Time-related Considerations
What is the analysis period in which the impact of DPV is being evaluated?
First and foremost, having a clear and well-defined analysis period is critical to any DPV analysis. Analysis documentation should explicitly state the timeframe being considered, so that the audience can understand the nature of the exact question being asked, and importantly whether there are any key caveats or qualifications (e.g., “This DPV analysis does not examine impacts beyond the first three years of DPV deployment.”).
As a simple example, an Individual Project Generation and Project Economics analysis could be conducted to ask:
- 1-Day Analysis Period: How much electricity will my DPV system inject onto the grid on an average day relative to my consumption?
- 1-Month Analysis Period: How much electricity will my DPV system generate in June?
- 1-Year Analysis Period: What will my bill savings be in the next calendar year?
- 30-Year Analysis Period: How many years will it be until my bill savings pay back my initial investment?
It is also important to note that different DPV costs and benefits can accrue over different timeframes. For instance, the value to a power system of deferred generation and transmission investments due to DPV deployment may take several years to accrue (assuming this value stream is tracked and quantified by utilities/regulators at all), whereas utility sales reductions may occur immediately. In general, short-term costs may be offset by longer-term benefits, or vice versa. Some impacts can be cumulative over time, such as revenue reductions accruing between a rate case that occurs every three years.
Does the analysis examine a period in the past, the present or the future?
All analysis questions, either implicitly or explicitly, are formed with (time) direction in mind.
| Direction | Analysis Type | Description |
|---|---|---|
| Past | Program Evaluation | Ex-post (or backward-looking) analyses evaluate impacts of existing programs. They are often more useful to inform adjustments to policies in the short-term. |
| Future | Projections and Forecasts | Ex-ante (or forward-looking) analyses evaluate the potential impact in the future; they can be used inform medium- and long-term planning and policy design/pathway discussions. They are also commonly used while performing cashflow analyses of projects. |
| Present | “What if X Today?” | At times, it may be helpful to create an analysis storyline around a current-day scenario, such as, “If we put 500 megawatts (MW) of DPV on our network today, would the current fleet be able to balance supply and demand?” |
| Hybrid | Multiple | Informing current-day and/or forward-looking analyses with historical experiences and data has proven to be a good approach. |
What is the time resolution of the analysis?
For DPV, the time resolution of data can be of particular importance, especially when attempting to model individual DPV customers and how various changes to policy impact customer economics and/or utility sales and revenues. More granular data makes for more robust analysis, and they can always be aggregated upward; however, the more granular the data, the more effort the analysis can require.
Commonly, customer demand data are available on a monthly basis, as this coincides with the timing of utility billing cycles. However, only having monthly data may limit one’s ability to accurately answer questions below that time resolution, such as how much energy a DPV system will inject into the grid versus be consumed on-site, which requires hourly or sub-hourly data to accurately answer and is an important question for distribution grid planning and certain rate and revenue impact analysis studies.
Picking an appropriate analysis method depends on four primary factors: