Performance and Reliability Foresight/SRP/Bolster

This page hosts all detailed analysis performed for the Bolster battery energy storage system.

Historical Operation

System Level

Figure 1. Use this figure to view operational data from any time period. The figure dynamically adjusts the displayed resolution depending on the number of days viewed. To see the native 10 second resolution view a single day of data.

Megapack Level

Figure 1. Use this figure to view operational data from any time period. The figure dynamically adjusts the displayed resolution depending on the number of days viewed.

Round Trip Efficiency (RTE)

For the Bolster system, RTE is being calculated in two ways:

1. Continuously, using cumulative charge and discharge energy data
2. Discretely, by focusing in on individual high-energy charge and discharge events

More details and results follow.

Cumulative RTE Calculations

Cumulative RTE calculations are derived by dividing the cumulative discharge energy profile by the cumulative charge energy profile. This provides a more practical view into energy losses associated with keeping the system operational, even when not in active use (charge or discharge). For this reason, this RTE calculation varies depending on the batteries use case. For example, a battery that is performing asset deferral (i.e. only discharges a few times per year) would generally have a lower cumulative RTE compared to an identical battery performing daily energy arbitrage. This is also why cumulative RTE is not well suited as a metric of comparison for different systems performing different duties.

Figure 2. AC Cumulative charge and discharge energy for all available data. This figure should be updated daily as new data is received.

Individual Event RTE Calculations

Calculating RTE from individual, dedicated reference performance cycles is a valuable technique for assessing and validating the system's specified round trip efficiency. A deep charge followed by an equally deep discharge at similar power levels can be used to calculate a systems RTE in a way that is typically more in line with the how vendors contractually specify round trip efficiencies. This method of RTE calculation provides results that are easier to compare across different system and technologies, though care must be taken to ensure an apt comparison.

Although the Bolster BESS is not yet performing regular reference performance test cycles, recent operation can provide a glimpse into its round trip efficiency (RTE). Because the system is performing repeated high energy charge & discharge half cycles it is possible to compare these events to get a sense of round trip efficiency. Note, special care must be taken when performing calculations as the half cycles often do not start and end at the same state of charge.

To arrive at these calculations the following steps are taken:

1. A "half cycle detection" algorithm is applied to all historical State of Charge (SoC) and AC Power data.
2. All identified charge and discharge half cycles are paired into groups
3. For each group, a common SoC boundary is identified and the half cycles are windowed on these boundaries to ensure that the same SoC ranges are being compared
4. The energy of each bounded half cycle is compared to calculate the RTE

Figure 3 shows the half cycles grouped together. Hover over each charge / discharge group to see the round trip efficiency calculation and SoC Range details.

Figure 3. A look at past charge and discharge half cycles which are grouped together to calculate RTE. This figure is not automatically updated and exists simply to demonstrate the half cycle grouping algorithm used to calculate RTE below. Please email Joe Thompson (jthompson@epri.com) to request a figure update.

Figure 4. The RTE events from Figure 3 shown vs time (left) and average ambient temperature (right). This figure should be updated daily as new data is received. Please email Joe Thompson (jthompson@epri.com) with any questions or to request a figure update.

Unavailability Analysis

Figure 5. Unavailability analysis at the system and individual Megapack level.