| Power system stability is a complex subject that has challenged power system for many years. With the development of power industry and power markets, there is a tendency of increased complexity of dynamic characteristics and stability mechanism, a tendency of extended impact of various uncertainties on system operation, and thus an ever-increasingly concern about consequences of loss-of-stability. How to improve the abilities of power systems to remain stability and reduce widespread power interruptions, and how to evaluate system stability level and effects of various operation and control actions in a comprehensive and scientific way, has become a challenge and an essential problem in both theory and practice.Asynchronized generator (ASG) is a new kind of machine with controlled excitation field distribution to rotor axis. Because of this control flexibility, ASG has many preferable features, compared with conventional synchronous generator (SG), in such as active/reactive power regulation, reactive power injection capability, speed adaptivity and stability characteristics. Theoretical analysis and digital/physical simulation results from simple systems have proved that ASG has positive effects on system stability and thus contributes a new solution to stability problems. Most studies on ASG are, however, focused on machine or confined to machine operation and control, which has retarded the progress of ASGs'practical application to some degree. With an effort to answer whether ASG in a multimachine system has contribution to stability improvement and how to provide a scientific measure of this contribution, this thesis carries out a thorough study on dynamic modeling and probabilistic stability evaluation of ASG in a multimachine system.A simplified ASG model for multimachine system analysis is presented. The simplified model is developed by defining d- and q-axis operational parameters and making various degrees of approximations on basic machine equations to adapt to machine-network interface and large scale system analysis. With this model, ASG can be represented in various levels of detail, ranging from the 2-order constant flux linkage model to the higher order models with or without the representation of damper windings. The presented model is systematic in form, clear in physical concept, and available for direct interconnection with quasi-steady network equations. Also the presented model is represented in a similar way to that of SG, with a simple neglecting q-axis field voltage equation it can be converted to SG model. This feature is helpful to explain the difference and relation between ASG and SG from their mathematic models. A single-machine infinite bus system and the New England 10-machine 39-bus system are used to test the presented ASG model.A linearized model of a multimachine system with ASGs is then developed based on the presented dynamic model and tested by post-disturbance time response and spectrum analysis. Then small-signal eigenvalue analysis and transient time-domain simulation are performed on multimachine systems with one or more ASGs. Quantified effects of ASGs on system small-signal and transient stability are obtained and their responses to changes in ASG excitation strategies, numbers, capacity percentages and arrangements are also discussed. Simulations on the WECC 3-machine 9-bus system have indicated that ASGs with proper excitation control can improve system damper and dynamic response, increase critical clearing time, and thus enhance the overall system rotor angle stability. Demonstration of ASGs on system stability enhancement and principles of ASG configurations proposed in this thesis are meaningful development of machine-centered studies so far, and can be used as a decision-making assistant in ASGs'practical application and/or modification of conventional power stations.Probabilistic stability analysis of ASGs and of power systems with ASGs is a previously unaccessed area. Traditional stability criteria often neglect the inherent stochastic nature of power systems and thus can hardly provide a comprehensive, realistic and scientific measure of system stability level. This thesis conducts a logical extension of ASG studies to probabilistic stability analysis. Taking uncertainties in load variations, generator outages, network configuration and fault events into account, effects of ASGs on system stability are studied in a probabilistic framework based upon Monte-Carlo simulation method. In probabilistic small-signal stability (PSSS) analysis, with uncertainties in network configuration (which are nearly ignored in PSSS so far) considered, a lot of information of the small-signal behavior of ASGs in a multimachine system are obtained, such as the mean values, standard deviations and distribution of system eigenvalues and probability of small-signal instability. In probabilistic transient stability (PTS) analysis, several indices, namely Probability of Transient Instability, Expected Transient Generation/Load Curtailments, Expected Critical Clearing Time and Expected Clearing Time Margin, are defined as PTS indicators of the overall system and/or at each component. These indices can be used to estimate the overall system transient stability risk or to identify the most critical component for maintaining transient stability and proved to be a meaningful extension of the existing PTS indices. Simulations on the WECC 3-machine 9-bus system have indicated that ASGs with proper excitation control can reduce the overall system risk to lose rotor angle stability. With uncertainties and their effects considered, studies above provide new ideas and methods to develop and extend the existing ASG area, which can be used to describe the dynamic behavior of ASGs in a multimachine system and to evaluate the contribution of ASGs on system stability in a more probabilistic and scientific way.Finally, possibilities of performing large scale probabilistic stability analysis on commercial power system analysis platform are explored. A method based on Monte-Carlo simulation and DSA Tools customization is proposed and verified on the IEEE 17-machine 162-bus system.
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