【作者】 王兴刚；

【导师】 王成山；

【作者基本信息】 天津大学 ， 电力系统及其自动化， 2007， 博士

【摘要】 可用输电能力(ATC)是现代电力系统运行的重要参数,而最大输电能力(TTC)的计算则是整个ATC分析的基础和关键,也是当前研究的热点。此外,随着风力发电产业的迅速发展,越来越多兆瓦级的大型风电场直接连入输电系统,风力发电所具有的随机特性为输电能力研究提出了新的课题。本文针对静态电压稳定约束下包含大型风电场的电力系统概率最大输电能力快速计算方法进行了深入细致的研究,取得了如下一些成果:(1)给出了可用于概率输电能力快速计算的全注入空间电压稳定域边界切平面表达式,结合矢量量化聚类分析,采用多个切平面近似描述电压稳定域边界。在此基础上,发展了一种考虑负荷和发电机出力不确定性因素的概率TTC快速计算方法,并利用该方法进一步研究了负荷波动及其不同增长方式对概率TTC的影响。(2)发展了一种能够计及线路故障的概率TTC分层快速计算方法。该方法针对因线路故障引起的电压稳定域边界的改变,利用阻尼牛顿法从故障前稳定域边界点直接计算得到故障后稳定域边界点,然后用切平面描述故障后稳定域的局部。针对线路连锁故障,发展了一种考虑线路故障相关性的Monte Carlo仿真方法,并以此分析了线路故障相关性对概率输电能力的影响。(3)在完整的异步发电机π型等值电路基础上,建立了含异步风电机组的统一迭代连续性潮流计算模型,提出了电压稳定约束下包含风电场的TTC计算方法,并进一步研究了风速、风电穿透功率对TTC的影响。(4)给出了可以直接反映风电场风速变化影响的扩展全注入空间相关定义,建立了加入异步风力发电机模型的含参潮流模型,推导出了含风电功率项的扩展全注入空间电压稳定域边界切平面解析式。在此基础上,提出了综合考虑风电场风速、负荷、发电机出力和线路故障不确定性因素的概率TTC分层快速计算方法。与传统概率性方法相比较,该方法不仅可以方便地考虑风电场风速波动随机性的影响,而且具有精度高、计算速度快、可在线应用的优点。更多还原

【Abstract】 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.更多还原