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Estimation of the Impact of Drought on Electricity Generation in the Western US Chris Harto - Argonne National Lab Eugene Yan - Argonne National Lab Vince.

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Presentation on theme: "Estimation of the Impact of Drought on Electricity Generation in the Western US Chris Harto - Argonne National Lab Eugene Yan - Argonne National Lab Vince."— Presentation transcript:

1 Estimation of the Impact of Drought on Electricity Generation in the Western US Chris Harto - Argonne National Lab Eugene Yan - Argonne National Lab Vince Tidwell – Sandia National Lab

2 Design Drought Scenarios

3 Drought Scenarios Summary Drought scenarios developed based on historical data and through a consensus building process. 2 Primary Scenarios (national lab team) – 10 th percentile drought year assumed in each individual basin – Assume 1977 drought conditions WECC low flow hydro scenario (WECC) – Assume 2001 drought conditions Drought Scenarios defined by HUC-2 Basins

4 HUC-2 Basins in WECC and ERCOT

5 Drought Scenario Flows ScenariosDescription HUC-2 Basin MissouriTexasRioGrandeUpper COLower COGreatBasinPacificCalifornia Normal Average historical flow ( ) (acf) 64,011,81020,291,1965,289,68014,348,3844,782,45513,457,301192,154,820101,293,852 Recent Normal* Average historical flow ( ) (acf) 51,309,98321,254,3742,763,4569,015,4342,258,77911,149,388178,925,89574,284,946 10th Percentile Drought Year Flow (acf)34,556,4336,605,4011,921,7328,271,2101,735,7627,265,298132,082,38548,509,010 West-wide Drought1977 flow(acf)41,532,11122,832,5431,364,7088,676,4281,412,1456,729,334127,188,28727,555,014 WECC Low Flow2001 flow (acf)62,459,14329,514,3072,785,1188,700,2642,324,1568,099,021121,128,92744,006,778 Worst Drought** Year Flow (acf)21,785,5773,207,2471,309,0062,550,4881,059,1094,466,372119,089,72027,555,014 **Worst Drought year shown for comparison *Recent Normal flows used for comparison and analysis of drought impact due to the fact that operations and expectations are most likely to be calibrated towards recent experience Note: Runoff was estimated using gauge data from the USGS stream gauge network. Runoff per area for each gauge based on its drainage area are combined to derive the runoff per area for the entire HUC-2 basin using a weighted factor estimated from the drainage area percentage of the HUC-2 basin for each gauge. The total runoff of HUC-2 basin is estimated by runoff per area time the area of the basin.

6 Comparison of Normalized Runoff in Selected Drought Years Average Runoff in

7 Hydro Generation Estimation

8 Approach Hypothesis: Hydro Generation Proportional to Basin Flow Validation: – Correlate annual flow volume to annual hydro generation within each basin for years (years I could get good hydro generation data) – Use USGS stream guage data – Use Bureau of Reclamation power generation data Assumes Bureau of Reclamation generation proportional to all hydro generation – Compare ratios of annual values (both generation and flow) to 9-year average of values – Challenge Matching Bureau of Rec regions with HUC-2 basins

9 HUC-2 Reclamation Bureau of Rec regionBest HUC-2 Equivalent Pacific NW Mid-PacificCalifornia Lower CO Upper CO Great PlainsMissouri Basins Note: Rio Grande, Great Basin and TX Gulf not included due to limited Rec hydro generation in basin

10 Ratios of Hydro Generation and Flow Year R2R2 Pacific NW - G Pacific NW - F Mid Pacific - G Mid-Pacific - F Lower CO - G Lower CO - F Upper CO - G Upper CO - F Great Plains - G Great Plains - F G = Ratio of annual generation to 9 year average generation F = Ratio of annual flow to 9 year average flow

11 Basins with good correlation between flow and hydro generation

12 Factors potentially leading to poor correlation? Required flows for other needs (fish, water supply) Drawdown or fill up of reservoir storage Flood control Electricity demand Alternative to flow correlation? Overall variability in flow is greater than variability in generation. Likely due to buffering effect of reservoir storage. Assuming correlation would represent a “worst case” for these basins. Basins with poor correlation between flow and hydro generation

13 Area of interest While correlation between basin flow and hydro generation is far from perfect, it represents a reasonable minimum or “worst case” estimate For flow ratio below 0.9, hydro generation always equal or greater

