Sales Reduction and Net Revenue Impacts
Costs, Benefits, and Analysis Timeframes
Net revenue impact analyses are inherently a netting calculation—a simple linear summation of specific costs and benefits associated with DPV that are typically quantified on an annual basis. The exact utility costs and benefits quantified in these analyses depend on the type of utility entity being examined, but typically include:
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Lost utility wholesale and/or retail electricity sales
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Additional required utility expenditures to purchase DPV grid injections
Benefits
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Reductions in bulk generation costs and/or wholesale electricity purchase costs
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Avoided network losses resulting in incremental ‘B1’ benefit
These analyses tend to be forward-looking in nature, quantifying expected utility revenue impacts for single- or multiyear periods of DPV deployment, often in alignment with ratemaking periods. Under certain circumstances, these methods can also be employed to evaluate the utility revenue impacts of existing DPV programs.
Importantly, ‘Net Revenue Impact Analyses’ are not designed to provide insights on how much revenue a utility may ultimately collect in the medium- to long-term, particularly in the event that tariffs are adjusted to reflect the financial impact of DPV and “true up” net revenue losses. Instead, they narrowly focus on quantifying changes in short-term utility operational expenses and revenue collection, which occur before tariffs might be adjusted.
Similarly, these analyses do not account for medium- to long-term investment-related utility financial impacts, such as changes in distribution network investments or the value of DPV to defer utility-scale generation investments. As they do not cover utility investment-related changes, these analyses cannot provide a complete picture of changes in utility earning opportunities, returns on equity, and utility profitability more broadly. However, quantifying changes in short-term operational expenses and revenue collection can still prove extremely useful for bounding concerns and shaping policy decisions.
Stakeholder Perspectives and DPV Behavior
Different types of utility entities experience distinct costs and benefits associated with DPV. Thus, the exact nature of DPV revenue impacts are unique, depending on the type of utility stakeholder being examined. In general, there are three categories of utility stakeholders that experience distinct DPV revenue impacts:
- Distribution Utility (DU) – A company that exclusively provides low-voltage distribution and retailing (i.e., metering and administration services) of electricity to retail electricity customers, including DPV customers.
- Electric Generation Utility (EGU)– A company that generates and sells wholesale electricity directly to DUs and larger (oftentimes industrial) customers.
- Vertically Integrated Utility (VIU) – A company that own all aspects of the electricity supply chain, providing retail, distribution, transmission, and generation services. Some VIUs may also sell electricity to DUs, which effectively turns them into an EGU for the purposes of these analyses.
Utility revenue impacts may also be distinguished based on the behavior of DPV systems. There are two key behaviors that a DPV system can exhibit that can have distinct financial impacts, depending on the stakeholder:
- Self-consumption of DPV generation: When DPV electricity is used to meet on-site load. Self-consumption allows DPV system owners to reduce or eliminate the variable utility charge portion of their electricity bill, resulting in a bill reduction for the customer, and a lost sale for the utility.
- Grid injection of DPV generation: When DPV electricity is injected into a local distribution network rather than the host’s load. This results in the utility purchasing electricity from the DPV system, resulting in an additional cost for the utility and an additional benefit for the customer.
In general, these two behaviors can have a distinct financial impact on different utility stakeholders, depending on the details of the DPV customer’s metering and billing arrangements, retail electricity tariff structure, sell rate level, and crediting terms. The short-term utility revenue impacts associated with DPV can be characterized as:
| Utility Type | DPV Behavior | Utility Revenue Cost | Utility Revenue Benefit |
|---|---|---|---|
| Distribution Utility |
Self-consumption Grid injection |
Lost retail electricity sale DPV purchase |
Avoided wholesale electricity purchase Avoided distribution network losses |
| Vertically Integrated Utility |
Self-consumption Grid injection |
Lost retail electricity sale DPV obligation |
Avoided wholesale electricity generation or procurement cost Avoided distribution network losses Avoided transmission network losses |
| Electric Generation Utility |
Self-consumption Grid injection |
Lost retail electricity sale |
Avoided wholesale electricity generation or procurement cost Avoided transmission network losses |
These impacts can also be further distinguished based on the DPV metering and billing arrangement (e.g., net energy metering vs. net billing) and how exactly the utility entity being analyzed procures and/or generates wholesale electricity.
Analysis Applications and Linkages
Utilities, regulators, or energy ministries can use net revenue impact analyses to bound concerns about expected DPV financial impacts under current policy and market conditions, or in some circumstances, to characterize net revenue losses that have already occurred. Net revenue impact analyses can also be used to quantify how a particular change in regulation or policy (e.g., a shift from net energy metering to net billing) may impact utility revenue in the future.
Importantly, this analysis relies heavily on ‘Techno-economic Performance Analysis.’ In order to quantify the expected net revenue impact of a given DPV deployment scenario, assumptions must be made about who exactly is deploying DPV; thus, average or statistically representative customers must be formulated and scaled to higher levels of deployment in order to understand the broader revenue impacts of a DPV deployment scenario. This analysis is also a foundational step of ‘Tariff Impact Analysis,’ calculating short-term net revenue impacts that might be passed through to ratepayers via tariff increases.
