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Understanding Regional Inertia Dynamics in CAISO from Real Grid Disturbances

Saurav Dulal, Mohammed M. Olama, Ali R. Ekti, Nils M. Stenvig, Yilu Liu

TL;DR

The paper addresses the problem of uneven inertia distribution in low-inertia grids like CAISO by introducing a measurement-based framework that estimates regional inertia from real disturbance data using FNET/GridEye. It computes RoCoF and inertia through a sliding-window approach anchored to the swing equation, and defines metrics such as Interconnection, Regional, and Local RoCoF, inertial arrival time, and the regional-to-system inertia ratio $\frac{H_{region}}{H_{intercon}}$. Applying the method to seven CAISO disturbances (2013–2024) reveals regional RoCoF up to six times the interconnection value, a mid-day inertia dip during the duck curve, and a recovery trend driven by front-of-the-meter BESS and grid-forming controls. The findings highlight the importance of region-specific inertia monitoring for planning and real-time operation as renewable penetration continues to rise, and suggest that targeted deployment of fast-frequency response resources can restore regional stability.

Abstract

The shift from synchronous generators to inverter-based resources has caused power system inertia to be unevenly distributed across power grids. As a result, certain grid regions are more vulnerable to high rate-of-change of frequency (RoCoF) during disturbances. This paper presents a measurement-based framework for estimating grid inertia in CAISO (California Independent System Operator) region using real disturbance-driven frequency data from the Frequency Monitoring Network (FNET/GridEye). By analyzing confirmed disturbances from 2013 to 2024, we identify trends in regional inertia and frequency dynamics, highlighting their relationship with renewable generation and the evolving duck curve. Regional RoCoF values were up to six times higher than interconnection-wide values, coinciding with declining inertia. Recent recovery in inertia is attributed to the increased deployment of battery energy storage systems with synthetic inertia capabilities. These findings underscore the importance of regional inertia monitoring, strategic resource planning, and adaptive operational practices to ensure grid reliability amid growing renewable integration.

Understanding Regional Inertia Dynamics in CAISO from Real Grid Disturbances

TL;DR

The paper addresses the problem of uneven inertia distribution in low-inertia grids like CAISO by introducing a measurement-based framework that estimates regional inertia from real disturbance data using FNET/GridEye. It computes RoCoF and inertia through a sliding-window approach anchored to the swing equation, and defines metrics such as Interconnection, Regional, and Local RoCoF, inertial arrival time, and the regional-to-system inertia ratio . Applying the method to seven CAISO disturbances (2013–2024) reveals regional RoCoF up to six times the interconnection value, a mid-day inertia dip during the duck curve, and a recovery trend driven by front-of-the-meter BESS and grid-forming controls. The findings highlight the importance of region-specific inertia monitoring for planning and real-time operation as renewable penetration continues to rise, and suggest that targeted deployment of fast-frequency response resources can restore regional stability.

Abstract

The shift from synchronous generators to inverter-based resources has caused power system inertia to be unevenly distributed across power grids. As a result, certain grid regions are more vulnerable to high rate-of-change of frequency (RoCoF) during disturbances. This paper presents a measurement-based framework for estimating grid inertia in CAISO (California Independent System Operator) region using real disturbance-driven frequency data from the Frequency Monitoring Network (FNET/GridEye). By analyzing confirmed disturbances from 2013 to 2024, we identify trends in regional inertia and frequency dynamics, highlighting their relationship with renewable generation and the evolving duck curve. Regional RoCoF values were up to six times higher than interconnection-wide values, coinciding with declining inertia. Recent recovery in inertia is attributed to the increased deployment of battery energy storage systems with synthetic inertia capabilities. These findings underscore the importance of regional inertia monitoring, strategic resource planning, and adaptive operational practices to ensure grid reliability amid growing renewable integration.

Paper Structure

This paper contains 15 sections, 3 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. Data Overview and CAISO Frequency Dynamics
  3. Regional Inertia Estimation Concept and Framework
  4. Regional Frequency Estimation
  5. Event Onset Detection
  6. RoCoF Computation
  7. Inertia Computation
  8. Advanced Metrics for Regional Dynamic Characterization
  9. Interconnection RoCoF
  10. Regional RoCoF
  11. Local RoCoF
  12. Inertial Support Arrival Time
  13. Regional-to-System Inertia Ratio ($H_{region}/H_{intercon}$)
  14. Results and Discussion
  15. Conclusion

Figures (5)

  • Figure 1: Geographical distribution of FDRs across the U.S. with the CAISO region highlighted for regional inertia analysis.
  • Figure 2: Frequency response of the U.S. Western Interconnection during a generation trip in CAISO.
  • Figure 3: Event-based regional inertia estimation process.
  • Figure 4: Event detection and regional RoCoF estimation for a real event occurred in CAISO.
  • Figure 5: CAISO duck curve with confirmed events marked with red dots. Curves are conceptual and reflect typical net-load patterns from 2013 to 2024 based on public CAISO and EIA data EIAduckcurve.