Parameter Estimation Techniques for Synchronous Machines
Summary
Accurate parameter estimation underpins the reliable operation, control and monitoring of synchronous machines in power systems, microgrids and renewable‐energy interfaces. Traditional methods employ standard tests such as sudden short‐circuit and no‐load saturation curves to derive equivalent circuit reactances and time constants. However, these can be invasive or destructive and often assume linear behaviour. Recent advances embrace data‐driven and adaptive strategies, combining signal processing, subspace identification and metaheuristic optimisation to capture nonlinear dynamics across a wide range of operating points. Low‐power test alternatives and real‐time in situ algorithms now enable continuous model refinement, supporting stability analysis, fault diagnosis and efficient control design for modern electrical networks.
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Parameter Estimation Techniques for Synchronous Machines publication trend
The graph below shows the total number of articles in parameter estimation techniques for synchronous machines across all publications each year (not limited to Nature Index journals).
Technical terms
Synchronous machine: An alternating‐current generator whose rotor speed is synchronized to the grid frequency.
Parameter estimation: The process of inferring model constants (e.g. reactances, time constants) from measured data.
Subspace identification: A data-driven technique that constructs state‐space models by projecting input–output measurements onto lower-dimensional subspaces.
Takagi–Sugeno fuzzy model: A rule-based system that approximates nonlinear dynamics by interpolating between local linear models weighted by membership functions.
DC-decay test: A low-power diagnostic method measuring the decay of injected direct current to determine synchronous machine equivalent circuit parameters.
Multivariate coupling: The interaction of multiple parameters or variables that influence each other, requiring simultaneous identification.
References
- A systematic approach to modeling synchronous generator using Markov parameters and Takagi–Sugeno fuzzy systems. Expert Systems with Applications (2024).
- Evaluating the Precision of the DC Decay Test Method for Characterizing Wound-Field Synchronous Machines in Power Plants. IEEE Open Access Journal of Power and Energy (2023).
- Parameter Identification of Synchronous Condenser and Its Excitation System Considering Multivariate Coupling and Symmetry Characteristic. Symmetry (2024).
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