Real-Time Implementation of a Dual Function Neuron Based Wide Area SVC Damping Controller

Sandhya R. Jetti
Ganesh K. Venayagamoorthy, Missouri University of Science and Technology

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The use of wide area measurements for power system stabilization is recently given a lot of attention by researchers and the power industry to avoid cascading failures and blackouts such as the August 2003. This paper presents the design of a nonlinear external damping controller based on wide area measurements as inputs to a dual function neuron (DFN). This DFN controller is specifically designed to enhance the damping characteristics of a power system considering the nonlinearity in the system. The major advantage of the DFN controller is that it is simple in structure with less development time and hardware requirements for real-time implementation. The DFN controller is implemented on a digital signal processor and its performance is evaluated on the IEEE 12 bus FACTS benchmark power system implemented on a real time platform - real time digital simulator (RTDS). Experimental results show that the DFN controller provides better damping than a conventional linear controller