Example Analysis Questions
Below is a nonexhaustive list of illustrative analysis questions for Net Revenue Impact Analyses.
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What was the actual net utility revenue impact of all DPV deployment in a Distribution Utility service territory between 2016 and 2018?
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What is the expected annual net revenue impact associated with 500 MW of DPV deployment by residential and commercial customers for the rate period between 2019 and 2021 for the Electric Generation Utility?
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What is the expected annual net utility revenue impact of 250 MW of DPV deployment by low-use residential customers versus high-use industrial customers for the Vertically Integrated Utility?
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What is the expected change in annual net utility revenue impacts to the Distribution Utility if new customers are shifted from Net Energy Metering with no annual net excess generation credit to Net Billing with a $0.04/kWh grid-injection sell rate beginning in 2020?
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What is the expected change in annual net utility revenue impacts for the Distribution Utility in 2022 if all DPV customers are placed on a declining block time-of-use retail electricity rate?
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How will annual DPV net revenue impacts change if the Electric Generation Utility begins selling wholesale electricity at distinct peak and off-peak tariffs?
Overview of Key Analysis Inputs, Assumptions, Outputs, and Tools
| Aspect | Description |
|---|---|
| Stakeholder Perspective | Utility |
| Key Input Data |
Prototypical Customer Data - See table on 'Individual Project Technical or Techno-Economic Analysis' page for a review of key input data required to formulate prototypical customers. Distribution and/or Transmission Loss Data - Recent utility data on average transmission losses and/or technical and nontechnical distribution losses are necessary for calculating avoided network losses. |
| Key Input Assumptions |
For All Net Revenue Impact Analyses DPV Deployment Assumptions - Each analysis scenario contains assumptions of: (1) how much DPV is being deployed; (2) a timeframe for DPV deployment within the analysis period; (3) the mix of customer types that are deploying DPV; and (4) where DPV is being deployed in the service territory. Prototypical Customer DPV System Size - The capacity (kW) of each prototypical customer's DPV system strongly influences the nature of utility revenue impacts. Prototypical Customer DPV System Performance Assumptions - The efficiency of the PV module to produce electricity, as well as the efficiency of the inverter to convert DC to AC energy, impact the technical performance of the DPV system along with several other DPV performance assumptions. Generation or Wholesale Purchase Off Set Value - The avoided utility expenditure associated with reduced bulk power generation levels or reduced wholesale electricity purchases due to DPV production. This assumption may change base on the time of DPV production, and/or evolve dynamically over multiyear periods. For Forward-looking Net Revenue Impact Analyses Annual Retail and/or Wholesale Tariff Escalation Rate - The assumed annual increase in the retail electricity tariff level can influence utility revenue impact in future years. Annual Change in Network Losses - Network losses and, in particular, distribution network losses, may reduce in a certain setting in the long-term. This change has implications for the value of avoided utility network losses. Inflation Rate - The inflation rate of the local economy can be an influential factor for utility revenue impacts over longer time periods. Changes in Generation or Wholesale Purchase Offset Value - Bulk electricity generation patterns tend to change over time and, therefore, the value of generation offset or wholesale purchase reduction value of DPV can be accounted for.
|
| Key Outputs |
Lost Utility Sales - Total financial value associated with a reduction in annual retail and/or wholesale electricity sales due to DPV. The value of lost utility sale may change dynamically with time if time-of-use tariff structures are present. Additional Utility DPV Purchase Obligation - Total additional expenditure for DU or VIU to purchase DPV electricity injected into the distribution network. The level of utility expenditure required may change dynamically with time-based if the DPV sell rate is time-variant. Avoided Utility Generation Costs or Wholesale Power Purchases - Total annual avoided utility expenditure for bulk electricity procurement due to DPV. The value of this avoided expenditure may change based on the timing of DPV production as well as the specific means of generation procurement. Total Utility Net Revenue Impact - Total annual or multiyear utility net revenue impact, summing all analyzed short-term DPV costs and benefits, in advance of any changes to retail and/or wholesale electricity tariffs. |
| Tools and Models |
System Advisor Model / PVWatt (NREL) Revenue Impact Calculations - Design of customized spreadsheet model is recommended for this element of the analysis. No known commercial or open-source models available. |
Discussion and Practical Considerations
Who can conduct this analysis? How costly and time-intensive is it to conduct?
In order to successfully conduct Net Revenue Impact Analyses, analysts must have a solid understanding of ‘Individual Project Technical and Techno-economic Analyses’ methods as well as a moderate to strong proficiency in designing spreadsheet-based financial analyses. A robust knowledge of retail tariff design and DPV metering and billing arrangements is quite important. Also, there are a variety of subtleties surrounding how utility entities generate and/or procure bulk electricity—an appreciation for these complexities can ensure a well-designed analysis. At the time of this writing, there are no existing commercial or open-source “plug-and-play” utility net revenue impact calculators; thus, customized spreadsheet design is currently a requirement. Depending on the availability of relevant data, the level complexity and time granularity of existing retail and wholesale tariffs, the number of DPV deployment scenarios examined, and an analyst’s prior experience, Net Revenue Impact Analyses can take one to three months of full-time work to complete.
