Demand response and energy efficiency are part of a larger suite of activities that utilities use to call upon their end-use customers to modify their demand (collectively referred to as demand side management). Both DR and EE rely upon end-use equipment and thus there is overlap between the potential of each. The interaction may be complementary or destructive – meaning installing energy efficiency measures may increase or decrease the availability of demand response. The 2021 Plan accounts for this interaction in the strategy analysis.

In the Northwest Power Act, energy efficiency is considered a priority resource [Northwest Power Act, §4(e)(1), 94 Stat. 2705]. In part because of the Act, EE has a long history in the region, with a robust infrastructure of implementation and adoption.  DR, on the other hand, is less prevalent and without the same strong foundation.[1] As such, the 2021 Plan assumes EE “comes first” when compared against demand response. In other words, the demand response potential is impacted by the EE adoption and not the other way around.

Description of Interaction

The interaction between energy efficiency and demand response was calculated differently depending on whether the product potential was estimated using the bottom-up methodology or the top-down methodology.

Bottom-up Products

For the bottom-up products, the DR potential is directly related to the number of available units. The table below provides the relationship between the EE measure and DR products evaluated using the bottom-up methodology.

Bottom-Up DR Products Interaction with Energy Efficiency

DR Product

EE Measure

Interaction as EE is acquired

Water heater control

Heat pump water heaters

DR potential shifts from electric resistance to heat pump water heater

HVAC control

Smart thermostats

DR potential shifts from AC/heat switch to BYOT

Thus, if through the EE supply curves, one million additional smart thermostats are available by the end of the plan period, the additional DR potential for BYOT will be one million multiplied by the impact per thermostat. There will also be one million fewer homes available for the AC and heat switch products and thus a reduction in the potential for those products. The total DR potential will be affected as the per-unit impact differs between a switch and a thermostat or between a heat pump water heater and an electric resistance water heater. (Per unit impact assumptions for these products can be found here).

Top-down Products

The DR potential is calculated for top-down products based on the end-use loads. Energy efficiency will reduce these loads; thus, the DR potential will decrease. In all cases, the relationship is destructive – energy efficiency only decreases the DR potential. Note, it may be that the installation of energy efficiency measures may help enable a customer to participate in a DR program. For example, high efficiency LED lighting is often coupled with integrated controls that could then be used for a DR program, resulting in an increased participation and/or reduced cost. As this is generally a secondary effect, this type of interaction was not explicitly captured in the analysis.

EE/DR Interaction Input Parameters 

In essence, to estimate this interaction, we calculate the peak megawatt reduction of EE for a certain bin and the corresponding reduction in potential for certain bin of DR. Then we take the ratio as follows: reduced DR potential in megawatts divided by the reduced peak load from EE in megawatts.

More specifically, we derive an array with multiplier \varepsilon _{i,j}, where i is the conservation bin number and the j is the DR bin number. Let m be the number of EE bins (currently, 14) and n be the number of DR bins (currently, 4). The term gif.latex?%5Cvarepsilon%20_%7Bi%2Cj%7D is defined as the following:

gif.latex?%5Cvarepsilon%20_%7Bi%2Cj%7D%20%3D%20%5Cfrac%7B%25%5CDelta%20DR_j%7D%7BEst%28%25%5CDelta%20EEPeak_i%29%7D

where Est(%\Delta EEPeak_i)  is an estimate of the percent of peak load contribution of conservation in bin i  of the total estimated peak load, and %\Delta DR_j  is the percent of DR potential reduced in bin j.  The m by n array that is populated by gif.latex?%5Cvarepsilon%20_%7Bi%2Cj%7D.

%\Delta EEPeak_i = \frac{(\Sigma_{x\leq p}(EE_i)_x){PeakRatioEE_i}}{(FEPeakDemand)_p}

where p is the current period,  FEPeakDemand  is the frozen efficiency peak load forecast in that period, and PeakRatioEEi  is the peak MW to aMW ratio for bin i of conservation. 

More details can be found in this presentation.

 

[1] There have been DR programs in the region starting in 1977, but limited sustained investment, see https://www.bpa.gov/EE/Technology/demand-response/Pages/history-of-dr.aspx

 

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