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Energy Efficiency Evolution: New Opportunities for Utility Programs

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Val Jensen's picture
Senior Fellow ICF Climate Center

Val is a specialist in the energy industry field with over 40 years of experience. As Senior Vice President for strategy and policy at Exelon Utilities, he oversaw technology and business...

  • Member since 2021
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  • Jul 27, 2022
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This item is part of the Energy Efficiency - July 2022 SPECIAL ISSUE, click here for more

Energy efficiency has delivered huge benefits over the last 40 years. Roughly 20 percent of the carbon dioxide (CO2) reductions in the electric power sector have been the result of reduced energy use; and, the magnitude of energy efficiency savings (211 billion kWh) was more than double the output of solar generation (96 billion kWh in 2018). Yet, we’re at an inflection point today. Efficiency is growing more expensive as incremental savings targets grow, and more pressure is put on energy efficiency programs as a key part of reaching deep carbon reduction.

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In turn, there is a growing sense across the industry that “what got us here won’t get us there,” where “there” is a largely clean energy economy underpinned by a very different electric power industry. Essentially, there is agreement that acquiring future energy savings will require a refreshed approach. Meeting the challenges associated with delivering more energy efficiency while achieving deep carbon reductions will require both policy and program design, delivery, and evaluation changes.

Program design, delivery, and evaluation challenges

In traditional programs, most savings came from rebate-driven commercial and residential lighting programs. However, continued shifts in federal lighting efficiency standards effectively reduce the savings that electric companies can reap from lighting-focused rebate programs significantly. Similar increases in the baseline efficiency of major appliances due to federal standards further reduce achievable efficiency potential in a variety of end uses.

Further, the cost-per-saved-kWh has been increasing, particularly for those electric companies that have been operating energy efficiency programs for a number of years. Although a recent Lawrence Berkeley National Lab study found that the national average cost of saved energy continues to be low at 2.5 cents-per saved kWh over the life of the programs, the report also highlighted significant cost disparities. The effect of rising cost-per-saved kWh is that budgets required to achieve any given level of savings must increase or, in the case of electric companies with statutory or regulatory budget caps, savings will be lower than they otherwise might be.

Existing program designs have also been heavily influenced by evaluation, measurement, and verification (EM&V) beliefs and practices that less and less reflect energy efficiency policy aims, advances in data analytics, or the growing understanding of customer behavior. This has created a bias toward programs that are easily evaluated, disincentivizing utilities to explore more innovative program designs that would require complicated analysis to determine program performance.

How efficiency and increased electrification support deep carbon reductions

Utilities also need to reconcile efficiency and increased electrification to achieve deep carbon reductions—and to adapt to a more distributed and dynamic energy grid. Momentum is building: at the end of 2019, carbon emissions in the U.S. power sector were 33 percent below 2005 levels.

Challenges arise when state energy efficiency targets meet state carbon reduction targets that require increases in electricity use. Ultimately, policies focused on reducing energy use will need to evolve to address efficiency and electrification in the context of deep carbon reductions. Reducing electricity use remains an important objective, but deep carbon reductions and a need to manage an increasingly dynamic grid require efficiency programs that can accommodate increased electrification and that can be deployed to meet time- and location-dependent grid management needs.

Elements of a new approach to electric company-administered energy efficiency

These challenges to the traditional approach to energy efficiency investment don’t diminish the value of the resource but do beg for a variety of policy, design, implementation, and evaluation changes. First, clear policy objectives need to be set upfront, such as reducing aggregate customer bills; deferring/avoiding the need for generation, transmission, and/or distribution investment; reducing carbon emissions more broadly; and providing bill relief for economically disadvantaged customers. Failure to align on the specific objectives and how achievement is to be measured creates uncertainty and risk.

Additionally, the near-simultaneous rise of powerful data analytics, powerful insights about how customers make energy use decisions, and powerful, inexpensive measurement and control devices have made possible a very different approach to program design that is driving an evolution from energy efficiency to smart energy programs. The evolution to smart energy programs is driven by five interrelated capabilities:

  • Data-driven insights. Granular energy use data can yield very specific insights about how a customer uses electricity and where opportunities for reducing/shifting use can be found. These insights can be paired with propensity data/models to identify the most valuable and likely participants in a smart energy program much more effectively.
  • Personalized offerings. These same data insights can help electric companies deliver actionable information tailored to individual customers through the channel most likely to attract their attention.
  • EM&V 2.0. These same data combined with sophisticated analytics can greatly improve program EM&V. The wider application of statistical techniques such as randomized control trials has boosted confidence in the savings associated with programs not reliant on specific technologies being installed. These techniques allow electric companies to shift the focus of EM&V from the behavior of individual customers to the aggregate behavior of groups of participants.
  • Pay-for-performance. This shift in focus supports the broader use of pay-for-performance (P4P) programs that reward customers, not for taking specific prescribed or allowed actions, but for achieving specific policy objectives (e.g., saving energy, reducing GHG emissions, etc.). These programs greatly simplify program logic models as the program administrator no longer decides which technology will be incented through which channels, leaving those choices to customers and the market.
  • Energy orchestration. The rapid fall in the cost of digital sensing and control technology has given rise to a new set of energy management technologies. From smart communicating thermostats to sophisticated campus-wide building energy management systems, technology gives customers and electric companies the ability to automatically adjust energy use quickly in response to system conditions.

Overcoming challenges such as rising costs associated with delivering more energy efficiency will require simultaneous policy and program overhauls. But there is hope: the data and analytics revolution sweeping the industry offers exciting opportunities both to improve program marketing and implementation and to support more customized and market-based efficiency programs at potentially lower cost. Combined with a wide range of inexpensive new sensing and control technologies, data-driven programs offer great promise as part of the next generation smart energy programs.

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Lily Li's picture
Lily Li on Jul 27, 2022

Great points in here, Val.  EE Programs designed a decade or more ago simply don't focus on today's goals for GHG reductions.  The days when assuming EE = GHG are numbered.  Data driven personalization, and site specific pay-for-performance oriented to GHG goals need to become utility priorities.  Thanks for the insights and the references.

John Benson's picture
John Benson on Jul 29, 2022

Hi Val. thanks for the post.

Appliance energy efficiency (including lighting, HVAC, etc.) always has a good payback, assuming two things: a reasonable period and a true cost of energy. The latter should include the true cost of emissions (greenhouse gas and others). This has been true for many decades. See the link to an earlier paper below for the early days of these programs in my home state (California).


https://energycentral.com/c/um/godfather-energy-efficiency
 

-John

JESSE NYOKABI's picture
JESSE NYOKABI on Aug 1, 2022

Am keen to see how artificial intelligence and IoT will contribute to EE.

Paul Meier's picture
Paul Meier on Aug 3, 2022

This is an excellent topic and I think we can point to several things that have led to CO2 reduction besides reduced energy use. First, there has been a large transition from coal to natural gas. Coal, which was responsible for 53% of the US electricity generation in 1998 was 19.3% in 2020, as natural gas has taken the leadership role (40.5%), surpassing coal in 2015 as the primary energy for producing electricity. Also, many natural gas plants now use combined cycle, using two turbines (gas and steam turbine) instead of just using combustion, thus increasing efficiency and lowering CO2 emissions.

In addition, wind and solar PV electricity generation are growing, especially wind. In 1989, there was no electricity generated from either wind or solar power. Now, after years of growth, the combined US generation from wind and solar PV surpassed hydroelectricity in 2017.  And currently, sixteen states generate more than 10% of their electricity from wind and four generated more than 30% (IA, 57.3%, KS, 43.9%, SD, 39.2%, OK, 35.7%).

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