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, 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 state estimation routines. Leveraging computationally efficient algorithms, JuliaGrid solves large-scale systems across all methods, offering competitive performance compared to other open-source tools. It is specifically designed for quasi-steady-state analysis, with automatic detection and reuse of computed data to boost performance. These capabilities are validated on systems with 10000, 20000 and 70000 buses.

翻译：现代电力系统因电力需求增长及多样化能源的接入而结构日益复杂。对这些大规模系统的监测依赖于高效的状态估计，是一项具有挑战性的计算任务，并需要高效的仿真工具进行电力系统稳态分析。基于此观察，我们提出了JuliaGrid——一个用Julia编程语言编写的开源框架，专为跨平台高性能执行而设计。该框架实现了可观性分析、加权最小二乘与最小绝对值估计器、不良数据分析和与相量测量相关的多种算法。为完善电力系统分析，框架还包含潮流计算与最优潮流计算，能够为状态估计程序生成测量数据。凭借计算高效的算法，JuliaGrid能够采用所有方法求解大规模系统，相比其他开源工具具有竞争优势。该框架专为准稳态分析设计，通过自动检测与复用计算数据以提升性能。这些功能已在包含10000、20000和70000个节点的系统上得到验证。