2021 · 16 citations · 11 references
EngineeringSystems EngineeringEnergy SystemsRenewable Energy SystemsSystem DynamicsMicrogridsPower Grid AnalysisPower System StabilitySmart Grid SystemsState EstimationSystem IdentificationDynamic System IdentificationEnergy Storage System ModelingMoving Horizon EstimationPower System IntegrationPower System OperationSystem Stability AnalysisWhite Noise
This paper investigates the design of low-level probing signals for accurate estimation of inertia and damping constants in microgrids. Increasing utilization of renewable energy sources and their different dynamics has created unknowns in time-varying system inertia and damping constants. Thus, it is difficult to know these parameters at any given time in converter-dominated microgrids. This paper describes the design characteristics, considerations, methodology, and accuracy level of different probing signals in determining unknown parameters of a system. The main goal of this paper is to find an effective probing signal with a simple implementation and minimal impacts on power system operation. The test-case model in this paper analyzes nonintrusive excitation signals to perturb a power system model (i.e., square wave, multisine wave, filtered white Gaussian noise, and pseudo-random binary sequence). A moving horizon estimation (MHE)-based approach is then implemented in an energy storage system (ESS) in MATLAB/Simulink for estimation of inertia and damping constants of a system based on frequency measurements from a local phase-locked-loop (PLL). The accuracy of parameter estimates alters depending on the chosen probing signal; when estimating inertia and damping constants using MHE with the different probing signals, square waves yielded the lowest error.
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Foundations and Challenges of Low-Inertia Systems (Invited Paper)
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Estimation of Power System Inertia From Ambient Wide Area Measurements
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