14 Hydro Generation Factors Basin10th percentileWest-wide (1977)WECC Low Flow (2001) Texas RioGrande Upper CO Lower CO GreatBasin Pacific California Missouri Key Assumptions – Hydro generation proportional to flow – Drought flows compared to recent “normal” flows Scenarios – 10 th Percentile = 10 th percentile drought in each basin – West-wide = Single year (1977) drought – WECC Low Flow = Single year (2001) drought

15 Analysis of Impact on Thermoelectric Generation

16 Determining Generation Risk Using data on individual generating units compiled by NREL and UT, total electricity generation for each basin was categorized into one of three categories – Hydro – thus at risk to reduced flow – Low Risk – generation that either required no cooling water (solar, wind, combustion turbine) or utilized non surface water (wells, ocean, treated wastewater) – At Risk Thermoelectric – Thermoelectric generation that relies on surface water or unspecified water sources.

17 Basin Generation Breakdown Nameplate (MW)Generation (MWh) Regionhydroat risk thermolow riskhydroat risk thermolow risk Missouri TX Gulf Rio Grande Upper CO Lower CO Great Basin Pacific NW California

18 Thermoelectric “Worst Case Scenarios” Fraction of thermoelectric generation “at risk” has been identified Determining how much of the “at risk” generation will actually have to be derated is more challenging Potential reasons for derating or forced outages – Junior water rights – Water levels dropping below intake structures – Discharge water temperatures exceeding permitted limits Operators generally have plans and strategies for mitigating these risks – Quote from AZ utility representative - “We have never experienced a water related outage” – Documents obtained from utilities indicate they have been thinking about these issues and have a range of mitigation options Alternative water supplies Demand Response Power Purchases/Exchange Agreements

19 Worst Case 1 Assume loss of “at risk” thermoelectric generation is proportional to the loss of flow from normal levels in drought scenario Poor assumptions – Assumes no excess flow in basin – Assumes no prioritization of water usage – Assumes no mitigation activities MWh Basis Worst Case 1 = at risk thermo * (1-(drought flow/recent normal flow))

20 Worst Case 2 Assume loss of “at risk” thermoelectric generation is proportional to the shortfall of flow relative to total basin water demand in 2010 Poor assumptions – Assumes all water demand supplied by surface flows (not good assumption for dryer basins) – Assumes no prioritization of water useage – Assumes no mitigation activities Worst Case 2 = at risk thermo * (1-(drought flow/2010 water demand))

21 Worst Case 3 Assumes minimum value from Worst Case 1 and Worst Case 2. Taking minimum of the two values eliminates the following errors – Cases where normal flow in the basin does not meet 2010 demand (indicating water supplied from other sources) – Cases where reductions in flows are still sufficient to meet total water demand. Still assumes: – No mitigation – No prioritization of water consumption – Potential for localized water shortages are ignored This is the best guess at the worst case loss of thermoelectric generation Worst Case 3 = min(Worst Case 1, Worst Case 2)

22 Drought Scenario Summaries

23 10 th Percentile Drought Drought flow vs. recent normal flow ( ) Drought flow vs water demand Thermoelectric water demand (based on NREL and UT estimates)vs. drought flow Thermoelectric water demand (Sandia 2010 consumption data)vs. drought flow Worst case loss of generation from hydro Worst case loss of total generation from thermoelectric Total Worst Case Loss of Generation Missouri TX Gulf Rio Grande Upper CO Lower CO Great Basin Pacific NW California

24 West-Wide Drought (1977) Drought flow vs. recent normal flow ( ) Drought flow vs water demand Thermoelectric surface water demand (based on NREL and UT estimates)vs. drought flow Thermoelectric water demand (Sandia 2010 consumption data)vs. drought flow Worst case loss of generation from hydro Worst case loss of total generation from thermoelectric Total Worst Case Loss of Generation Missouri TX Gulf Rio Grande Upper CO Lower CO Great Basin Pacific NW California

25 WECC Low Flow Hydro (2001) Drought flow vs. recent normal flow ( ) Drought flow vs water demand Thermoelectric water demand (based on NREL and UT estimates)vs. drought flow Thermoelectric water demand (Sandia 2010 consumption data)vs. drought flow Worst case loss of generation from hydro Worst case loss of total generation from thermoelectric Total Worst Case Loss of Generation Missouri TX Gulf Rio Grande Upper CO Lower CO Great Basin Pacific NW California

26 Final thoughts Estimates of lost electricity generation should be viewed as the worst case for the given scenario A number of basins appear to have relatively low risk from lost generation in all scenarios Greatest risk appears to be from hydro generation in the Pacific NW Better understanding of the true risk to thermoelectric generation is still needed.

27 Supplementary Slides


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