基于深度强化学习的储能与其他电源协同AGC控制策略

A Collaborative AGC Control Strategy for Energy Storage and Other Power Sources Based on Deep Reinforcement Learning

  • 摘要: 针对大型风光基地并网有功调节不足、联络线关口考核压力大的问题,提出一种计及控制性能标准和储能荷电状态(state of charge,SOC)恢复至全天各时段最佳常态设置值的多能协同自动发电控制策略。搭建互联电网负荷频率控制模型,区分区域控制偏差值的大小,分别设计含控制性能标准、断面越限控制和多个储能单元SOC恢复至对应时段最佳常态设置值的奖励函数,以火电机组日前两阶段随机优化调度结果为依据,得到全天各时段平抑风光功率波动和联络线功率波动效果最好的储能SOC常态设置值,构建多时间尺度的状态感知体系,制定储能最优自适应协调频率控制策略。通过加入蒙东电网实际风光波动数据仿真,验证了所提方法在区域控制偏差较小时,多个储能单元SOC值能恢复至最佳常态设置值。在控制过程中,各储能单元SOC也逐渐趋于一致。仿真结果表明,所提方法不仅能够满足控制性能标准,而且储能能够持续、高效运行。

     

    Abstract: Aiming at the issues of insufficient active power regulation capacity in grid-connected large-scale wind-solar bases and high assessment pressure at the interface of line corridors, a multi-energy cooperative automatic power generation control strategy is proposed, which incorporates the control performance standard and restores the state of charge (SOC) of energy storage to the optimal normal setpoint throughout the day. A load frequency control model is developed for the interconnected power grid to distinguish the size of regional control deviation values, and respectively design reward functions including control performance criteria, cross-sectional over-limit control, and multiple energy storage unit SOC recovery to the optimal normal setpoint of the corresponding period. Based on the random optimization dispatching results of the thermal power units in the previous two stages, the normal setpoint of the energy storage SOC that has the best effect in suppressing the fluctuations of wind and solar power and the power fluctuations of the connection line at each time period throughout the day is obtained. In addition, a multi-time scale state perception system is constructed, and an optimal adaptive coordinated frequency control strategy for energy storage is formulated. Through the simulation incorporating the actual wind and solar output fluctuation data from the Inner Mongolia East Power Grid, it is verified that when the regional control deviation is within a small range, the SOC values of multiple energy storage units can be restored to the optimal normal setting values by the proposed method. During the control process, the SOC of each energy storage unit gradually becomes consistent. The simulation results indicate that the proposed method not only satisfies the control performance specifications, but also enables the energy storage systems to operate continuously and efficiently.

     

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