenmaier 1999)

Hydropower

Monthly Natural Streamflow

Hydropower

Electricity Demand Model

Based on a regression of observed daily average or peak hour load with observed daily maximum temperature 1993-2000, and day type ( week end, national holyday, week day)

Derive 1916-2002 daily and peak hour electricity demand for California and the PNW

More skill in summer time in CA and in wintertime in the PNW

PNW CA

In Brief

1915-2002 meteorological data set in CA and PNW 1916-2002 naturalized bias corrected streamflow in CA and PNW 1917-2002 hydropower time series in CA and PNW 1917-2002 electricity demand in CA and PNW 1917-2002 ENSO and PDO climate signals

Episode V, VIC strikes back

Observed Covariability

Goal: confirm litterature review results with our time series derive new relationships

Streamflow and Climate Hydropower and Climate Energy demand and Climate Hydropower and Energy Demand

Streamflow covariability

Seasonal: North CA and the PNW are out of phase

Interannual based on ENSO and PDO: out of phase

Streamflow Covariability

CA NORTH (cfs)

Mean annual 22,353

std 9,880

CV 0.4

CA SOUTH (cfs)

Mean annual 7,709

std 4,128

CV 0.5

North CA: peak in winterSouth CA: peak in spring

ENSO: 17% annual flow differencePDO: 2%

Natural Streamflows in South California, San Joaquin River

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

Flo

w (

cfs

)

Cold ENSO

Warm ENSO

Cold PDO

Warm PDO

Natural Streamflows in North California, Sacramento River

0

10,000

20,000

30,000

40,000

50,000

60,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

Flo

w (

cfs

)

Cold ENSOWarm ENSO

Cold PDOWarm PDO

Streamflow Covariability

DALLES (cfs)

Mean annual 181,063

std 33,066

CV 0.2

PNW: peak in early summer

ENSO/PDO: 12-16% annual flow difference

Natural Streamflows at the Dalles

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

Flo

w (

cfs

)

Cold ENSO

Warm ENSO

Cold PDO

Warm PDO

Columbia River Discharge at The Dalles, Or.

MAY-JUNE-JULY ANNUAL

Avg flow in cfs % of Average Avg flow in cfs % of Average

WARM ENSO 354,006 89% 172,501 92%

PDO 347,049 87% 172,063 91%

ENSO/PDO 330,980 83% 165,425 88%

COLD ENSO 416,866 105% 197,647 105%

PDO 438,924 110% 204,213 108%

ENSO/PDO 449,240 113% 209,527 111%

AVG 397,628 100% 188,271 100%

  CALIFORNIA    

NORTH, MAMJJ SOUTH, MJJAS

ANNUAL FLOW

NORTH SOUTH

Avg Flow

% of Avg

Avg Flow

% of Avg

Avg Flow

% of Avg

Avg Flow

% of Avg

WARM ENSO 13,272 110% 3,224 98% 8,481 107% 2,430 102%

  PDO 13,221 110% 3,896 119% 8,495 107% 2,628 111%

  ENSO/PDO 13,211 109% 3,524 108% 8,505 107% 2,579 109%

COLD ENSO 10,938 91% 3,166 97% 7,253 91% 2,277 96%

  PDO 11,876 98% 2,830 86% 7,734 98% 2,154 91%

  ENSO/PDO 10,673 88% 2,687 82% 7,175 90% 2,013 85%

AVG   12,074 100% 3,275 100% 7,933 100% 2,374 100%

Hydropower Covariability

PNW (avg MW)

mean 13,644

std 3,082

CV 0.2

CA (avg MW)

mean 976

std 399

CV 0.4

PNW: peak in JCA: peak in M

Hydropower Production in the PNW

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

16,000,000

18,000,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

MW

h

cold ENSO

warm ENSO

cold PDO

warm PDO

Hydropower Production in CA

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

MW

h

cold ENSO

warm ENSO

cold PDO

warm PDO

Hydropower Covariability

53% correlation between PNW and CA hydropower

PNW April-May-June-July 

Hydro. pdtion aMW

% of the avg

Demand on avg aMW

Hydro/ Demand

WARM ENSO 17,574 93% 17,458 101%

PDO 17,473 92% 17,466 100%

ENSO/PDO 16,737 88% 17,441 96%

COLD ENSO 19,708 104% 17,471 113%

PDO 20,586 108% 17,460 118%

  ENSO/PDO 20,546 108% 17,466 118%

AVG   18,983 100% 17,470 109%

Energy Demand Covariability

I/ Seasonally:

Demands are out of phase in CA and in the PNW!!

