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含双馈感应风电机组的配电网无功优化 被引量:3

Reactive Power Optimization in Distribution Network with Doubly Fed Induction Generators
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摘要 考虑传统无功调节设备调节次数限制和双馈感应电机无功容量限制等约束条件,提出一种基于双馈感应电机与传统无功调节设备协调控制的分时段分层无功优化策略。首先,该策略采用谱系聚类算法对预测等效负荷曲线进行分段;其次,在每个时段采用分层调控策略进行无功优化,建立以网损和平均电压偏离度之和为目标函数的无功优化模型,上层利用改进粒子群算法计算出包括双馈感应机组在内的各种无功调节设备的优化运行状态,并预先对变压器、电容器动作;在此基础上,下层利用双馈感应机组的无功调节能力对上层优化得出的并网点电压进行自动跟踪控制,由此实现了每个时段内接入点电压控制和全局无功优化相结合,最后以IEEE33节点配电系统为算例来验证上述策略的有效性。 Considering the constraint conditions such as the restriction of regulating times of the traditional reactive-power regulation device and limitations of the DFIG’s reactive capacity, this paper proposes a time-interval and hierarchical reactive optimization strategy based on the coordinated control between doubly-fed induction generator(DFIG) and the tradi-tional reactive optimization device. In this strategy, first of all, the prediction effective load curve is divided into several periods by hierarchical clustering analysis algorithm. Second, the stratified control strategy is applied for reactive optimization in different periods. The sum of the network loss and average node voltage deviation is chosen as the objective in the proposed reactive power optimization algorithm. The upper layer uses improved particle swarm optimization to calculate the optimal operation state of all kinds of reactive power regulation devices including DFIG. The switching of transformer taps and capacitor is pre-performed. On the basis, the lower layer uses the flexible control capacity of the DFIG’s reactive power to follow the reference voltage value which is provided by the upper layer’ optimization results, herefrom the voltage control at the grid-connecting point during each time interval and global reactive optimization is implemented. Finally, a 33-node distribution system is used as a test case to verify the validity of the theory.
出处 《电网与清洁能源》 2013年第10期74-79,90,共7页 Power System and Clean Energy
关键词 双馈感应电机 分时段分层 配电网 无功优化 改进 粒子群算法 DFIG time-interval and hierarchical distribu-tion system reactive optimization improved PSO
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