Distributed Generation and Distributed Energy Resources Cost Estimation Trends Evaluated

By April 5, 2018 No Comments

A February 2018 Pacific Northwest National Labs (PNNL) white paper provides helpful perspective on factors to consider when utilities evaluate the economics of distributed generation (DG) and associated analytics challenges.


Source:  “Distributed Generation Valuation and Compensation.”  Page 35

It also includes a detailed review of the approach across a set of different states (Arizona, California, California, Hawaii, Indiana, Maine, Minnesota, Mississippi, New Jersey, New York, and Oregon).

An important early step in performing valuations, according to the report, is to survey the different value components and their associated costs and benefits that could be used as valuation building blocks.  Examples of valuation building blocks include avoided costs associated with fuel, generation capacity, transmission capacity, reserve capacity, distribution capacity, fixed and variable operations, and maintenance and environmental compliance and/or impacts.

While these building blocks are often present across different evaluations, the report points out that utilities and stakeholders can have different interpretations of how key elements should be calculated.  In addition, in some states the objective of standardized calculators and methods is to reduce ambiguity and inconsistencies in how valuations are performed.

The report also states that certain value elements “are difficult or impossible to quantify and most efforts to establish workable value of solar or value of distributed energy resource tariffs are emerging and nascent,” adding that “assessing locational and temporal value of distributed generation and applying that in compensation schemes is a new and emerging field of study being explored by a handful of research organizations and advanced states and utilities.”

Of additional interest are some of the comparisons provided by the report between various states:

  • The most advanced states, such as California, are using demonstration projects to test valuation and compensation methodologies or are applying valuation and compensation strategies to a subset of customer projects, such as for community solar projects (e.g., Oregon and New York), before rolling out programs to the full customer base.
  • A variety of states are moving away from full net metering, in many cases substituting avoided cost rates. In some cases, to account for extra value such as societal benefits beyond direct utility avoided cost, so called “adders” are used, often involving a fixed addition percentage being added, in lieu of full retail rate compensation, instead of pursuing valuation of distributed energy resource approaches.
  • For example, in Indiana a 25% adder is applied to average wholesale electricity prices and in Mississippi a 25 cents/kWh adder is applied to avoided cost rates. These adders appear to have been established through policy directives rather than comprehensive cost of service valuations.
  • The report also discusses the controversial VOST (Value of Solar Tariff) method, for which Minnesota is an early adopter. As of the time of the report, its authors stated that “no IOUs have implemented a VOST at this time.” (See chart below).
Minnesota Value of Solar Calculation Table: LBNL Report Page 12

Analytics Will be Needed to Even the Score

Given the numerous ways in which goals for DG programs vary, context-sensitivity will continue to drive different valuations. But whether the focus is the customer, the utility, or society, DG markets will continue to evolve dynamically, as they have ever since the big regulatory push associated with enactment of the Public Utility Regulatory Policies Act (PURPA) in 1978, and subsequent Net Energy Metering (NEM) and related programs.

Advanced analytics is playing an increasing role in helping to drive market efficiencies, to ensure valuations keep pace with changing ways in which utilities and stakeholders derive wider-ranging benefits and account for associated costs equitably.

They say sunlight is the best disinfectant.  Utility planners and regulators and various customer and third-party advocates all benefit when avoided cost and other evaluative model’s design goes hand in hand with model transparency.  Such transparency is vital not just to optimally capture the full range of values which DG brings different stakeholders, but to ensure communication of such value adheres to standards that help ensure clarity.

Ideally, advanced analytics capabilities will play a role akin to the scales held by the blind statue of justice.

For the most advanced states, such as California, very sophisticated dynamic modeling and analytical techniques for forecasting have replaced earlier linear approaches.  The ongoing efficiency improvements of these and other DG markets means go/no-go decisions will be made more clearly, to the benefit or detriment of specific traditional or distributed forms of generation.  And such modeling efficiency also will mean less energy will be wasted in public debates and expensive regulatory proceedings where the focus is on avoiding penalizing customers moving forward with DG for any cross-subsidizing sufficiently sizeable to be of concern.

The full LBNL report is at this link: “Distributed Generation Valuation and Compensation.”