On-line transient stability enhancement using multi-agent technique

Abstract

This paper proposes a multi-agent technique that is divided into two parts. The first part is a prediction agent that will predict power system instability. According to the prediction agent's output, control agent is initiated. The prediction agent is adapted from a proven robotic ball-catching algorithm. The control agent initiates turbine fast valving. The resulting multi-agent technique can predict system instability and establish system stability. Decoded MATLAB programs of both agents are linked to ETMSP program, power system simulation program, used in verifying the results. Results show that the proposed technique could be used on-line for power system instability prediction and control if the control agent speed can be increased.

A multi-agent approach for enhancing transient stability of smart grids

“…In practice, the rotor angle of generators cannot be measured conveniently [2,21]. A robotic ballcatching algorithm along with MAF is proposed in [22] for online transient stability analysis with post-fault valve control application where the algorithm is used for predicting the instability for out of synchronizing machines. Another multi-agent approach has been proposed in [23,24] to enhance the transient stability where two agents-prediction and control, are used under abnormal operating conditions through the application of potential energy boundary surface (PEBS) method.…”

Distributed Multi-Agent-Based Protection Scheme for Transient Stability Enhancement in Power Systems

“…A multi-agent-based coordinated control scheme is proposed in [15,16] where multi-agent framework is developed through wide area measurements (WAMs). In [17,18] an output tracking agent is used to track the output where the output of the generator is considered as the rotor angle of the generator and the control agent is used to initiate the turbine valving control. In practice, the rotor angle of generators may not be conveniently measured [19,20].…”

A real-time generator-angle prediction method based on the modified grey Verhulst model

“…Literature [12] proposed that the perturbed trajectory of post-fault rotor angle can be expressed by the trigonometric function combination model. By adopting Taylor's Series and the interpolation method to predict the future angular velocity, literature [13,14] estimate the future rotor angle value by integration of the predicted angular velocity.…”