Advances in power system small signal stability analysis considering load modeling and emerging generation resource

With the increasing complexity of the power system, electromechanical oscillations are becoming one of the major problem. Several blackouts have been reported in the past due to insufficient damping of the oscillatory modes. The starting point to avoid catastrophic behaviors would be to simulate actual power system and study the response of the system under various outages leading to blackouts. Recently, it has been identified that appropriate modeling of the load is necessary to match the actual system behavior with the computer simulated response. This research throws some insight into the detailed load modeling and its impact on the system small signal stability. In particular, Composite load model is proposed and its effect on the system small signal stability is investigated. Modeling all the loads in a large power system would be a cumbersome job and hence the method for identifying the most sensitive load location is also proposed in the thesis. The effect of load modeling on the eigenvalue movement is also investigated. The low damped electromechanical modes are always undesirable in the large inter-connected power systems as they might get excited under some event leading to growing oscillations. Proper damping of these modes is essential for effective and reliable system operation. Power system stabilizers have been proved to be an effective way of damping these electromechanical modes. The optimal number and location of PSS to effectively damp the modes via improved Differential algorithm is proposed. Moreover, the effect of TCSC, series compensated FACTs device, on enhancing the system damping is investigated. A fixed order model matching technique is presented to design a damping controller for the TCSC. With the increasing global pressure for reducing carbon emissions, there is a great amount of interest in the renewable sources of energy, particularly Wind Energy Conversion Systems. Of all the present methods of wind generation systems, Doubly Fed Induction Generation (DFIG) based wind farms are gaining popularity. The comparison of various methods of wind generation techniques is presented. In particular, the impact of DFIG based wind farms on the system small signal stability is investigated in this work. Co-ordinated tuning of the controllers is performed using Bacterial Foraging Technique, which is another member of Evolutionary algorithms. Damping controller for the DFIG system is proposed to enhance the damping of the electromechanical modes. Results have proved the effectiveness of the control methodology. The contributions made in this thesis could be utilized to promote the further development of the damping controllers for large power systems