TEP-UNS Electric Load and Peak Demand Forecast Overview Jon M. Bowman Senior Supply-Side Planner TEP and UES Resource Planning Workshop 1
Objectives Provide an overview of the load and peak demand forecasts for TEP and UNS Electric (Prior to additional DSM/EE adjustments) Discuss the key inputs, data sources, and tools used in the forecasting process Identify key areas of uncertainty that have the potential to significantly impact future iterations of the forecast 2
TEP and UNS Electric Service Territories UTAH COLORADO NEVADA Mead Navajo Kayenta Ship Rock Four Corners Navajo San Juan San Juan Mine Davis Black Mountain Kingman Griffith N. Havasu Lake Havasu Parker City Peacock Pinnacle Peak Palo Verde Pinal West Liberty Prescott Yavapai West Wing Phoenix Saguaro Moenkopi Flagstaff South Cholla Tucson Sundt Vail Coronado Springerville Greenlee McKinley Mine Hidalgo McKinley Luna Lee Ranch NEW MEXICO Service Areas TEP UNS Gas UNS Gas & Electric UNS Electric High Voltage Transmission Lines Generating Station Coal Mine Interconnection With Other Utility Substation Solar Station MEXICO Valencia Nogales 3
Methodology A monthly load forecast is prepared for each of the major rate classes: Residential Commercial Industrial Mining Other (street lighting, etc.) The individual rate class level forecasts are aggregated to produce the total load forecast for each company A monthly peak demand forecast for each company is prepared based on: Anticipated load Historical relationship between consumption and peak demand 4
Methodology, cont. Load forecasts for the residential and commercial classes are based primarily on statistical models with inputs including: Weather (e.g. HDD, CDD, Humidity, etc.) Demographic forecasts (e.g. population growth) Historical usage patterns Economic indicators Price response (TEP December 2008 rate increase first in 13 years) Load forecasts for the industrial and mining rate classes are prepared individually for each customer based on: Historical usage patterns Inputs from the customer (e.g. planned operational expansions) Inputs from account managers 5
Data Sources Data used in the forecasting process is collected from a variety of sources including: IHS Global Insight The University of Arizona Forecasting Project Arizona Department of Commerce U.S. Census Bureau 6
TEP Forecast Summary 7
8 TEP 2008 Sales by Rate Class Other 3% Mining 11% Industrial 24% Residential 41% Commercial 21%
Residential Customers Residential Customer Growth Rate 370,000 TEP Residential Customer Growth 3.00% 360,000 2.50% 350,000 340,000 2.00% 330,000 1.50% 320,000 1.00% 310,000 300,000 0.50% 290,000 2001 2002 2003 2004 2005 2006 2007 2008 2009 0.00% 9
Commercial Customers Commercial Customer Growth Rate 1 36,000 TEP Commercial Customer Growth 3.00% 35,000 2.50% 34,000 33,000 2.00% 32,000 1.50% 31,000 1.00% 30,000 29,000 0.50% 28,000 2001 2002 2003 2004 2005 2006 2007 2008 2009 0.00%
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 GWh Sales 13,000 12,000 TEP Reference Case Load Growth Price Impacts (Rates, PPFAC) Lower Population Growth Structural Changes 11,000 10,000 ~1.5% Average Growth 2010-2020 9,000 ~2.2% Average Growth 1998-2008 ~0.8% Average Growth 2009-2010 8,000 7,000 6,000 Increase in Average Home Size High Population Growth AC and Appliance Saturation 5,000 Actual Load Forecast Load 11
GWh Sales 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 12 6,000 TEP Reference Case Load Growth by Segment 5,000 Actual Projected 4,000 Residential 3,000 Industrial 2,000 Commercial 1,000 Mining 0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Peak Demand (MW) 3,500 TEP Reference Case Peak Demand Growth 3,000 2,500 2,000 1,500 1,000 Actual Demand Baseline Forecast 13
Risks to Forecast Recession and Recovery Timing and strength of recovery Possible structural changes Copper price volatility (Mining) Impact of Technological Innovation Efficient lighting, appliances, etc. Plug in hybrids Volatility and Uncertainty in Demographic Assumptions Higher population growth than currently forecast Significant changes to persons/household, etc. High levels of uncertainty in forecast assumptions necessitate the consideration of multiple scenarios 14
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Peak Demand (MW) 3,600 TEP Peak Demand Scenarios High Growth 3,400 Plug in Vehicle 3,200 3,000 Reference Case 2,800 2,600 DSM Target 2,400 2,200 2,000 15
UNS Electric Forecast Summary 16
UNS Electric Estimated 2009 Sales Mix Industrial/Mining 20% Residential 45% Commercial 35% 17
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total Sales (GWh) 2,600 2,400 UNS Electric Reference Case Load Growth Lower Population Growth 2,200 2,000 1,800 ~2.3% Average Growth 2010-2020 1,600 1,400 1,200 High Population Growth Mining Expansion Obscures Res/Com Slowdown 1,000 Actual Load Forecast Load 18
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 GWh Sales 1,200 UNS Electric Reference Case Load Growth by Segment Projected 1,000 Actual Residential 800 600 Commercial 400 200 Industrial/Mining 0 19
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Peak Demand (MW) 650 UNSE Reference Case Peak Demand Growth 600 550 500 450 400 350 300 Actual Demand Baseline Forecast 20
TEP and UES Resource Planning Workshop 1