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TEPPC 2011 STUDY PROGRAM – WESTERN GOVERNOR’S ASSOCIATION DROUGHT STUDY

TEPPC 2011 STUDY PROGRAM – WESTERN GOVERNOR’S ASSOCIATION DROUGHT STUDY NREL Proposal to Address Energy Demand Impacts of Drought. Data Work Group Call Tuesday, November 29, 2011. KC Hallett, NREL Jordan Macknick , NREL. Purpose of the Drought Study

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TEPPC 2011 STUDY PROGRAM – WESTERN GOVERNOR’S ASSOCIATION DROUGHT STUDY

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  1. TEPPC 2011 STUDY PROGRAM – WESTERN GOVERNOR’S ASSOCIATION DROUGHT STUDY NREL Proposal to Address Energy Demand Impacts of Drought Data Work Group Call Tuesday, November 29, 2011 KC Hallett, NREL Jordan Macknick, NREL

  2. Purpose of the Drought Study • The purpose of this study is to examine the impacts of higher temperatures and changes to the timing and quantity of precipitation and runoff on electricity generation relative to the 2022 Common Case*. • Key Question to be Addressed by NREL • What impact does a prolonged drought, and the corresponding higher temperatures, have on energy demand? * Additional details can be found in the TEPPC 2011 Study Program Study Case Scoping Form

  3. Study Case Tasks • 1. Investigate whether the impact to energy demand can be estimated within the timeframe established for preparing the study • 2. If the impact to energy demand is to be modeled, determine how the energy demands are to be modified. • For TEPPC modeling purposes, there are two ways to modify energy demands: • Modify peak and energy values for the 2022 forecasted year • Modify directly the hourly load shapes that will be used for the 2022 Common Case

  4. Study Case Tasks • 1. Investigate whether the impact to energy demand can be estimated within the timeframe established for preparing the study [yes] • 2. If the impact to energy demand is to be modeled, determine how the energy demands are to be modified. • For TEPPC modeling purposes, there are two ways to modify energy demands: • Modify peak and energy values for the 2022 forecasted year • Modify directly the hourly load shapes that will be used for the 2022 Common Case

  5. Key Considerations for Drought Impact on Energy Demand • 1. Energy Requirements of Supplemental Water • Agriculture:Increased groundwater pumping (and associated energy requirements) • Water Agencies/Suppliers: Increased reliance on energy-intensive supplies/solutions, such as desalination or inter-basin transfers. • 2. Energy Demands Associated with Increased Summer Temperatures • Increased cooling demands in commercial and residential buildings • Note: Increases in temperature have a larger impact on peak demand than total energy demand.

  6. Proposed Focus: • Impact of Higher Temperatures on Energy Demand 1. Cooling demand due to increased temperatures has a greater impact on peak demand than agricultural requirements data from 1999, [Brown and Koomey, 2002] 2. Data availability: there is more data available about high temperature impacts on cooling requirements than on increased agricultural pumping demands due to drought 3. Less regional variability: Locations, size, and number of agricultural sites; groundwater availability and rights; and pumping technology will affect the degree to which electricity demand increase at agricultural sites during drought. Cooling demand requirements also vary by location, but to a lesser degree and can be generalized more easily. 4. Time and budget constraints: Working with limited time and budget, we felt that we could provide more meaningful estimates if we focused on the single most impactful issue (the impact of higher temperatures on cooling demand).

  7. Is there an “industry standard” for adjusting energy demand (and peak demand) per degree increase in temperature?

  8. Is there an “industry standard” for adjusting energy demand (and peak demand) per degree increase in temperature? • [No*] * An annotated list of the literature we reviewed is available

  9. Is there an “industry standard” for adjusting energy demand (and peak demand) per degree increase in temperature? • [No] • Are there estimates in the literature for adjusting energy demand and/or peak demand to increases in temperature (that could be used in the WGA Drought Study)?

  10. Is there an “industry standard” for adjusting energy demand (and peak demand) per degree increase in temperature? • [No] • Are there estimates in the literature for adjusting energy demand and/or peak demand to increases in temperature (that could be used in the WGA Drought Study)? • [Yes] • A 1999 study by the California Energy Commission [CEC, 1999] provides estimates of the percent change in peak demand for each of 17 transmission areas in the Western States Coordinating Council (WSCC) due to higher summer temperatures. Of all the literature reviewed (see Appendix I), the findings of this study are most relevant to this component of the WGA Drought Study, and most easily adapted to create estimates of the change in load given the 2020 TEPPC Dataset.

