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To deem or not to deem? That is the (valid) question.

During the annual program planning and design phase, energy efficiency utility incentive program implementation teams have to consider how to balance risk and reward when determining whether measures should be custom or prescriptive. A utility and a program implementer have to consider the pros and cons when deciding whether to make a measure prescriptive or custom.

One consideration, apart from risk management, is the marketable influence of the prescriptive measures. The results of our two-year national contractor survey identified that, aside from the incentives, the fact the local utility has endorsed a list of measures is sometimes the only utility marketing support that is needed to sell them. Additionally, there is a higher risk for a customer (even when supported by a contractor) to implement a measure that is not on the list for a prescriptive rebate. The custom calculated incentive based on measured and verifiable savings may increase their hesitation to implement a measure without knowledge of the expected co-payment. The incentive amount helps customers make the decision to proceed with the installation, although there is a larger risk with custom measures.

In most cases, the prescriptive measure savings estimates are considered locked in and the evaluation risk is minimal. However, because some of the prescriptive measures are not backed by a Technical Resource Manual (TRM) or have received ex-ante (pre-evaluation) review and may have been adjusted, there is a risk for the implementer/utility. However, custom measures bring risk for all involved parties.

Consequently, when DNV GL weighs the benefits and risks associated with classifying a measure as prescriptive, our analysis includes the following considerations:

  • What is the regulatory infrastructure?
  • Are the deemed values locked in?
  • Besides the first year savings risk, what other risks exist? Peak demand, non-energy benefits, lifetime savings, and cost-effectiveness are a few to consider.
  • What level of risk is acceptable? Are the program managers and utility leadership okay with a +/- realization rate greater than 5 or even 10%?
  • How can risks be mitigated based on goals?
  • When does it make sense to determine a deemed value?
  • Is it too early to push the measure forward because there is low confidence in the value? Or is the calculated savings value too dependent on large variances of the independent variables?
  • Can a measure have a calculated deemed or quasi deemed value (or in other words pay a prescriptive incentive and custom-calculate the savings) to address potential savings variability?
  • Custom takes more time and resources than prescriptive, for both the regulator and implementer.
    • Is the benefit greater than the cost to society?
    • Are increased kWh savings worth the increased cost?
  • What are the pros and cons of transforming custom measures into prescriptive measures: will the disruption to the marketplace and end use customers be positive, negative or both?

Addressing these questions could be a blog unto itself.  Instead, in this post, we will highlight a few key areas:

  • Defining variability
  • Mitigating evaluation risk while balancing customer satisfaction/service

Defining Variability

Let’s start with one area many are very familiar with: deemed lighting savings. Even though lighting savings with no change in fixture wattage range is quite straightforward, the industry has moved on and the per-widget calculation of the rebate will become a relic of the past. Calculating lighting savings depends on the following:

The second equation addresses variability in both pre- and post-installation wattage and operating hours. The pre- and post-wattage variability is new and does not appear in many TRMs or deemed measures, but this is more prevalent today due to the increased penetration of LEDs. Pre- and post-wattage may not always equal the specification sheet wattage due to various control technologies. If we break down the approach without the last item, pre- and post-operating hours have been highly studied over the years with many metering studies that are typically disaggregated by building type (and occasionally by space type). Pre- and post-wattages are well known and documented by the measure specification definition with a small range of possibilities. All of this is not relevant for LEDs. Post-wattage LEDs can be highly variable and dependent on the space and fixture design, as well as controls.

Next, we examine variable speed drives (aka VSDs or VFDs). DNV GL moved variable-speed drive measures to prescriptive several years ago for many of its programs. This is similar to lighting where the wattage (pre- and/or post-retrofit) can vary; however, in this case, fixture wattage is replaced by load variability. We found that load and savings can vary from 0 to 90% for retrofit. Our understanding of risk and the regulatory framework are all taken into consideration when deciding which measures could be deemed versus needing to go through a site-specific calculation.  Additionally, if you start reviewing the deemed workpapers/TRMs for VSDs, the methodologies and inputs used across the country are quite diverse. We believe that part of our role in due diligence and risk management as an implementer (as well as program planner/designer) is to help specify the measure requirements for eligibility based on the balance of cost and risk. This can be done more easily by simplifying the program measures (one line item for VSD installations) or identifying multiple conditions/applications (VSDs on pumps, fans, cooling tower fans, or process motors).

Mitigating Evaluation Risk

One risk mitigation strategy is to undertake a portfolio analysis. Regardless of whether program design requirements dictate cost-effectiveness on a measure level or portfolio level, there is a need to understand the measure level expectations of the program term (annual or some other length of time). If there is a desire to have a low or high tolerance of realization rate exposure, a measure level analysis provides a starting point for sensitivity analysis and insight on what to expect, which can help to balance the risk. One of the things we look for in this review is the expected volume of projects for “high risk” deemed measures that may be in the 0-90% savings range. This includes compressed air, energy management system (EMS), and VFDs/VSDs. In addition, it is critical to determine the penetration of the measure in the marketplace (e.g. past the maturity phase of the market diffusion) for the program for balancing free-ridership.

Conclusion

So far, our risk has been minimal on these variable measures and we deliver a balanced portfolio with strong realization rates. But, DNV GL monitors the rate of growth or decline of these measures or measure potential which is critical to insure the overall program/portfolio gross realization rate does not significantly impact cost-effectiveness.

Our team offers dynamic measure design while anticipating and responding to changing market conditions, so that the program achieves reliable and robust progress toward goals and stays relevant to customer and trade ally needs.

Karen Maoz is a Senior Consultant with DNV GL.  Karen has more than 16 years of experience in energy efficiency ranging from program planning, research, evaluation, and implementation. One of her areas of focus has been in annual program planning and moving appropriate measures from custom to prescriptive. Karen has a Bachelor of Science in mechanical engineering from the University of Texas Austin, and a Master of Science in mechanical engineering from the University of California, Berkeley. She is a registered PE in California and is on the Board of Directors for the AESP California Chapter.

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