Intended Application of Analysis
DPV analysis can be used to support myriad investment decisions and policy and regulatory design processes, including the design of DPV compensation mechanisms, retail electricity tariffs, policy incentives, and grid codes and equipment standards. The exact analytical method used will depend on the specific question being asked.
For example, if a residential customer is considering purchasing a DPV system, they may wish to know how to design their system to achieve the best return on investment—this question would require a DPV project economics analysis. A regulator that is considering moving forward with a DPV program may wish to know what impact the program will have on retail electricity tariffs—this question would require a ratepayer impact analysis that considers a range of representative DPV customers. In general, the intended application of the analysis to inform a specific question determines which type or types of DPV analysis are appropriate. A list of DPV analyses categories is available under DPV Analysis Types below.
Compounding this complexity are the many costs and benefits of DPV that can be analyzed, which can change with each prospective DPV customer and can change dynamically over time. While quantifying all costs and benefits may be desirable in theory, doing so in practice is a highly resource-intensive effort that involves multiple types of analysis to ask a range of interrelated but distinct questions that are contingent on assumptions that can evolve over time.
Thus, it is paramount to decide upfront which DPV costs and benefits are truly most relevant for the question being asked, as the costs and benefits being quantified will shape the analysis methodology. For instance, DPV programs require utilities to evaluate interconnection applications and augment their metering and billing procedures, which can be considered a new administrative cost. However, in practice, these costs tend to be quite small compared to the forgone revenue utilities may experience from reduced retail sales. An analyst could spend an equal amount of effort quantifying these administrative costs (in a separate analysis with distinct assumptions, data, and methods) as understanding the impact of lost sales on utility revenues, only to find that the administrative costs are “in the noise” compared to the impact of lost utility sales. Because it is impossible to quantify every DPV cost and benefit, or to do so perfectly, analysts must make pragmatic decisions about where best to focus their efforts.