摘要
为了增强含高渗透率风电电网的消纳能力,提高控制精度与运行经济性,提出了一种改进的基于双层递阶自适应模糊系统(double stage hierarchical ANFIS(adaptive neuro-fuzzy inference system),DSA)功率预测模型的风电分层有功调度控制策略。将有功调度分为系统层、风电场群层、分群子场层、风机机组层与反馈校正层,结合DSA模型对风电场超短期风电功率进行预测,考虑电网与机组安全运行等约束条件,给出了各个层级之间的协调控制关系与每个层级相应的功率分配方法,同时以滚动优化对误差进行校正。最后通过算例对所提控制策略的有效性进行分析验证,结果显示,所提控制策略在功率波动较大情况下其控制精度高,并且能有效减少风机启停次数,降低系统网损。
In order to enhance the capacity of wind power high-permeability grid and improve control accuracy and operational economy,this paper improves and proposes a layered control strategy based on DSA power prediction model wind power dispatch. The active power scheduling is divided into system layer,wind farm group layer,group sub-field layer,wind power generation unit layer and feedback correction layer. The DSA model is used to predict the ultra-short-term power output of wind farm,taking into account the constraints of the grid and the safe operation of the wind power units. The coordinated control relationship between levels and corresponding power allocation method for each level are eliminated,and the error is corrected by rolling optimization. Analysis of the example demonstrates the effectiveness of the proposed control strategy.Compared with existing control strategies,the prediction accuracy is higher. Under the condition of large power fluctuation,the root mean square error of the control is small,and the number of starts and stops of the wind power units can be effectively reduced. It reduces the network loss of the system and has the advantages of high control precision and fast response speed.
引文
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