II/ Interannually: ~1% variation of peak or daily electricity demand, underestimation of the variability due to monthly averaging

Daily Energy Demand (93-00)

0100,000200,000300,000400,000500,000600,000700,000800,000900,000

1,000,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

MW

-hr

day PNW

day CA

Peak Hour Energy Demand (93-00)

05,000

10,00015,00020,00025,00030,00035,00040,00045,00050,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

MW

-hr

peak PNW

peak CA

Climate based predictabilities

Predictable variables Streamflows Hydropower Electricity demand ENSO and PDO indices

Seasonal timing Energy demand is out of phase in CA and in the PNW PNW energy production and energy demand are out of phase PNW hydropower and CA peak energy demand are in phase

Interannual variability: Streamflows tend to be out of phase in CA and PNW Hydropower productions are correlated at 53% PNW hydropower and CA peak energy demand are in phase

Episode VI, Return To Modeling

Development of the transfer model Economic benefit New management timeline

The Pacific NW-SW Intertie

Slightly less than 8000 MW capacity Reliable transmission Southward transfer during peak hour Northward transfer overnight, if needed

Notes: The energy transfer follows the energy demand Transfers are decided on an hourly basis during

the day Currently climate information is not used in

planning West Coast energy transfers

Transfer Model

Based on conservative EXCESS PNW HYDROPOWER estimate( Production – daily demand)

Assumption: intertie used for California Peak Hour ~ 10 hour/day

Additional Constraints Capacity:

Excess Hydro. <= Intertie Transfer capacity (7500 MW)

Location:Excess Hydro. <= Hydro. Production at The Dalles and John Day

Price:Sell Price <= CA production price with conventionnal resources

Economic Benefit

ELECTRICITY RATES April May June July August

CA Natural Gas electricity $/MWh 59.52 59.52 59.52 59.52 59.52

PNW hydropower sale (HHL + load variance)

$/MWh 19.15 19.08 23.63 30.71 44.94

(PNW transmission) $/MWh 3.39 3.39 3.39 3.39 3.39

(PNW high load hour sale (HHL), PNW benefit)

$/MWh 18.05 17.98 22.53 29.61 43.84

Transfer Model

Constraint Excess Hydropower

PNW April-May-June-July 

% of the avg

Hydro/ Demand

Avg available extra hydro over 10 hours aMW

% of the avg

WARM ENSO 93% 101% 3336 88%

PDO 92% 100% 3333 88%

ENSO/PDO 88% 96% 3017 80%

COLD ENSO 104% 113% 4321 114%

PDO 108% 118% 4900 129%

  ENSO/PDO 108% 118% 4697 124%

AVG   100% 109% 3788 100%

Economic Benefit

Extra Benefits and Costs over April-May-June-July in millions $

CA BENEFIT PNW BENEFIT

WARM ENSO 132 77

  PDO 135 78

  ENSO/PDO 120 69

COLD ENSO 172 102

  PDO 186 111

  ENSO/PDO 189 112

AVG   159 95

Predictability Tools

Predictability Tools

A new Timeline

Based on

A Forecast Timeline

Jun Aug Jun

On ~June 1 we have:

•CurrentReservoirContents (PNW and CA)

•Current SummerStreamflow Forecast (PNW and CA)

•ENSO forecast•PDO forecast

CA Demand

Surplus PNWEnergy forComing Spring

PNW Winter Demand

Jan

Forecasts:

Conclusions (1)

1917-2002 retrospective Analysis CA and PNW hydropower covary 53% of the time

PNW hydropower is predictable using ENSO and PDO indices

Excess PNW hydropower is predictable

Electricity demands are predictable

Electricity tranfers are of the same order of magnitude as the CA hydropower (for a total of up to 20% of CA peak demand)

Predictable economic benefit, averaging $159 and $95 million for CA and the PNW

Conclusions (2)

Perspective for Forecasting Prediction of next winter ENSO available California summer electricity demand is predictable using MAM PDO

indices (Alfaro et al 2005 and our electricity demand model) Excess hydropower can be simulated

Thank You!

Meteorological Data : NCDC

Preprocessing Regridding

Lapse Temperatures

Correction to RemoveTemporal

Inhomogeneities

HCN/HCCD

Monthly Data

Topographic Correction forPrecipitation

Coop Daily Data PRISM Monthly

PrecipitationMaps

Extended time series from 1916 to 2003

Temperature &

Precipitation

Overall Covariability

TRENDS WARM ENSO PDO ENSO/

PDO

COLD ENSO PDO ENSO/

PDO

Temp CA JA - - - + + +PNW JFMA + + + - - -

Peak Hour Energy Demand

CA JA + + + - - -PNW JFMA - - - + + +

Daily Energy Demand

CA JA + + + - - -PNW JFMA - - - + + +

Hydro-power

CA JA + + + (-) (-) (-)PNW JJ - - - + + +

The scientific question

CLIMATEENSO / PDO

Streams

Electricity DemandHydropower production

IntertieMutual Benefit