Statewide Impacts of Climate Change on Hydroelectric Generation and Revenues in California Kaveh Madani* Josue Medellin-Azuara Christina Connell Jay Lund *
[email protected] Dept. of Civil and Environmental Engineering University of California, Davis September 2008
Outline • • • • • • • •
CALVIN updates Hydropower in California Effects on Low Elevation System (CALVIN) Effects on High Elevation System (EBHOM) Results Limitations! Next Step? Conclusions
Water Management Adaptation to Climate Warming using CALVIN
The CALVIN model • An hydro-economic model for water resources management in California • Applications – Conjunctive use and water markets – Climate change – Alternatives for the Sacramento-San Joaquin Delta.
The CALVIN model • GIS-based land use for the agricultural demand Model (DWR surveys) • Population projections for year 2050
Climate Change Scenarios • Historical Hydrology (1921-1992) • Warm-Dry Climate (GFDLCM1 A2) • An estimated warm-only hydrology – Historic mean annual flow – Warm-dry patterns of early snowmelt and dryer summers
• Compared use of 6 versus 18 index basins to obtain perturbed rim flows
Preliminary Results 1000
Warm-only
900
800
Warm Dry
700 Stream flow (TAF)
Sacramento River 600
500
Historical
400
300 San Joaquin River 200
100
0 1
2
3
4
5
6
7
8
9
10
11
12
Month
Sacramento River - historical San Joaquin River - historical
Sacramento River - warm dry San Joaquin River - warm dry
Sacramento River - warm only San Joaquin River - warm only
Rimflows in the Sacramento and San Joaquin Rivers
Preliminary Results • Shortages of 15% of the target demands for agriculture are expected under the warm-dry scenario • Historical and warm only scenario only vary slightly in terms of water deliveries and shortages
Conclusions • Agriculture remains vulnerable to shortages in the climate scenarios • Water scarcity in California is more sensible to changes in precipitation rather than temperature • Similar reductions in dry rim flows are expected using 18 versus just 6 index basins
Hydropower Systems Imported hydropower Pacific Northwest & Lower Colorado River
High elevation hydropower
Power Demands Surface reservoir hydropower
Thermal
Aquifer water storage
Pumped storage hydropower
Hydropower and California 1,000 GWH/yr, 2004
* Estimated
Sources: CEC; McCann 2005
Climate Effects on Hydropower 1. Energy demand 2. Timing of water availability 3. Quantity of water available 4. Availability of hydropower to import 5. Thermal generation efficiency 6. Sensitivity of environment to hydro operations
Water Supply Dam Hydropower Seasonal Generation Changes
Major water supply reservoirs in CALVIN system optimization model
Average Water Supply Reservoir Hydropower Benefits ($M/year)
High-Elevation System
(CA Energy Commission, 2003)
• 156 Highelevation power plants • Snowpack dependant • High-head, little headstorage effect • Limited storage or flow data!!
High-Elevation Runoff (Snowpack Effect) Historic Mean Monthly Flow 30 Percentage (%)
25 20
1000-2000 (ft)
15
2000-3000 (ft)
10
>3000 (ft)
5 0 Ju n Ju l A ug S ep
M ar A pr M ay
Ja n Fe b
O ct N ov D ec
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Month l
the calculations i
average _ Runoff (i ) runPercent (i ) = average _ Annual _ Runoff
High-Elevation Generation (Snowpack Effect) Monthly Generation
Percentage (%)
13 11 1000-2000 (ft) 2000-3000 (ft)
9
>3000 (ft) 7
O
ct
. N ov . D ec . Ja n. Fe b. M ar . Ap r. M ay Ju ne Ju ly Au g Se . pt .
5
Month
average _ generation(i ) genPercent (i ) = average _ Annual _ generation
White Rock C O M P
Historic monthly electricity generation and optimized monthly electricity generation (by EBHOM) in an average year
SMUD System
Comparison of EBHOM and traditional optimization applied to SMUD system
High-Elevation Model Results 137 of 156 hydropower plants 1984 – 1998 period
Generation (1000 GWH/Month)
Monthly Generation 4 3.5 3 2.5 2 1.5 1 0.5 Recorded
0 Oct
Nov
Dec
Base
Jan
Feb
Dry
Mar
Wet
Apr
Month
May
Warming Only
Jun
Jul
Aug
Sep
Model Results Scenario
Generation (1000 GWH/yr)
Base
Dry
Wet
WarmingOnly
22.3
18.0
23.4
22.0
- 19.3
+ 4.8
- 1.4
224
1,661
735
- 46.0
+ 283.9
+ 58.8
1,271
1,483
1,435
- 12.3
+ 2.3
- 0.9
Generation Change with Respect to the Base Case (%) Spill (MWH/yr)
433
Spill Change with Respect to the Base Case (%) Revenue (Million $/yr)
1,449
Revenue Change with Respect to the Base Case (%)
average of results over 1984-1998 period
Average total end-of-month energy storage (1984-1998) Storage (1000 GWh/Month)
8 Base
7
Dry
6
Wet
5
Warming Only
4 3 2 1 0 Oct
Nov
Dec
Jan
Feb
Mar
Apr
Month
May
Jun
Jul
Aug
Sep
Average monthly energy spill (1984-1998) 1.0
Base Scen
Dry Scen
Wet Scen
Warming Only
Energy Spill (1000GWH/Month)
0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Oct
Nov
Dec
Jan
Feb
Mar
Apr
Month
May
Jun
Jul
Aug
Sep
Benefit of Storage Capacity Expansion 50
Base
Dry
Wet
Warming-Only
$/Year/MWh
40 30 20 10 0 0
20
40
60
80
Number of Plants
100
120
Benefit of Generation Capacity Expansion
$/Year/MWh
50
Base
Dry
Wet
Warming-Only
40 30 20 10 0 0
20
40
60
80
Number of Plants
100
120
Limitations of EBHOM • • • • • • • •
NSM Limitations Few stream gauges Coarse elevation ranges Hydrologic variability Perturbation ratios Energy demand/price changes Deterministic (perfect foresight) No Environmental Constraints
Overall Conclusions • Sierra loses snowpack, the natural reservoir. • Storage works. Generation changes more with total runoff than seasonal runoff shift. • Problems for smaller high-elevation reservoirs - more spills even without change in total runoff • Drier climate causes more problems than wetter climate causes benefits. • Revenue reduction may be economically insufficient to justify expanding storage or generation capacity.
Next Steps? • Climate change effects on energy demand/ price • More detailed high-elevation studies
Acknowledgements • Supported by CA Energy Commission (PIER) and the Resources Legacy Fund Foundation • Maury Roos, CA DWR • Omid Rouhani, UC Davis • Marcelo Olivares, UC Davis • Sebastian Vicuna, UC Berkeley
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