TODAY’S STUDY: A Review Of Alternative Rate Designs
A Review Of Alternative Rate Designs; Industry Experience With Time-Based And Demand Charge Rates For Mass-Market Customers
Aman Chitkara, Dan Cross-Call, Becky Li, and James Sherwood, May 2016 (Rocky Mountain Institute)
There is a serious conversation unfolding around electricity rate design for mass-market (residential and small commercial) customers—both in the U.S. and internationally. New proposals are appearing for how to improve rates to meet emerging challenges (and opportunities) around environmental impact, customer engagement, bill management, reliability, and cost recovery. These proposals frequently generate debate and conflicting opinions between stakeholders.
RATE DESIGN CHALLENGES
Recent trends are forcing stakeholders across the industry to take stock of how customer needs are evolving and how that affects the electricity system. Customer load profiles are becoming more diverse while new technology is increasing potential customer capabilities. Existing default rates in the U.S. are simple—typically pairing a flat, volumetric energy rate with a customer charge. These rates have worked well enough but are proving inadequate in the face of recent trends, as they fail to provide price signals that reflect system costs and enable customer response. An expanded rate design toolkit is needed, but it is critical that solutions do not reduce signals for energy efficiency or be difficult for customers to understand and respond to.
Two types of alternative mass-market rate designs are often proposed to meet rapidly evolving customer needs in the near-term:
• Time-based rates can provide more accurate price signals to customers, better reflecting the marginal cost of supplying and delivering electricity. These price signals may lead customers to change their consumption patterns to reduce both peak and total consumption.
• Demand charge rates can provide a price signal to reduce peak demand and can potentially allocate peak driven costs more fairly. Customers may respond by changing their consumption patterns to reduce peak demand, flattening their load profile. These solutions can be important near-term steps in the ongoing evolution of rate design.
Objectives of This Report
To support informed decision making, this report provides a meta-analysis of numerous existing studies, reports, and analyses to support an objective assessment of the efficacy of time-based rates and demand charge rates for mass-market customers. The report:
• Provides a structure for utilities, regulators, and stakeholders to design and evaluate time-based and demand charge rates.
• Identifies major design choices required for each rate, and reviews options for those dimensions.
• Identifies whether empirical data confirms (or refutes) the potential benefits of each rate, and notes where clear evidence is not available.
• Determines best practices that can help achieve and maximize desired outcomes.
• Highlights areas where further study is needed.
RESEARCH INSIGHTS ON TIME-BASED RATES; RANGE OF FINDINGS
Our review of industry experience with time-based rates finds that they can reduce customers’ peak consumption and total energy consumption without compromising customer acceptance (in terms of enrollment and retention). Empirical evidence shows that time-based rates have the potential to result in:
• Peak load reduction of 0–50%
• Reduction in total energy consumption of 0–10%
• Customer enrollment rates of 6–98% and retention rates of 63–98% These impacts depend on key choices made in designing the rate.
KEY DESIGN CHOICES THAT INFLUENCE IMPACTS
The impact of time-based rates can vary widely, as evidenced by the wide ranges at left.
This variation is influenced by key choices made along nine important design dimensions. Several of these dimensions have a particularly noteworthy effect on the efficacy of the rate:
• Peak/Off-Peak Price Ratio is one of the strongest predictors of customer peak load reduction, as higher ratios send a stronger price signal to shift consumption away from peak hours—for instance, time-of-use rates with a 5:1 ratio tend to double the peak reduction compared to a 2:1 ratio.
• Peak Period Duration and Peak Period Frequency have a significant impact on customer acceptance. Customers are less willing to enroll in a rate, and less able to respond once enrolled, where the peak periods are too long or when critical peak pricing events occur too often.
• The Financial Mechanism is a strong driver of peak load reduction. Price-based rates can double the reduction achieved with rebate-based rates, which reward conservation but do not penalize consumption.
• The Enrollment Method affects customer acceptance, where opt-in rates attract more-engaged participants, but opt-out (default) rates have enrollment rates 3–5 times higher than opt-in rates, as well as increased peak reduction.
• Enabling Technology can substantially increase the peak load reduction by customers. Rates coupled with “active” technologies (which automate customer response) reduce peak load by an additional 10–20 percentage points compared to the same rate without technology.
