Abstract
This paper proposed an ANN (Artificial Neural Network) controller to damp out inter-area oscillation of a power system using BESS (Battery Energy Storage System). The conventional lead-lag controller-based PSSs (Power System Stabilizer) have been designed using linear models usually linearized at heavy load conditions. This paper proposes a non-linear ANN based BESS controller as the ANN can emulate nonlinear dynamics. To prove the performance of this nonlinear PSS, two linear PSS are introduced at first which are linearized at the heavy load and light load conditions, respectively. It is then verified that each controller can damp out inter-area oscillations at its own condition but not satisfactorily at the other condition. Finally, an ANN controller, that learned the dynamics of these two controllers, is proposed. Case studies are performed using PSCAD/EMTDC and MATLAB. As a result, the proposed ANN PSS shows a promising robust nonlinear performance.
Highlights
As electro-mechanical oscillations between interconnected synchronous generators may cause instability of the entire power system, Kunder [1,2] presented the local mode oscillation and inter-area oscillation, and proposed a two area four machine power system model
This paper proposes a non-linear Artificial Neural Network (ANN) based Battery Energy Storage System (BESS) controller as the ANN can emulate nonlinear dynamics
The simulation werecontroller verified with using trained ANN
Summary
As electro-mechanical oscillations between interconnected synchronous generators may cause instability of the entire power system, Kunder [1,2] presented the local mode oscillation and inter-area oscillation, and proposed a two area four machine power system model. This hypothetical reduced power system model, the so-called IEEE 2 area 4 machine benchmark model, has been widely used to study inter-area oscillation as real power systems are very large and complex. Regarding the BESS application, Du [9]
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