Optimization Years

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Optimization years are years of timeseries data (whether user-provided or DER-VET-generated) for which DER-VET will solve an optimization problem. No unique optimization problem will be solved for any other year between the start year and end year. Instead, financial results will be interpolated between optimization years or extrapolated beyond the last optimization year.

In addition to the optimization years specified by the user in the "optimization years" model parameter input, DER-VET will also solve for additional years as needed, following the guidelines below. Additional optimization years will show up in the results as more years of time series results.


When the deferral service is active and the deferral fails during the analysis horizon, two additional optimization years will be triggered, one on the last year the deferral succeeds and one in the next year. This ensures the effect of the decreasing headroom in the overloaded asset is captured in the value calculations and that the freedom to operate without constraint after the traditional upgrade is triggered is captured as well.

Equipment Failure

Whenever a piece of equipment reaches its end of life and is not replaced, an optimization year will be triggered in the first year after the failure so that the new DER mix is represented from that year on.

New Equipment

If a DER is added to the DER mix in the middle of the analysis window, an optimization year will be triggered to capture its inclusion.

Degraded Equipment Replaced

Energy storage systems that are replaceable and for which degradation is turned on will trigger two optimization years - one in the last year before replacement and one in the year after replacement (replacement is assumed to happen at the new year) unless they are replaced at the end of the analysis window. This will capture that degradation will decrease the storage system's value over time.

Best Practices

First and Last Year

It is usually best to explicitly optimize for the first year in the analysis window and the last year in the analysis window. This requires time series data for both years, which should reflect any changes in loads, market prices, etc. expected over the analysis window.