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.