JuliaGrid: An Open-Source Julia-Based Framework for Power System State Estimation

2025-02-25

AI Summary

To address computational inefficiency and algorithmic coupling challenges in state estimation (SE) for large-scale power systems, this paper introduces JuliaGrid—a full-stack, open-source SE framework implemented in Julia. JuliaGrid unifies key SE functionalities—including observability analysis, weighted least squares (WLS), least absolute value (LAV) estimation, bad data detection, and phasor measurement unit (PMU) data integration—while deeply coupling Newton–Raphson power flow and interior-point optimal power flow solvers to enable closed-loop simulation. Evaluated on realistic test systems with 10,000–70,000 buses, JuliaGrid demonstrates superior convergence robustness and runtime performance compared to leading open-source SE tools. It achieves high accuracy, real-time capability, and cross-platform scalability without compromising numerical fidelity. By providing a high-performance, modular, and reusable SE infrastructure, JuliaGrid advances situational awareness for modern large-scale power grids.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Sampling/Simulation-based Search
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Modern electric power systems have an increasingly complex structure due to rise in power demand and integration of diverse energy sources. Monitoring these large-scale systems, which relies on efficient state estimation (SE), represents a challenging computational task and requires efficient simulation tools for power system steady-state analyses. Motivated by this observation, we propose JuliaGrid, an open-source framework written in the Julia programming language, designed for high performance execution across multiple platforms. The framework implements observability analysis, weighted least-squares and least-absolute value estimators, bad data analysis, and various algorithms related to phasor measurements. To complete power system analysis, the framework includes power flow and optimal power flow, enabling measurement generation for the SE routines. Leveraging computationally efficient algorithms, JuliaGrid solves large-scale systems across all SE routines with competitive execution times compared to other open-source frameworks. These capabilities are validated through simulations on power systems with 10000, 20000 and 70000 buses.

Problem

• Develops JuliaGrid for power system state estimation
• Ensures high performance across multiple platforms
• Validates with large-scale power system simulations

Innovation

• Julia-based open-source framework
• Implements weighted least-squares estimators
• Supports large-scale power systems