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Electric “Grid” Savings and Non-Electric Benefits for Residential HVAC-effected UES Measures . Regional Technical Forum March 20, 2013. Overview. For residential measures that effect heating and cooling usage:
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Electric “Grid” SavingsandNon-Electric BenefitsforResidential HVAC-effected UES Measures Regional Technical Forum March 20, 2013
Overview • For residential measures that effect heating and cooling usage: • RTF electric savings estimates should be reliable from an electric utility planning perspective (i.e. “Grid Savings”). • Measured Savings are considered reliable. • There appear to be non-electric benefits the RTF can account for in its cost-effectiveness tests. • Measured Savings < Modeled Savings. • Primary questions: • Is the following proposed framework for “Grid Savings” and NEB’s correct? • How should RTF monetize non-electric benefits?
Modeled Savings(“The Whole Pie”) • Definition: Estimated electric energy savings; based on physics (lower UA = lower heating energy use). • Example: Model assumes 100% electrically heated houses and “typical” usage.
Model Correction • Definition: Adjustment to modeled savings to account for non-typical usage. • Example: Partial Occupancy; occupants are away for the winter months and leave t-stat at a very low setting.
Measured Electric Savings(a.k.a “Grid Savings”) • Definition: Electric energy savings for the population, measured through submetering or billing studies.
Non-Electric Benefits • Definition: Portion of the Modeled Savings that apply to the following two non-electric components: • Fuel Savings (Non-electric) • Example: Occupant stops using their wood stove in the efficient-case, in favor of the electric heating system. • Example: Occupant continues using their wood stove, but uses less wood because of the lower house heat loss. • Increased Comfort • Example: Occupants operate their house at a warmer (winter) and cooler (summer) temperature in the efficient-case.
Not to Scale – These will vary by program, region, modeling method, etc.
Examples • DHP • Weatherization
Using DHP as an Example Non-Electric Benefits (need to monetize) Grid Savings (kWh) Notes: 1. All values in kWh/yr. 2. Values and method are for example only – we’ll discuss DHP measure specifics later. 3. Model Correction is assumed to be 0 kWh/yr based on design of Metering Study.
Using Weatherization as an Example Note: This method is shown for illustration of the framework only; it has not been reviewed by the RTF and may not meet the RTF’s guidelines.
Next Steps • In both examples, Non-Electric Benefits are quantified in kWh’s. • We need to then monetize the Non-Electric Benefits
Data Source(s) ProCost Inputs kWh/$ Conversion
How to Monetizethe Non-Electric benefits? • Option 1: Convert each Non-Electric Benefits into Dollars • Non-Electric Fuel Savings • Convert kWh savings to cords of wood savings to dollar savings • Issue: Many assumptions needed (Btu/cord; efficiency of stove, $/cord, pollution benefit, etc.) • Increased Comfort • Value at the retail cost of electricity • Occupant chose to pay for more electricity, so value of comfort should be at least equivalent to the price of electricity, if not more. • Issue: Split between Increased Comfort and Non-Electric Fuel Savings is unknown. • Option 2: Value both Non-Electric Benefits at the retail cost of electricity • Same logic as for Increased Comfort above • The “many assumptions” for converting kWh savings to cords of wood to dollar savings would likely be “calibrated” to this value. • (Value of wood calibrated to be no lower than value of electricity.)
Decisions 1. Adopt the presented framework for quantifying Measured Electric Savings and NEB’s? • Current Method • NEB’s are not included in the cost-effectiveness test. • Proposed Method • Quantify and Monetize NEB’s according to framework. • Include in cost-effectiveness test. 2. How to Monetize NEB’s? • Option 1: Convert each Non-Electric Benefits into Dollars; or • Option 2: Value both Non-Electric Benefits at the retail cost of electricity • Other Options
Related slides from the January 2014 RTF Meeting (“SEEM 94 Calibration to RBSA Data” Presentation)