The reliable control of the large-scale wind farm is crucial for the stability and security of the renewable power system with high wind power penetration. Due to the uncertain and variable nature of wind power, the traditional control strategy is difficult to work. Regarding the large-scale, geographically dispersed wind farm, an efficient distributed economic model predictive control strategy is proposed, which integrates the power tracking and economic optimization of the wind farm into one optimal control framework. By adopting the global economic cost function, the Nash optimal solutions under distributed framework approach the Pareto optimum. Thus, the reference power from the transmission system operator is accurately tracked, while the global dynamic economic optimality is guaranteed. The simulation results under step wind speed and practical wind speed variations verify the efficiency and reliability of the proposed control strategy.

大型风电场的可靠控制对于具有高风电渗透率的可再生电力系统的稳定性和安全性至关重要。由于风电的不确定性和可变性，传统的控制策略难以奏效。针对大规模、地理分散的风电场，提出了一种高效的分布式经济模型预测控制策略，将风电场的功率跟踪和经济优化集成到一个最优控制框架中。通过采用全局经济成本函数，分布式框架下的纳什最优解逼近帕累托最优。从而准确跟踪来自输电系统运营商的参考功率，同时保证全局动态经济最优。