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1 Modeling Disturbances to Electric Power in the South: An Initial Step By: Marilyn Brown and Alex Smith Georgia Institute of Technology August 29, 2014.

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Presentation on theme: "1 Modeling Disturbances to Electric Power in the South: An Initial Step By: Marilyn Brown and Alex Smith Georgia Institute of Technology August 29, 2014."— Presentation transcript:

1 1 Modeling Disturbances to Electric Power in the South: An Initial Step By: Marilyn Brown and Alex Smith Georgia Institute of Technology August 29, 2014 This analysis was conducted for Georgia Tech’s “Future of Electric Power in the South” (FEPS) initiative.

2 2 Progress Since our August 8 th FEPS Webinar Continued to examine options for modeling “disruptions”. Modeled an initial disruption scenario using Georgia Tech’s National Energy Modeling System (GT-NEMS 2014). Developing an approach to modeling EPA Section 111(d) compliance options in the South on September 19 at 2 pm. Plans have continued for a meeting co-convened with Duke University’s Nicholas Institute at Georgia Tech on September 26: “Shaping the Southeast’s Energy Future: Regional Electricity Trends and the EPA’s Clean Power Plan”

3 3 The Value of Modeling Disturbances Members of the FEPS Economics Working Group advocated the use of scenario modeling to “stretch the limitations” of popular thinking regarding the future of electric power, rather than simply forecasting expected trends. “it is more important to develop scenarios that involve imperfect foresight to show the potential impact of hard-to-predict disturbances or sudden changes in trends affecting electric power systems”

4 4 Our Initial “Disturbance Scenario” Has Multiple Storylines We model a case where beginning in 2020 electricity demand significantly exceeds expectations, creating a need for rapid power system expansion. This type of disturbance could be caused by:  A sudden surge in global warming  Malaise in EE and DG (the anticipated “vicious cycle of utility company demand loss doesn’t play out”)  A battery breakthrough that enables electric vehicles  Rapid expansion of digital networks and the industrial internet

5 5 The South Census Region For the analysis or energy demand, we focus on the U.S. Census Bureau’s Southern Region with three Census Divisions and 16 states plus DC. For the analysis of electricity systems, we examine four regions defined by the North American Electric Reliability Corporation (NERC): the Southeast Reliability Council (SERC), the Southern Power Pool (SPP), the Texas Reliability Entity (TRE), and the Florida Reliability Coordinating Council (FRCC).

6 6 Disturbance Scenario in GT_NEMS NEMS uses “perfect foresight” in modeling its electricity capacity planning  NEMS completes a cycle of modeling with a demand projection  Capacity planning module uses prior cycle’s demand projection as its demand expectation for current cycle  NEMS iterates until current cycle demand expectation and current cycle demand projection match We de-activate perfect foresight  Expectations are based on prior two-year demand projection in current cycle instead of prior cycle’s demand projection We overwrite expectations with demand growth rates of low economic growth side case  0.5% lower demand growth on average nationally

7 7 Reference Case Demand Exceed Expectations Demand expectation deviations vary by sector Gap between demand and expectations for the commercial and residential sectors are greater in the South than the rest of the country; smaller for industry.

8 8 The Disturbance Causes Less Capacity to be Built, and Less Generation Capacity____________ Generation__________

9 9 Disturbance scenario exhibits improved energy efficiency of US economy Disturbance case exhibits a ~5% decrease in energy intensity of US economy

10 10 Recall that Electricity Prices in the South are Projected to Remain Low History Projections 2012 Projection for the South Average Electricity Prices in the South, 2005-2040 (2012 cents per kWh) The average annual growth rate of retail electricity prices from 2013- 2040 is forecast to be 0.51% for the US, 0.47% for the South Average Electricity Prices in the U.S, 2005-2040 (2012 cents per kWh)

11 11 The Disturbance Scenario Increases Electricity Prices Non-SouthSouth Reference Case ($/kWh) Disturbance Case (% change) Reference Case ($/kWh) Disturbance Case (% change) Residential Demand 2020 0.134 5% 0.110 5% 2025 0.135 8% 0.110 10% 2030 0.140 9% 0.113 13% Commercial Demand 2020 0.111 6% 0.098 6% 2025 0.112 11% 0.097 12% 2030 0.116 12% 0.100 16% Industrial Demand 2020 0.079 9% 0.066 8% 2025 0.081 14% 0.067 16% 2030 0.086 16% 0.070 22%

12 12 Recall the Forecast for Electricity Generation by Fuel in the South History Projections 2012 Electricity generation by fuel in the South, 2005-2040 (trillion kWh) Natural Gas Renewables Nuclear Coal Petroleum liquids and other Electricity generation by fuel in the U.S., 2005-2040 (trillion kWh)

13 13 The South’s Response to the Disturbance Scenario South’s 2030 power portfolio The South responds to low load expectations by shedding coal Natural gas becomes the preferred fuel for electric power for meeting the unexpected demand Reference CaseDisturbance Case

14 14 The Rest of the Country’s Response to the Disturbance Scenario Non-south’s 2030 power portfolio Non-south’s response to disturbance involves retaining its renewables. Still, natural gas is the “swing fuel” for this region as well Reference CaseDisturbance Case

15 15 Ideas for Further Work on Disturbances What other sorts of disturbances should be modeled?  The FEPS Economics Working Group agreed that some scenario involving a natural disaster or weather-related event would be useful, as such disturbances are expected to be more likely and more severe in the future – e.g. drought scenario Two other scenarios were suggested:  a high electricity demand, high economic growth scenario  a low electricity demand, low economic growth scenario.  Each of these scenarios was then to receive its own “shock”– that is, a sudden change in trend. Value of identifying low-cost means to improving power system resilience  Modeling alternate assumptions with disturbances

16 16 Next Steps for FEPS Develop approach to modeling EPA Section 111(d) compliance options in the South. Prepare preliminary results to discuss at the fourth FEPS webinar on September 19.

17 17 For More Information Professor Marilyn A. Brown School of Public Policy Georgia Institute of Technology Atlanta, GA 30332-0345 Marilyn.Brown@pubpolicy.gatech.edu Climate and Energy Policy Lab: http://www.cepl.gatech.edu Research Assistants: Alexander Smith asmith313@gatech.edu asmith313@gatech.edu Gyungwon Kim joykim@gatech.edu


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