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Conventional state estimation routines of electrical grids are mainly relianton dynamic models of fossil fuel-based resources. These models commonly containdifferential equations describing synchronous generator models and algebraicequations modeling power flow/balance equations. Fuel-free power systems thatare driven by inertia-less renewable energy resources will hence require newmodels and upgraded estimation routines. To that end, in this paper we proposea robust estimator for an interconnected model of power networks comprised of acomprehensive ninth order synchronous generator model, advanced powerelectronics-based models for photovoltaic (PV) power plants, constant powerloads, constant impedance loads, and motor loads. The presented state estimatordesign is based on Lyapunov stability criteria for nonlinear differentialalgebraic equation (DAE) models and is posed as a convex semi-definiteoptimization problem. Thorough simulations studies have been carried out onIEEE-39 bus test system to showcase the robustness of the proposed estimatoragainst unknown uncertainty from load demand and solar irradiance.

Robust Dynamic State Estimation of Multi-Machine Power Networks with Solar Farms and Dynamics Loads