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.

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.

Modern interconnected power systems are becoming highly complex and sophisticated, while increasing energy penetrations through congested inter-tie lines causing the operating point approaching stability margins. This as a result, exposes the overall system to potential low frequency power oscillation phenomena following disturbances. This in turn can lead to cascading events and blackouts. Recent approaches to counteract this phenomenon are based on utilization of wide area monitoring systems (WAMS) and power electronics based devices, such as flexible AC transmission systems (FACTS) and HVDC links for advanced power oscillation damping provision. The rise of hybrid AC-DC power systems is therefore sought as a viable solution in overcoming this challenge and securing wide-area stability. If multiple FACTS devices and HVDC links are integrated in a scheme with no supervising control actions considered amongst them, the overall system response might not be optimal. Each device might attempt to individually damp power oscillations ignoring the control status of the rest. This introduces an increasing chance of destabilizing interactions taking place between them, leading to under-utilized performance, increased costs and system wide-area stability deterioration. This research investigates the development of a novel supervisory control scheme that optimally coordinates a parallel operation of multiple FACTS devices and an HVDC link distributed across a power system. The control system is based on Linear Quadratic Gaussian (LQG) modern optimal control theory. The proposed new control scheme provides coordinating control signals to WAMS based FACTS devices and HVDC link, to optimally and coherently counteract inter-area modes of low frequency power oscillations inherent in the system. The thesis makes a thorough review of the existing and well-established improved stability practises a power system benefits from through the implementation of a single FACTS device or HVDC link, and compares the case –and hence raises the issue–when all active components are integrated simultaneously and uncoordinatedly. System identification approaches are also in the core of this research, serving as means of reaching a linear state space model representative of the non-linear power system, which is a pre-requisite for LQG control design methodology.

Power flow (PF) control can increase the utilization of the transmission system and connect lower cost generation with load. While PF controllers have demonstrated the ability to realize dynamic PF control for more than 25 years, PF control has been sparsely implemented. This research re-examines PF control in light of the recent development of fractionally-rated PF controllers and the incremental power flow (IPF) control concept. IPF control is the transfer of an incremental quantity of power from a specified source bus to specified destination bus along a specified path without influencing power flows on circuits outside of the path. The objectives of the research are to develop power system operation and planning methods compatible with IPF control, test the technical viability of IPF control, develop transmission planning frameworks leveraging PF and IPF control, develop power system operation and planning tools compatible with PF control, and quantify the impacts of PF and IPF control on multi-decade transmission planning. The results suggest that planning and operation of the power system are feasible with PF controllers and may lead to cost savings. The proposed planning frameworks may incent transmission investment and be compatible with the existing transmission planning process. If the results of the planning tool demonstration scale to the national level, the annual savings in electricity expenditures would be $13 billion per year (2010$). The proposed incremental packetized energy concept may facilitate a reduction in the environmental impact of energy consumption and lead to additional cost savings.