风电场的随机优化模型及其混合智能算法

Stochastic optimization model and its hybrid intelligent algorithm for wind power station

由于发电场无功优化本身的复杂性和风力发电的随机性,含有风电的无功优化问题不再是一个常规意义下的确定性问题,利用传统的方法也难获得既经济又有较高可靠性的解。把输入输出功率及无功功率看成随机变量,建立了基于机会约束规划的风电场无功优化数学模型,以概率的形式描述相关约束条件,考虑了利用风能的发电机机端电压限制、发电机的有功无功出力限制、线路潮流方程及负荷节点的出力限制等约束条件,利用混合智能算法求解该问题。通过3个节点系统的算例验证,证明该模型与算法具有有效性。

Due to the complexity of wind power station reactive power optimization and the randomness of wind power generation,the reactive power optimization of wind power station is no longer a question with certain solution in conventional sense,and it is difficult to obtain economical and more reliable solution by traditional method. Considering the input and output power and reactive power as random variables,a reactive power optimization mathematic model for wind power station had been built based on the chance-constrained programming.In this model the relevant constraint conditions were described in probability mode,the constraint conditions were considered which include the terminal voltage limit of wind power generator,the limit of output active and reactive power of generator,the line tidal flow equation,the output power limit of load nodes and others,and the hybrid intelligent algorithm was used to find the solution of the question. It is proved by an example of a system with three nodes that the model and the algorithm are effective.