Knowledge domain states mapping concept for controller tuning in an interconnected power network

This paper presents novel power system stabilizers (PSS) tuning approach with particles swarm optimization (PSO) driven knowledge domain states mapping for multi area power system. Tuning of PSS parameters has been done by PSO technique offline at different operating conditions as load dynamics change. The objective function for PSS parameters tuning is integral time multiplied by absolute error (ITAE). The sets of tuned parameters at different operating conditions thus obtained are termed as knowledge domain. The process is viewed as knowledge domain mapping. The dynamical system response has been linked with states, and if there is any violation from desired limits, control action is initiated and thus retuned control parameters obtained straight away from the respective knowledge domain helps to provide quick response and precise damping of signals of interest. Proposed concept also demonstrates that if one controller (PSS) fails to stabilize the system at certain operating condition then another controller (UPFC) connected in the system acts as supplementary controller in automation which assists PSS functioning and thus entire system operation improves by way of modulating the signal dynamics at interface points which quickly damps oscillations. The system study has been performed on a sample six area power systems comprising of UPFC connected between area two and three and PSS to all areas. The proposed concept demonstrates auto tuning of PSS for quick oscillation damping as the operating conditions change and also under situations of PSS failure due to relatively larger perturbation, UPFC acts as supplementary controller by assisting the entire system PSS to recover ensuring stability.