  11. Proposed methodology for developing load estimates to reflect higher temperatures • Approach: Modify peak and energy values for the 2022 forecasted year • “Raw” data available from TEPPC (2020 TEPPC Dataset): • Load forecasts for PC0 and PC1: peak electricity demand (MW) and corresponding total energy demand (GWh) for all 40 transmission areas • Map depicting locations of the 40 transmission areas • Existing resources for estimating change in peak energy demand for the study area: • 1999 CEC study provides percent change in peak demand for each of 17 transmission areas in the Western States Coordinating Council (WSCC) due to an increase in the summer high temperature • Map depicting locations of the 17 transmission areas

  12. Proposed Steps • 1. Agree by consensus that the information most applicable to this WGA Drought Study is, the set of the estimates of change in peak demand for WSCC transmission areas (1999 CEC Study). • 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. • Why? The 1999 CEC Study provides estimates of peak demand (MW), not total energy. • How? Since the load forecasts for PC0 and PC1 are different for 13 of the 17 transmission areas, we could calculate how a difference in peak load corresponds to a difference in total energy for those transmission areas (from the perspective of PROMOD). In other words, we can calculate the difference (as a percent) in total energy between PC0 and PC1 per 1% difference between peak load between the two scenarios. • 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with the: • 17 WSCC transmission areas (in the 1999 CEC study) • Water Resource Regions (HUC-2 regions) of the EWN Drought Analysis“Drought years”, as identified by the selected design droughts of the EWN Drought Analysis • High temperature scenarios: A summer high 3-day average temperature with a: • 1-in-5 probability & • 1-in-40 probability • 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios*; these are the “load factors” for each transmission area.

  13. Proposed Steps • 1. Agree by consensus that the information most applicable to this WGA Drought Study is, the set of the estimates of change in peak demand for WSCC transmission areas (1999 CEC Study). • 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. • Why? The 1999 CEC Study provides estimates of peak demand (MW), not total energy. • How? Since the load forecasts for PC0 and PC1 are different for 13 of the 17 transmission areas, we could calculate how a difference in peak load corresponds to a difference in total energy for those transmission areas (from the perspective of PROMOD). In other words, we can calculate the difference (as a percent) in total energy between PC0 and PC1 per 1% difference between peak load between the two scenarios. • 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with the: • 17 WSCC transmission areas (in the 1999 CEC study) • Water Resource Regions (HUC-2 regions) of the EWN Drought Analysis“Drought years”, as identified by the selected design droughts of the EWN Drought Analysis • 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios*; these are the “load factors” for each transmission area.

  14. Proposed Steps • 1. Agree by consensus that the information most applicable to this WGA Drought Study is, the set of the estimates of change in peak demand for WSCC transmission areas (1999 CEC Study). • 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. • Why? The 1999 CEC Study provides estimates of peak demand (MW), not total energy. • How? Since the load forecasts for PC0 and PC1 are different for 13 of the 17 transmission areas, we could calculate how a difference in peak load corresponds to a difference in total energy for those transmission areas (from the perspective of PROMOD). In other words, we can calculate the difference (as a percent) in total energy between PC0 and PC1 per 1% difference between peak load between the two scenarios. • 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with the: • 17 WSCC transmission areas (in the 1999 CEC study) • Water Resource Regions (HUC-2 regions) of the EWN Drought Analysis“Drought years”, as identified by the selected design droughts of the EWN Drought Analysis • 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios*; these are the “load factors” for each transmission area.

  15. 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. Percent Change in Peak Demand; no estimate of change in total energy From 1999 CEC Report: High Temperatures & Electricity Demand: An Assessment of Supply Adequacy in California, Trends & Outlook.

  16. 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. Load forecasts from “2020 TEPPC Dataset” Estimate of % increase in total energy that corresponds to a 1% increase in peak demand (from 1999 CEC study)

  17. Proposed Steps • 1. Agree by consensus that the information most applicable to this WGA Drought Study is, the set of the estimates of change in peak demand for WSCC transmission areas (1999 CEC Study). • 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. • Why? The 1999 CEC Study provides estimates of peak demand (MW), not total energy. • How? Since the load forecasts for PC0 and PC1 are different for 13 of the 17 transmission areas, we could calculate how a difference in peak load corresponds to a difference in total energy for those transmission areas (from the perspective of PROMOD). In other words, we can calculate the difference (as a percent) in total energy between PC0 and PC1 per 1% difference between peak load between the two scenarios. • 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with the: • 17 WSCC transmission areas (in the 1999 CEC study) • Water Resource Regions (HUC-2 regions) of the EWN Drought Analysis“Drought years”, as identified by the selected design droughts of the EWN Drought Analysis • 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios*; these are the “load factors” for each transmission area.

