# Characterization of a Fast Battery Energy Storage System for Primary Frequency Response

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## Abstract

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## 1. Introduction

## 2. Materials and Methods

- The gain (G) in MW/Hz, is equivalent to the slopes of the lines between Pts. 1 and 2, and Pts. 3 and 4. Gains of 20 MW/Hz and 30 MW/Hz were tested. The original test plan included a gain of 40 MW/Hz, but it was found that the excessive cycling caused the temperature of the battery modules to increase to undesirable levels when this setting was used.
- The deadband (DB) is the magnitude of the frequency change around 60 Hz for which the BESS does not respond to fluctuations in frequency. Deadband widths of 0 mHz, 10 mHz, and 20 mHz were tested (Pt 3 to Pt 2).

## 3. Results

## 4. Discussion and Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**A simplified single line diagram of the Hawaii island battery energy storage systems (BESS) highlighting metering units.

**Figure 2.**The frequency-Watt curve used to adjust the frequency response characteristics of the BESS.

**Figure 3.**BESS power (

**top**) and frequency (

**bottom**) from representative 200-min experiment conducted on 15 March 2013. BESS parameters: gain = 30 MW/Hz, and deadband = 0 Hz. The results shown here were from an early experiment. In subsequent experiments, when we tried to isolate the frequency variability to wind generation (not solar), the start time was 6 pm.

**Figure 4.**Methodology to determine the frequency variability metric. The red line shows grid frequency from one 20-min period. Small numbers above graph represent standard deviation of each one-minute window. The mean of those standard deviations (in this case, 7.5 mHz) is used to characterize the entire 20-min period.

**Figure 5.**Representative results for a 200-min experiment from 9-April 2015.

**Top**: This is a time series of the BESS power output;

**Middle**: shows the grid frequency;

**Bottom**: the running standard deviations over one-minute (lines) along with the frequency variability metric for the entire 20-min period (dots).

**Figure 6.**

**Top**: A plot of the frequency variability metric for 20-min periods when the BESS was ON, versus adjacent 20-min periods when the BESS was OFF, from multiple experiments using the (0 MW/Hz, 0 mHz) (red dots) and (20 MW/Hz, 20 mHz) (blue dots) parameter sets.

**Bottom**: A plot of the energy throughput in kW-H for each 20-min period when the BESS was ON, versus the background grid frequency variability of the adjacent 20-min period with the BESS OFF.

**Figure 7.**

**Top Left**: Grid frequency variability results for a gain of 30 MW/Hz with the magenta lines and dots showing results for a deadband of 20 mHz and the cyan lines and dots showing results for a deadband of 10 mHz.

**Bottom Left**: Energy throughput results for the same two cases shown immediately above.

**Top Right**: Grid frequency variability results for a gain of 20 MW/Hz with the gray lines and dots showing results for a deadband of 10 mHz and the purple lines and dots showing results for a deadband of 0 mHz.

**Bottom Right**: Energy throughput results for the same two cases shown immediately above.

**Figure 8.**A diagram of the effects of increasing deadband and increasing gain on the ability of the BESS to reduce grid frequency variability (top plots of Figure 6 and Figure 7). The orange line represents a reference parameter set, the green line represents the effect of increasing the deadband only, and the blue line represents the effect of increasing the gain only. The deadband determines the minimum frequency values to which the BESS responds; for frequency values below the deadband the BESS has no effect (green). At high frequency variability, a larger proportion of frequency values lie outside the deadband, so its influence is weaker, and the BESS effectiveness is determined by the gain setting (blue).

**Table 1.**Top: The average percent reduction in frequency variability and Bottom: Energy throughput of the BESS under different control algorithm parameter sets and for Low (12 mHz), Medium (16 mHz), and High (20 mHz) background frequency variability regimes. “G” is short-hand for Gain, while “DB” stands for Dead-Band. † and * denote exceptional results that will be discussed further in the following paragraph.

Low Variability | Medium Variability | High Variability | ||||
---|---|---|---|---|---|---|

Percent Frequency Variability Reduction (Effectiveness) | ||||||

Percept Frequency Variability | G = 20 | G = 30 | G = 20 | G = 30 | G = 20 | G = 30 |

DB = 0 | 32.4 * | 36.1 | 39.9 * | 42.7 | 44.3 * | 46.6 |

DB = 10 | 15.9 | 29.3 | 29.0 | 38.9 | 36.8 | 44.6 |

DB = 20 | 13.7 | 18.6† | 21.7 | 32.6† | 26.4 | 41.0† |

Energy Throughput (Usage) | ||||||

Energy Throughput | G = 20 | G = 30 | G = 20 | G = 30 | G = 20 | G = 30 |

DB = 0 | 50.1 * | 74.7 | 60.7 * | 93.0 | 71.3 * | 111.3 |

DB = 10 | 43.3 | 50.0 | 53.0 | 69.4 | 62.7 | 88.9 |

DB = 20 | 28.0 | 35.9† | 38.4 | 41.6† | 48.8 | 47.3† |

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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**MDPI and ACS Style**

Stein, K.; Tun, M.; Matsuura, M.; Rocheleau, R.
Characterization of a Fast Battery Energy Storage System for Primary Frequency Response. *Energies* **2018**, *11*, 3358.
https://doi.org/10.3390/en11123358

**AMA Style**

Stein K, Tun M, Matsuura M, Rocheleau R.
Characterization of a Fast Battery Energy Storage System for Primary Frequency Response. *Energies*. 2018; 11(12):3358.
https://doi.org/10.3390/en11123358

**Chicago/Turabian Style**

Stein, Karl, Moe Tun, Marc Matsuura, and Richard Rocheleau.
2018. "Characterization of a Fast Battery Energy Storage System for Primary Frequency Response" *Energies* 11, no. 12: 3358.
https://doi.org/10.3390/en11123358