Abstract. The paper considers simultaneous placement and tuning of power system stabilizers for stabilization of power systems over a wide range of operating conditions using genetic algorithm. The power system operating at various conditions is considered as a finite set of plants. The problem of setting parameters of power system stabilizers is converted as a simple optimization problem that is solved by a genetic algorithm and an eigenvalue-based objective function. A single machine -infinite bus system and a multi-machine system are considered to test the suggested technique. The optimum placement and tuning of parameters of PSSs are done simultaneously. A PSS tuned using this procedure is robust at different operating conditions and structure changes of the system.

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The primary tasks af an electric utility is to predict the load requirements of the power system. Especially important k forecasting of the peak load. since it is the basis for the system state estimation and for technical and economic calculations of the generation and distribution system. To minimize the operating cost, electric supplier will use forecosted load to control the number of running generator unit. This paper i s concemed with the prediction of the daily peak value of the load in the power system using emotional leaming basedjiqy approach.Emotional learning is a family of intelligent algorithms, which can be used for time series prediction, classification, control and identification. The simulation results show lhat the proposed method is suifoble for forecasting application. This method is relatively simple, and effectively uses historical data to provide loadforecasts.

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