  18. TEPPC Areas (40) WSCC Areas (17) 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with WSCC areas and Water Resource Regions Water Resource Regions (8)

  19. 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with WSCC areas and Water Resource Regions Column 1: TEPPC Areas (40) Column 2: WSCC Areas (17) Column 3: Water Resource Areas (8)

  20. Proposed Steps • 1. Agree by consensus that the information most applicable to this WGA Drought Study is, the set of the estimates of change in peak demand for WSCC transmission areas (1999 CEC Study). • 2. Quantify the relationship between peak (MW) and total energy (GWh) in the 2020 TEPPC Dataset. • Why? The 1999 CEC Study provides estimates of peak demand (MW), not total energy. • How? Since the load forecasts for PC0 and PC1 are different for 13 of the 17 transmission areas, we could calculate how a difference in peak load corresponds to a difference in total energy for those transmission areas (from the perspective of PROMOD). In other words, we can calculate the difference (as a percent) in total energy between PC0 and PC1 per 1% difference between peak load between the two scenarios. • 3. Match the 40 transmission areas in the 2020 TEPPC Dataset with the: • 17 WSCC transmission areas (in the 1999 CEC study) • Water Resource Regions (HUC-2 regions) of the EWN Drought Analysis“Drought years”, as identified by the selected design droughts of the EWN Drought Analysis • High temperature scenarios: A summer high 3-day average temperature with a: • 1-in-5 probability & • 1-in-40 probability • 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios*; these are the “load factors” for each transmission area.

  21. Note: “Issues” with five TEPPC Areas 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios

  22. Largest Increases in Total Energy Demand (top 1/5th) 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios

  23. Largest Increases in Peak Demand (top 1/5th) 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios

  24. Total Energy Demand Peak Demand Side by Side Comparison 4. Calculate percent change in forecasted peak and total energy (for PC0 and PC1) due to two high temperature scenarios

  25. Additional Assessment: How hot were the “Drought years*”? • High temperature scenarios: A summer high 3-day average temperature with a: • 1-in-5 probability & • 1-in-40 probability • Why? The 1999 CEC study looked at two high temperature scenarios • How? Summarize average monthly summer (June – August) temperatures across all 8 Water Resource Regions, for all years identified as design drought years in the EWN Drought Study (as well as the low-flow years identified in that study) to illustrate how well the “1-in-40” and “1-in-5” high temperature scenarios align with the years selected for the design drought. • * “Drought years” = years from the historic streamflow record identified as worst on record for each of the 8 Water Resource Regions, as well as those selected for the design drought: 10th percentile, “west-wide drought” (1977), and WECC low-flow year (2001).

  26. Additional Assessment: How hot were the “Drought years”? • Evaluate average monthly temperature time series data for each state in the study area • Map each state to the appropriate Water Resource Region • Calculate the “1-in-40 probability” and the “1-in-5 probability” high temperature per month for all states • Determine the relative rank of average monthly temperature among all years in the time series (1901 – 2009) in order to compare the hottest years across all states

  27. << shown during phone call>>

  28. << shown during phone call; note, NEW updated graphic at end of this file>>

  29. NOTE: From the Energy-Water-Nexus Group’s Drought Study, the 8 Water Resource Regions are spatially correlated as displayed below

  30. NOTE: The table below highlights which “drought years” apply to each Water Resource Region. GREEN shows the year of the 10th percentile drought; PURPLE shows low-flow year;BLUE shows west-wide drought (1977) & WECC drought year (2001)

  31. Assumptions • The relationship between peak (MW) and total energy (GWh) represented by the load forecasts of two scenarios (PC0 and PC1) in the 2020 TEPPC Dataset holds when conditions are hotter than average. • The two “hot” summer scenarios identified in the 1999 CEC Study (“1-in-40 probability” and “1-in-5 probability”) are representative of the type of high temperatures that would be experienced during drought conditions (representing a more “extreme” condition and a more common hotter than average condition). • The size of the change in peak load for each of the 40 transmission areas in the 2020 TEPPC Dataset is reasonably estimated by the change in peak load of the closest WSCC transmission area (from the 1999 CEC Study)

  32. Gaps/Details to Address • Four (AESO, BCTC, CFE, and PSC) of the 17 WSCC transmission areas do not have different load forecasts under the two scenarios (PC0 and PC1), so we do not have an estimate of the how total energy might increase when peak load increases. • Since the temperature data is by available by state, it is worth noting: Three of the TEPPC areas seem to cover portions of more than one Water Resource Area (WACM: Missouri, U. Colorado; PSC: Rio Grande, Arkansas (not included in this study), U. Colorado and Missouri; Pace_UT: Great Basin, U. Colorado).

  33. Limitations of Approach • There are discrepancies between the 17 areas in 1999 CEC Study and the 40 areas in 2020 TEPPC Dataset. • Data from 1999 may not be representative of current/future conditions. • The high temperature scenarios (“1-in-40” and “1-in-5”) may not correspond exactly with droughts considered in drought study.

  34. Contact Information • KC Hallett • Strategic Energy Analysis Center • National Renewable Energy Laboratory • kc.hallett@nrel.gov • 303-275-3725 • Jordan Macknick • Strategic Energy Analysis Center • National Renewable Energy Laboratory • Jordan.Macknick@nrel.gov • 303-275-3828

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