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Title: AI-Based Faster-Than-Real-Time Stability Assessment of Large Power Systems with Applications on WECC System

Journal Article · · Energies
DOI:https://doi.org/10.3390/en16031401· OSTI ID:2000251
 [1];  [1];  [1];  [1];  [1];  [2];  [3]
  1. University of Tennessee, Knoxville, TN (United States)
  2. University of Tennessee, Knoxville, TN (United States) ; Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
  3. Stronghold Resource Partners, Dallas, TX (United States)

Achieving clean energy goals will require significant advances in regard to addressing the computational needs for next-generation renewable-dominated power grids. One critical obstacle that lies in the way of transitioning today’s power grid to a renewable-dominated power grid is the lack of a faster-than-real-time stability assessment technology for operating a fast-changing power grid. This paper proposes an artificial intelligence (AI) -based method that predicts the system’s stability margin information (e.g., the frequency nadir in the frequency stability assessment and the critical clearing time (CCT) value in the transient stability assessment) directly from the system operating conditions without performing the conventional time-consuming time-domain simulations over detailed dynamic models. Since the AI method shifts the majority of the computational burden to offline training, the online evaluation is extremely fast. This paper has tested the AI-based stability assessment method using multiple dispatch cases that are converted and tuned from actual dispatch cases of the Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. The results show that the AI-based method could accurately predict the stability margin of such a large power system in less than 0.2 milliseconds using the offline-trained AI agent. Therefore, the proposed method has great potential to achieve faster-than-real-time stability assessment for practical large power systems while preserving sufficient accuracy.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Electricity (OE)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
2000251
Journal Information:
Energies, Vol. 16, Issue 3; ISSN 1996-1073
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

References (24)

Resilient Adaptive Parallel sImulator for griD (RAPID): An Open Source Power System Simulation Toolbox journal January 2022
Disturbance location determination based on electromechanical wave propagation in FNET/GridEye: a distribution‐level wide‐area measurement system journal June 2017
Design of a Real-Time Security Assessment Tool for Situational Awareness Enhancement in Modern Power Systems journal May 2010
Parareal in Time for Fast Power System Dynamic Simulations journal May 2016
Transient Stability Prediction of Power Systems Using Post-disturbance Rotor Angle Trajectory Cluster Features journal September 2016
Support Vector Machines for Transient Stability Analysis of Large-Scale Power Systems journal May 2004
A Time–Power Series-Based Semi-Analytical Approach for Power System Simulation journal March 2019
U.S. Eastern Interconnection (EI) Model Reductions Using a Measurement-based Approach conference April 2018
A Reliable Intelligent System for Real-Time Dynamic Security Assessment of Power Systems journal August 2012
Oscillation mode identification based on wide-area ambient measurements using multivariate empirical mode decomposition journal May 2016
Power System Dynamic Simulations Using a Parallel Two-Level Schur-Complement Decomposition journal September 2016
Implementation of a Massively Parallel Dynamic Security Assessment Platform for Large-Scale Grids journal May 2017
Power System Modelling and Scripting book August 2010
Adaptive Nonlinear Model Reduction for Fast Power System Simulation journal November 2018
Comparative Implementation of High Performance Computing for Power System Dynamic Simulations journal May 2017
Artificial Intelligence Techniques for Power System Transient Stability Assessment journal January 2022
Non-Invasive Identification of Inertia Distribution Change in High Renewable Systems Using Distribution Level PMU journal January 2018
Parallel-in-Time Power System Simulation Using a Differential Transformation Based Adaptive Parareal Method journal January 2023
Instantaneous Relaxation-Based Real-Time Transient Stability Simulation journal August 2009
Power System Time Domain Simulation Using a Differential Transformation Method journal September 2019
A Review of Machine Learning Approaches to Power System Security and Stability journal January 2020
Two-Stage Parallel Waveform Relaxation Method for Large-Scale Power System Transient Stability Simulation journal January 2016
Parallel Transient Stability Simulation Based on Multi-Area Thévenin Equivalents journal May 2017
Power System Simulation Using the Multistage Adomian Decomposition Method journal January 2017

Figures / Tables (14)