RESEARCH INSIGHTS ON DEMAND CHARGE RATES; RANGE OF FINDINGS
Our review finds that there is comparatively little industry experience with mass-market demand charges relative to time-based rates. Limited empirical evidence is available to provide insight on the efficacy or impact of demand charges on any desired outcome beyond cost recovery. However, there is a serious debate and much theory about how they may affect customers’ peak consumption, total energy consumption, and acceptance.
Claims regarding the impact of demand charge rates on these outcomes (positive or negative) are largely speculative. The industry needs to better align on what is currently known and unknown, and where further research will be most useful.
KEY DESIGN CHOICES THAT INFLUENCE IMPACTS
While there is a clear gap in the empirical evidence, our research suggests that there are key design choices that will determine the efficacy of the rate. Of the eight important design dimensions for demand charges (some of which differ from time-based rates), four are likely to be particularly influential:
• The Cost Components & Allocation directly determine the magnitude of the demand charge price. Approaches range from including only customer-specific costs (e.g., service transformer) to including all costs associated with system infrastructure built to meet peak demand (e.g., including marginal generation and transmission capacity). The magnitude of the price will impact both peak consumption and customer acceptance, depending on whether customers are able to change behavior in response to the rate.
• Peak Coincidence can provide a more-targeted price signal, where charges coincident with system peak may help customers understand when to reduce their demand. In contrast, non-coincident charges are assessed against customer demand at any time, regardless of whether non-coincident demand affects system costs.
• A Ratchet Mechanism can help stabilize utility revenue by locking in a floor at a certain level for the customer’s demand bill, but the mechanism may remove customers’ incentive to reduce peak load, depending on how the ratchet is designed. • Enabling Technology may be the most important determinant of whether customers actually respond to a demand charge price signal. It is possible that sufficiently educated customers will respond by reducing peak demand, but technology that automates their response will reduce the possibility of customers not changing their behavior due to confusion about the rate.
• Specific design choices are key to the efficacy of any time-based or demand charge rate. In particular, the accuracy of the price signal (e.g., cost components and allocation) and the ability for customers to respond (e.g., peak period duration or a ratchet mechanism) are critical design choices.
• In theory, it may be possible to achieve similar objectives using either time-based rates or demand charges, but this remains unproven. Proposals often state similar objectives, including recovering costs while sending price signals that better reflect the drivers of those costs. However, it is unclear whether the two rate designs send equally effective price signals—more evidence on the impacts of demand charges is needed.
• Regulators and utilities considering these alternative rates should incorporate identified best-practice design principles. Evidence shows effective time-based rates—particularly time-of-use rates—can be developed and widely deployed using design choices described in this report. While there is insufficient evidence on the impacts of demand charges, demonstration and evaluation projects can be implemented to gain experience.
• Improved mass-market rates for consumption are necessary but not sufficient. Ongoing attention is also needed to develop improved pricing structures and compensation mechanisms that fairly represent the benefits and costs of distributed generation and other distributed energy resources. Although this report focuses exclusively on rates for consumption, a more complete transformation of electricity pricing will also include accurate and fair value pricing for on-site generation and similar customer-provided grid services.
FUTURE RESEARCH NEEDS
There are significant knowledge gaps related to both time-based and demand charge rates that the industry and researchers should address. Specific topics that emerged through this work include:
• Evaluating rate impacts on total energy consumption
• Identifying the impact of demand charges on key outcomes
• Improving understanding of the relationship of rates and technology
• Clarifying methods for including and allocating cost components
Moving toward time-based or demand charge rates is an important step in the evolution of more-sophisticated rates. While near-term improvements are critical, it is also important that the industry stay focused on longer-term goals for rate design. This can include:
• Transitioning more-sophisticated rates from opt-in to default, as California is doing with time-of-use rates, and exploring opportunities to further evolve rate sophistication, such as by combining time-based and demand charge rates.
• Developing new rates that provide greater pricing granularity to better signal value and enable response, both through behavior and with technology.
• Developing new ways to manage the tension between maintaining a minimally complex customer experience and continuing to increase rate sophistication.