Research On Fast Calculation Of Probabilistic Total Transfer Capability Considering Static Voltage Stability Constraints

In a competitive market environment, Available Transfer Capability (ATC) is a very important parameter for both independent system operator (ISO) and all market participants. The calculation of Total Transfer Capability (TTC) is the groundwork of ATC research. In the actual real-time operation of power system, TTC is usually updated every half or one hour, and currently only calculated using deterministic model. However, deterministic model only considers the worst case. A large number of system uncertainties, such as loads, generations and contingency randomness, are ignored in the deterministic model. Accordingly, the probabilistic model can provide more useful information, such as the expectation value and the probability distribution of TTC. However, present probabilistic methods are too slow to be used in real-time TTC evaluation.Meanwhile, there are more and more megawatt large-scale wind farms being connected directly into power systems while wind power generation is developing rapidly all through the world. The randomness and fluctuation of wind energy will bring new problems to the research of transfer capability.In this thesis, fast calculation methodology of probabilistic TTC considering static voltage stability constraints is systematically and thoroughly studied, and some conclusions are derived:Firstly, for the fast calculation of probabilistic TTC, a hyper-plane equation is derived to estimate part of the SVSR boundary in power injection space. The SVSR boundary under base system configuration is described by a set of hyper-planes, whose number and tangent point are determined by Vector Quantification (VQ) clustering method. Then a fast probabilistic TTC calculation method is proposed with the consideration of loads and generation uncertainties. Using the proposed method, The influence of load fluctuation and load increasing mode on probabilistic TTC is also discussed.Secondly, a layered probabilistic TTC calculation model is developed for line outage uncertainties. The partial boundary of the post-contingency SVSR is also described by a hyper-plane, whose tangent point is directly calculated from the pre-contingency point by damped Newton method. Then the TTC of each sampled system condition can be obtained quickly using the SVSR boundary to represent voltage stability constraints. In order to show the influence of line outage correlation on TTC, a new Monte Carlo simulation method is also proposed to simulate line cascading contingencies.Thirdly, based on the completeπ-type equivalent circuit of asynchronous wind turbine, a new unified iterative continuation power flow algorithm is proposed. Using this method, TTC of power system containing wind farms can be investigated under static voltage stability constraints. The influence of wind speed variation and wind power penetration on TTC is also analyzed.Finally, an extended full injection space, which can reflect wind speed variation in wind farms, is defined. And a new hyper-plane equation containing wind mechanical power is derived to estimate part of the SVSR boundary in the extended full injection space. Then a new probabilistic method to evaluate TTC in power system including large-scale wind farms is developed. Wind speed, loads, generation and line contingencies uncertainties are considered at the same time in this model.Compared with traditional probabilistic method, the proposed method can not only consider conveniently the influence of wind power randomness, but also significantly reduce the computation load while maintaining a satisfied accuracy. This method will be useful for system operator to evaluate probabilistic TTC in real-time. Based on this method, the influence of wind speed probability distribution parameters on TTC is also discussed.