基于遗传算法的双馈风场分群无功控制策略

现有的双馈风电场无功控制多数采用恒功率因数控制,既没有充分利用风电场内双馈风电机组和无功补偿设备的无功调节能力,也没有考虑风电场集电系统的网损。提出了一种综合考虑集电系统特点和DFIG无功调节能力的无功控制策略,该策略以实时监测的风电场并网点电压数据和DFIG有功出力数据为基础,通过分析双馈风电机组的功率特性和风电场的无功需求,利用遗传算法求解风电场多目标无功优化控制模型,达到降低集电系统网损和改善并网点电压的目的。对某实际风场的仿真算例验证了所提策略的有效性。

A Clustering Reactive Power Control Strategy in DFIG-based wind farm based on genetic algorithm

Most of the reactive power control of doubly-fed wind farm uses the constant power factor control , which doesn’ t make full use of the reactive power adjustment capability of DFIG and reactive compensation equipment in doubly-fed wind farm , nor does it takes the network-loss in the power collector system into consideration .This paper presents a comprehensive consideration of the characteristics of current collector systems and reactive power regulation capabilities of DFIG for reactive power control strategy .The strategy is based on the real-time monitoring date includes the point of common coupling and active power output date of DFIG , according to analysis the power characteristics of DFIG and the reactive power demand of wind farm , it uses the genetic algorithm for multi-objective reactive power op-timization control model of wind farm to reduce network-loss of the collector system and improve the power quality of the point of common coupling .A simulation case of an actual wind field verifies the validity of the strategy .