Controller design with model identification approach in wide area power system

Abstract

Using wide area monitoring systems (WAMS) offers a possibility for an integrated measurement-based and model-based control, which suits to the operation of large electric power system (EPS), along with online analysis. This study presents studies on fixed-order controller design through model identification approach with use of synchronous measurement data. Firstly, in the study, the coherent generator in each area of large EPS is determined by the mutual information theory. Then, state-space two-input two-output model is identified for the generator that has highest participation factor and thus referred as coherent generator. The model identification algorithms; least-square, instrumental variable and subspace state-space based generalised Poisson moment function are used. Next, WAMS level model is identified between the input controllable variable and speed deviation difference of coherent generator of each area. Finally, a local controller (decentralised) in each coherent area and a centralised controller at WAMS level between two coherent areas are designed by optimisation of the several design functions; H∞ norm, H2 norm, spectral abscissa and complex stability radius, as much as possible. These controllers feed supplementary control signal in addition to one fed by local conventionally tuned power system stabiliser. The centralised controller at WAMS level is demonstrated to stabilise the speed deviations of each generator between any two areas in the large EPS. The study is investigated with different input signal variables; ΔVref, ΔPm excited by different pattern of disturbances.