What other costs and benefits can be included in these analyses?
The costs and benefits detailed in this analysis description are easily noticeable and trackable short-term utility revenue impacts of DPV deployment. Other potential “value aspects” of DPV that might be included in these analyses include, but are not limited to: program administration costs, generation capacity value, distribution capacity value, transmission capacity value, grid support value, fuel diversity value, and environmental value. When considering including other utility costs and benefits in a Net Revenue Impact Analysis, it is important to remember that the costs and benefits of DPV are not always realized immediately, and if the DPV impact under consideration is outside of the immediate-term purview of a Net Revenue Impact Analysis, it may be more effectively calculated in a separate analysis. Furthermore, while reduced electricity sales or increased utility DPV purchase obligations are easily noticed and tracked by utilities, this cannot be assumed to be the case for all DPV costs and benefits. If a particular impact may be complex for utilities to track in real life and include in ratemaking procedures (e.g., generation investment deferral value of DPV), analysts can consider excluding this aspect from the Net Revenue Impact Analysis.
What are the key challenges to getting these analyses right?
Perhaps the greatest source of complexity in executing Net Revenue Impact Analyses properly is related to the time resolution of revenue impacts. For instance, if a Distribution Utility offers time-of-use retail tariffs with a distinct schedule of peak/regular/off-peak tariffs for various customer classes, then spreadsheet tools must parse lost retail sales and DPV grid injections accordingly based on those time windows—this can be a tedious and time-consuming process but is of critical importance to ensure accuracy. This complexity is further compounded if the Distribution Utility also procures wholesale electricity under time-variant wholesale tariffs. And, similar to ‘Individual Project Technical and Techno-economic Analyses,’ adequate data availability can be a significant challenge. Sufficiently detailed customer demand data tend to be the most difficult type of data to acquire because this type of data is not always collected by utilities in developing country settings for a variety of reasons; it can often be confidential in nature yet it remains critically important to accurately characterize utility net revenue losses for each prototypical customer being analyzed.
What are some key practical tips to keep in mind?
The “energy benefit” of DPV (i.e., the reduction in electricity generation or procurement costs) is likely to be the largest magnitude DPV benefit considered in a Net Revenue Impact Analysis; analysts must take great care to quantify this benefit as accurately as possible. However, they must also understand the ‘who’ behind the accrual of this energy benefit. This means understanding not only the type of generator that is likely to reduce output at a given time of day due to DPV production, but also to what extent the utility entity in question actually benefits from this reduction of generation. At a high level, the energy benefit can accrue to different types of utilities as either:
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Reduced direct generation costs (e.g., fuel costs) from power plants owned by an EGU, VIU, or independent power producer (IPP)
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Reduced regulated wholesale electricity purchases under a wholesale tariff structure by a DU from an EGU or VIU
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Reduced contracted electricity by a DU, EGU, or VIU from an IPP
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Reduced wholesale electricity spot market purchases by a DU, EGU, or VIU.
Understanding the ‘who’ behind this energy benefit can ensure that analysis results reflect what might actually happen in a real-life scenario where DPV production is occurring. For instance, if a diesel generator owned by a VIU is expected to reduce its output due to DPV, there would be an energy benefit in the form of reduced diesel fuel use to the VIU. However, if a diesel IPP is contracted under a take-or-pay contract to the same VIU and reduces its output to accommodate DPV production, the VIU may still have to pay the IPP despite a reduction in generation; therefore, no energy benefit would accrue for the VIU.
Please also reference this question under the ‘Individual Project Technical and Techno-economic Analyses’ page for a discussion of practical tips for formulating the prototypical DPV customers that underpin Net Revenue Impact Analyses.
How can results be discussed effectively?
Context matters significantly for presenting results from net revenue impact analyses. For instance, annual net revenue losses can be particularly useful for utilities and policymakers if they are put in the context of (a) annual utility revenue collection levels and (b) information on which specific revenue impacts might be trued up during future rate cases or through interim tariff adjustments. It is also useful to present revenue impacts broken down into their key drivers (e.g., lost sales, avoided generation costs)—doing so helps to paint a more complete picture to analysis stakeholders and demonstrates the extent to which DPV benefits may offset revenue losses associated with reduced utility sales.
Example Analyses
- Quantifying Rooftop Solar Benefits: a State-Level Value of Solar Analysis for India
- Distributed Solar Utility Tariff and Revenue Impact Analysis
- Understanding the Impact of Distributed Photovoltaic Adoption on Utility Revenues and Retail Electricity Tariffs in Thailand
- The Impact of Residential Rooftop Solar PV on Municipal Finances: An Analysis of Stellenbosch
- Distributed Photovoltaic Economic and Technical Impact Analysis in the Philippines
- Distributed Photovoltaic Economic Impact Analysis in the Philippines (Webinar)
For further information, please contact Alexandra Aznar ([email protected])