QuESt’s approach is very similar to DER-VET’s for cases like this, so should calculate near-identical results to DER-VET when given the same inputs. QuESt also achieved similar results, though QuESt’s inability to accept the full tariff without errors results in somewhat higher bill savings. In other scenarios with long-duration storage or in cases with unusual load profiles, there might be a larger difference between the two tools. Because most of the benefit from the storage comes from demand charges and there are no constraints on how the storage can be used to shift energy during normal operation, DER-CAM’s approach does not impact the results very much. One of the design days in DER-CAM is the peak day in each month, which will very likely set the demand charge before and after storage. This tariff is a time of use (TOU) tariff that defines three periods each for summer and winter.ĭER-VET and DER-CAM realize extremely similar results despite their different approaches – DER-VET uses a full year of data and DER-CAM uses 3 days per month. No storage valuation tool can model every tariff in existence, but all the tools selected for this comparison support the relatively simple but high-cost TOU-8 tariff. This comparison uses the TOU-8 Option D (<2kV) for 2020 from Southern California Edison (SCE). Many of the differences between the tools will not be highlighted by this use case, so future work will involve expanding the set of comparison cases to provide a comprehensive exploration of quantitative results for standard use cases across valuation tools. While none of these tools are perfectly comparable, the use case selected for this initial comparison is fully covered by all the selected tools. This section selects EPRI’s DER-VET, Sandia National Laboratory’s QuESt, The National Renewable Energy Laboratory’s System Advisor Model, The National Renewable Energy Laboratory’s REopt Lite, and Lawrence Berkeley National Laboratory’s DER-CAM tools for quantitative comparison based on their status as free to use models with somewhat overlapping capabilities. The provided converter spreadsheet was used to extract the monthly average weekday, average weekend, and peak days to use in DER-CAM. This site exhibits very little seasonal variation in the scale and timing of its electricity use. The tariff specifies that demand charges are calculated based on 15-minute data, but so that all tools could be compared (most do not go below hourly resolution), hourly data is used for all. Hourly interval data is used to represent the customer. The differences between the models should come out in the expected demand and energy charge savings as a result of operating the storage system and the associated operational profile for the batteries. This customer’s electric demand profile will be consistent across tools as will the size of the storage system and the customer’s tariff. The use case used to compare between tools is a simple customer side of the meter case where a fixed-size battery energy storage system is used to reduce the energy and demand charges experienced by a large commercial customer in Southern California. This comparison will rely on the results from a single use case, which will be expanded in future publications to span the breadth of energy storage use cases more fully.
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