March 1, 2011 Load Analysis Update Calvin Opheim Manager, Load Forecasting and Analysis

2 Agenda Current work underway –Load Forecast –Energy Efficiency –Plug-In Electric Vehicles (PEV) Future work –Distributed Generation (premise) –Demand Response March 1, 2011

3 Load Forecast Completing the Business as Usual (BAU) scenario load forecast –Economic Data Moody’s economic forecast (base economic forecast) Expect to be receiving their low and high case economic forecasts by the end of March (used in future sensitivities) –Energy Efficiency Impacts Based on data that was reported to the PUC Effects from the historical time period used in model development are included in the forecast Will not include additional incremental energy efficiency adjustments in the first iteration of the business as usual load forecast March 1, 2011

4 Load Forecast Completing the Business as Usual (BAU) scenario load forecast (cont) –Distributed Generation Impacts –Demand Response Impacts –Plug-in Electric Vehicles Impacts Will not be including additional incremental energy adjustments for the above in the first iteration of the business as usual load forecast Load forecast will be created at the county level March 1, 2011

5 Energy Efficiency ERCOT is evaluating the following three approaches for developing energy efficiency impacts to the load forecast –Building a “bottom up” model of impacts using data from the “Assessment of Feasible and Achievable LeveIs of Electricity Savings from Investor Owned Utilities in Texas: ” ( g_ _ pdf) g_ _ pdf –Building a “bottom up” model of impacts using the model that has been developed by Dr. Haberl from Texas A&M –Building a “top down” model. This approach is being investigated in California ( 2012_Energy_Efficiency_EM&V_Plan_ pdf, Chapter 7) 2012_Energy_Efficiency_EM&V_Plan_ pdf March 1, 2011

6 Energy Efficiency – Bottom Up Models “Bottom up” models measure individual impacts –Examples (far from an exhaustive list) Replacing existing air conditioning unit with higher SEER unit, Implementing an energy management system, Replacing incandescent light bulbs with compact fluorescent lamps (CFLs), lighting controls, etc. The change in electric consumption is calculated for the specific location. The estimated savings from the location are then generalized to all similar locations. March 1, 2011

7 Energy Efficiency – Top Down Models “Top down” models quantify the energy efficiency impact based on aggregate customer levels such as residential, commercial, or industrial. Using aggregate customer 15-minute load shapes, determine statistically the component of load that is weather sensitive and the component of load that is not weather sensitive (base load). By applying assumed energy efficiency improvements for weather sensitive load and/or base load, an adjusted aggregate customer load shape can be created. March 1, 2011

8 Energy Efficiency Note there is no consensus as to which approach is “better” Goal is to complete the first iteration of the long-term energy efficiency load forecast by June March 1, 2011

9 Plug-In Electric Vehicles Data has been collected and an initial model has been created Contains four charging pattern scenarios from the report entitled “Costs and Emissions Associated with Plug-In Hybrid Electric Vehicle Charging in the Xcel Energy Colorado Service Territory” ( –Uncontrolled - charging occurs only at home at the owners discretion –Continuous - charging occurs at anytime during the day –Delayed - charging at home beginning at 10 pm –Off peak - charging at home during the overnight hours when prices are assumed to be lowest March 1, 2011

10 Plug-In Electric Vehicles Used hourly load shape from a NYISO report entitled “Alternate Route: Electrifying the Transportation Sector Potential Impacts of Plug-In Hybrid Vehicles on New York State’s Electricity System” ( es/2009/Alternate_Route_NYISO_PHEV_Paper_ pdf) es/2009/Alternate_Route_NYISO_PHEV_Paper_ pdf March 1, 2011

11 Future Work – Distributed Generation Create Distributed Generation (DG) premise models –Currently there are 1,100 premises with DG in competitive areas –Of these, 340 have interval data meters (15-minute data) Will analyze the interval data and the registration information to assist in the development of the models March 1, 2011

12 Future Work – Demand Response Create Demand Response (DR) model Will analyze the FERC report and investigate the possible transfer of some/all of their methodology to ERCOT ( response.pdf) response.pdf March 1, 2011

13 Questions March 1, 2011 ON OFF

14 Contact Information For additional information: Phone March 1, 2011