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DERs-Aided Blackstart and Load Restoration Framework for Distribution Systems Considering Synchronization and Frequency Security Constraints

Salish Maharjan, Cong Bai, Han Wang, Yiyun Yao, Fei Ding, Zhaoyu Wang

Abstract

Extreme weather events have led to long-duration outages in the distribution system (DS), necessitating novel approaches to blackstart and restore the system. Existing blackstart solutions utilize blackstart units to establish multiple microgrids, sequentially energize non-blackstart units, and restore loads. However, these approaches often result in isolated microgrids. In DER-aided blackstart, the continuous operation of these microgrids is uncertain due to the finite energy capacity of commonly used blackstart units, such as battery energy storage (BES)-based grid-forming inverters (GFMIs). To address this issue, this article proposes a holistic blackstart and restoration framework that incorporates synchronization between microgrids and the entire DS with the transmission grid (TG). To support synchronization, we leveraged virtual synchronous generator-based control for GFMIs to estimate their frequency response to load pick-up events using only initial/final quasi-steady-state points. Subsequently, a synchronization switching condition was developed to model synchronizing switches, aligning them seamlessly with a linearized branch flow problem. Finally, we designed a bottom-up blackstart and restoration framework that considers the switching structure of the DS, energizing/synchronizing switches, DERs with grid-following inverters, and BES-based GFMIs with frequency security constraints. The proposed framework is validated in IEEE-123-bus system, considering cases with two and four GFMIs under various TG recovery instants.

DERs-Aided Blackstart and Load Restoration Framework for Distribution Systems Considering Synchronization and Frequency Security Constraints

Abstract

Extreme weather events have led to long-duration outages in the distribution system (DS), necessitating novel approaches to blackstart and restore the system. Existing blackstart solutions utilize blackstart units to establish multiple microgrids, sequentially energize non-blackstart units, and restore loads. However, these approaches often result in isolated microgrids. In DER-aided blackstart, the continuous operation of these microgrids is uncertain due to the finite energy capacity of commonly used blackstart units, such as battery energy storage (BES)-based grid-forming inverters (GFMIs). To address this issue, this article proposes a holistic blackstart and restoration framework that incorporates synchronization between microgrids and the entire DS with the transmission grid (TG). To support synchronization, we leveraged virtual synchronous generator-based control for GFMIs to estimate their frequency response to load pick-up events using only initial/final quasi-steady-state points. Subsequently, a synchronization switching condition was developed to model synchronizing switches, aligning them seamlessly with a linearized branch flow problem. Finally, we designed a bottom-up blackstart and restoration framework that considers the switching structure of the DS, energizing/synchronizing switches, DERs with grid-following inverters, and BES-based GFMIs with frequency security constraints. The proposed framework is validated in IEEE-123-bus system, considering cases with two and four GFMIs under various TG recovery instants.

Paper Structure

This paper contains 32 sections, 31 equations, 17 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Holistic formulation of blackstart and load restoration process
  3. Modeling BES-based grid-forming inverter (GFMI)
  4. Constraining dynamic frequency responses to comply with security limits:
  5. Modeling synchronization of GFMIs
  6. Modeling grid-following PV inverters
  7. Modeling cold load pick up (CLPU)
  8. Modeling switching structure of distribution system
  9. Modeling switches
  10. Energizing switch (ESW)
  11. Synchronizing switch (SSW)
  12. Bus blocks energizing constraints
  13. Linear power flow model adaptive to network topology
  14. Modeling transmission grid outage and recovery
  15. Dynamic radiality constraint driven synchronization
  16. ...and 17 more sections

Figures (17)

  • Figure 1: Example DS illustrating bus-blocks, switches, and blackstart units.
  • Figure 2: (a) Control diagram and (b) dynamic frequency response of a VSG.
  • Figure 3: Energization of grid-following DERs such as PV.
  • Figure 4: Cold load pickup model after an extended outage.
  • Figure 5: Possible switch states while blackstarting.
  • ...and 12 more figures