论文标题
用于运营具有强大动力储量的快速频率调节服务的最佳控制设计
Optimal Control Design for Operating a Hybrid PV Plant with Robust Power Reserves for Fast Frequency Regulation Services
论文作者
论文摘要
本文提出了一种最佳控制策略，用于运营由太阳能光伏（PV）和高功率，低存储电池储能系统（BESS）组成的太阳能混合动力系统。首先得出了混合PV工厂的状态空间模型，基于设计自适应模型预测控制器。控制器的目标是控制PV和BESS，以遵循发送到混合系统的功率设定点，同时保持所需的功率储备并满足系统操作约束。此外，实施了扩展的卡尔曼过滤器（EKF）来估计电池SOC，并执行错误敏感性以评估其局限性。为了验证提出的策略，开发了混合系统的详细EMT模型，以便可以准确量化损失和控制限制。长时间的模拟使用第二次实际的PV农场数据作为输入在Opal-RT实时模拟器中进行。结果验证了所提出的方法可以遵循功率设定点，同时即使使用较小的BESS存储，也可以在高辐照度间歇性的天数中保持功率储备。
This paper presents an optimal control strategy for operating a solar hybrid system consisting of solar photovoltaic (PV) and a high-power, low-storage battery energy storage system (BESS). A state-space model of the hybrid PV plant is first derived, based on which an adaptive model predictive controller is designed. The controller's objective is to control the PV and BESS to follow power setpoints sent to the the hybrid system while maintaining desired power reserves and meeting system operational constraints. Furthermore, an extended Kalman filter (EKF) is implemented for estimating the battery SOC, and an error sensitivity is executed to assess its limitations. To validate the proposed strategy, detailed EMT models of the hybrid system are developed so that losses and control limits can be quantified accurately. Day-long simulations are performed in an OPAL-RT real-time simulator using second-by-second actual PV farm data as inputs. Results verify that the proposed method can follow power setpoints while maintaining power reserves in days of high irradiance intermittency even with a small BESS storage.
