Single network adaptive critic design for power system stabilisers

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Single network adaptive critic design for power system stabilisers

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The recently developed single network adaptive critic (SNAC) design has been used in this study to design a power system stabiliser (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. PSS design is formulated as a discrete non-linear quadratic regulator problem. SNAC is then used to solve the resulting discrete-time optimal control problem. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a single machine infinite bus test system for various system and loading conditions. The proposed stabiliser, which is relatively easier to synthesise, consistently outperformed stabilisers based on conventional lead-lag and linear quadratic regulator designs.

Inspec keywords: power system stability; optimal control; neural nets

Other keywords: small-signal stability; discrete nonlinear quadratic regulator problem; iterative training loop; single machine infinite bus test system; action-critic dual network architecture; single network adaptive critic design; single critic neural network; discrete-time optimal control problem; linear quadratic regulator design; power system stabiliser

Subjects: Power system control

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