风电高渗透率系统的有功调控策略研究

发布时间：2018-08-05 14:43

【摘要】：随着风电场并网容量的逐渐增加，其给电网带来的不利影响也愈加明显，如果完全依靠传统电源对所造成的影响进行补偿，可能会因此增加传统电源的备用容量，加大系统的运行成本。所以，，随着分布式电源并入电网容量的增加，需对含高渗透率风电场的电力系统的有功功率策略进行研究。首先对双馈式风力发电系统进行建模，分析其各模块的数学模型，研究其网侧逆变器和转子侧逆变器的控制策略。在此基础上设计了考虑风速变化及稳态频率误差的一次调频控制器，减少系统频率偏差。并提出了基于直流灵敏度的风电场间有功功率的调控策略，通过此调控策略可以调控各个风电场的出力，从而解决系统发生大扰动时有功潮流的变化问题。同时对所提出的控制策略分别进行了验证分析，结果表明所提的一次调频控制策略可以有效改善系统的频率偏差，基于直流灵敏度的风电场间有功功率的调控策略可以有效消除支路的潮流越限。其次针对电力系统接纳风电备用容量不足的情况，同时综合考虑风功率预测、风电场装机容量等因素，提出基于风功率预测的比例算法、基于风功率预测的优化算法两种风电场间限值优化策略，使风电场自主参与系统调峰。通过实例对传统的基于风电场装机容量的优化分配算法及所提出的两种优化策略分别进行验证，结果表明基于风功率预测的优化算法和基于风功率预测的比例算法均明显优于传统的基于风电场装机容量的分配算法，其中基于风功率预测的优化算法最优。最后提出基于机组分类的风电场内各机组间的优化分配策略。根据场内各个机组不同的运行特性，计算出各机组的特征矩阵，运用模糊聚类分析方法对机组进行分类，并根据遗传寻优算法对分类机组进行机组组合，选取最优的机组运行组合，通过基于风功率预测的优化算法对最优的机组运行组合进行具体的功率数值分配。并通过实例对所提优化策略进行验证，结果表明此策略可以准确地按照调度指令对风电场内机组间的功率进行优化分配。
[Abstract]:With the gradual increase of wind farm grid capacity, the negative impact on power grid becomes more and more obvious. If we rely on the traditional power supply to compensate for the impact, it may increase the reserve capacity of traditional power supply. Increase the operating cost of the system. Therefore, with the increase of the capacity of distributed generation integrated into power grid, the active power strategy of power system with high permeability wind farm should be studied. Firstly, the model of doubly-fed wind power generation system is built, the mathematical models of each module are analyzed, and the control strategies of grid-side inverter and rotor-side inverter are studied. On this basis, a primary frequency modulation controller considering the variation of wind speed and the error of steady frequency is designed to reduce the frequency deviation of the system. An active power control strategy based on DC sensitivity is proposed, which can be used to control the output of each wind farm, thus solving the problem of the change of active power flow in the event of large disturbance of the system. At the same time, the proposed control strategies are verified and analyzed respectively. The results show that the proposed primary frequency modulation control strategy can effectively improve the frequency deviation of the system. The active power regulation strategy based on DC sensitivity between wind farms can effectively eliminate the branch power flow limit. Secondly, considering the wind power forecast, wind farm installed capacity and other factors, a proportion algorithm based on wind power prediction is proposed. The optimization algorithm based on wind power prediction can make wind farm participate in the system peak shaving independently by optimizing the limit value between two kinds of wind farm. The traditional optimal allocation algorithm based on installed capacity of wind farm and the proposed two optimization strategies are verified by examples. The results show that the optimization algorithm based on wind power prediction and the proportion algorithm based on wind power prediction are obviously superior to the traditional allocation algorithm based on wind farm installed capacity, among which the optimization algorithm based on wind power prediction is optimal. Finally, an optimal allocation strategy for wind farms based on unit classification is proposed. According to the different operating characteristics of each unit in the field, the characteristic matrix of each unit is calculated, and the unit is classified by using fuzzy cluster analysis method, and the unit combination is carried out according to the genetic optimization algorithm. The optimal unit operation group is selected and the optimal unit operation unit is allocated numerically by the optimal wind power prediction algorithm. An example is given to verify the proposed optimization strategy. The results show that the proposed strategy can accurately allocate the power between units in a wind farm according to the dispatching instructions.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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