Litcius/Paper detail

A pole placement approach for multi‐band power system stabilizer tuning

Wesley Peres, Francisco C. R. Coelho, Junior N. N. Costa

2020International Transactions on Electrical Energy Systems28 citationsDOI

Abstract

Low-frequency electromechanical oscillations is a topic of great concern in power system operation. Undamped oscillations reduce the power transfer capacity and can lead the system to blackouts. Since the 70s, synchronous generators operate with power system stabilizers that add damping torque to oscillations through the excitation system control. These controllers can have either a conventional fixed structure, composed by stages of gain and phase compensation, or a multi-band structure (MB-PSS), composed by three bands that correspond to a specific frequency range (low, intermediate and high frequency). In the MB-PSS structure, each band consists of two branches based on differential filters (with a gain stage and lead-lag blocks). This paper presents an approach based on the Newton-Raphson method for tuning MB-PSS for power systems taking into consideration several operating conditions to ensure robustness. The approach adjusts the controller's gains to place a set of poles into a region in the complex plane with a desired damping ratio. Firstly, the method is applied to the well-known single-machine infinite bus system represented by the Heffron-Phillips model. Secondly, an application to the multimachine South-Southeastern Brazilian power system is discussed considering different operating conditions. The convergence of the proposed approach is evaluated regarding the initial conditions, the desired damping ratio, and the set of monitored poles. Linear and nonlinear time-domain simulations validate the designed controllers. Finally, it is shown that the computational effort required by the proposed approach is lower than the one required by a class of methods widely reported in the literature for MB-PSS design.

Topics & Concepts

Control theory (sociology)Robustness (evolution)Electric power systemNonlinear systemEngineeringFrequency domainPower (physics)Computer scienceControl engineeringControl (management)ChemistryArtificial intelligenceQuantum mechanicsComputer visionPhysicsGeneBiochemistryPower System Optimization and StabilityPower Systems Fault DetectionOptimal Power Flow Distribution