风电场与AGC机组分布式协同实时控制

Distributed Coordinated Real-time Control of Wind Farm and AGC Units

受风电预测相对负荷预测水平较低的影响,常规自动发电控制(automatic generation control,AGC)机组计划出力与实际最佳出力有较大的偏差。如何在最大化消纳风电的同时减少风电波动对AGC调节裕度的影响,成为大规模风电接入背景下实时控制的主要问题。为此,构建分钟级时间尺度下的风电场与AGC机组分布式协同实时控制模型,提出适用于大规模风电并网下实时控制过程的分布式增量一致算法,将净负荷增量的预测值在常规AGC机组与风电场之间通过等边际成本法则进行分配,以降低系统运行成本和提高系统风电消纳能力。算例表明,所提策略的应用既可以保证AGC机组调节性能,又可以在一定程度上降低风电受限量和系统的运行成本。

For the predication error of wind power is much larger than that of loads, there may be great deviation between the actual output power and scheduled value of conventional automatic generation control（AGC） units. How to reduce the impact of wind power fluctuation on AGC regulation capacity and curtail the amount of wind power becomes an important problem for active power real time control. To solve the problem, a minutely distributed coordinated real-time control model of wind farm and AGC units was constructed, and a distributed incremental consistent algorithm applying to real-time control process with high wind power penetration was proposed. In order to reduce the power system operating cost and the curtailed amount of wind power, the minutely net-load increment was allocated between the wind farm and conventional AGC units according to the law of equal marginal costs. The simulation results validate the effectiveness of the proposed control strategy, and the regulation capacity of AGC units can be guaranteed as well as reducing the curtailed amount of wind power and power system operating cost.