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Robust Control Scheme for Distributed Battery Energy Storage Systems in Load Frequency Control

机译:负载频率控制中分布式电池储能系统的鲁棒控制方案

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This paper proposes a robust control scheme to involve the distributed Battery Energy Storage Systems (BESSs) in Load Frequency Control (LFC) through BESS aggregators with sparse communication networks. In order to cope with the uncertainties associated with system operation, a two-layer Model Predictive Control (MPC) is developed so that more efficient control signals are provided to improve the response of BESSs to make larger contribution to the LFC. The outer layer in the proposed structure produces the command signal for the aggregator based on signals which are produced by the inner layer as well as the signal provided from the actual system. These command signals are provided so as to achieve the least value of error in Area Control Error (ACE) with a minimum control effort taking a variety of operational and physical constraints into consideration. Optimization procedures are also carried out to compute the optimal value of weighting coefficients contained in the objective functions. The capability of controller to cope with uncertainties is compared with a conventional single-layer MPC. In addition, the delay caused by propagation channels in delivering control signals to BESSs is modeled, and its impact on the performance of frequency regulation is evaluated. An intelligent fuzzy coordination control is then developed to coordinate the BESS aggregator and conventional power plants to avoid extra power injection/withdrawal by the conventional power plants in case of long delays. Case studies are conducted to illustrate the effectiveness of the proposed structure in controlling distributed BESSs with diverse energy capacities, rated powers, charging/discharging coefficients and time constants; and State of Charges (SoCs).
机译:本文提出了一种稳健的控制方案,以使负载频率控制(LFC)中的分布式电池能量存储系统(BESS)涉及具有稀疏通信网络的BESS聚合器。为了应对与系统操作相关的不确定性,开发了一种双层模型预测控制(MPC),从而提供了更有效的控制信号来提高BESS对LFC对LFC进行更大贡献的更有效的控制信号。所提出的结构中的外层基于由内层产生的信号以及由实际系统提供的信号产生聚合器的命令信号。提供了这些命令信号,以便在考虑到考虑各种操作和物理限制的最小控制工作中实现区域控制误差(ACE)的最小值。还执行优化过程以计算目标函数中包含的加权系数的最佳值。将控制器应对不确定性的能力与传统的单层MPC进行比较。另外,由传播信道在将控制信号传送到贝塞斯的传播信道引起的延迟被建模,并且评估其对频率调节性能的影响。然后开发了一种智能模糊协调控制以协调BESS聚合器和传统发电厂,以避免传统发电厂在长延迟的情况下通过额外的功率注入/取出。进行案例研究以说明所提出的结构在控制具有不同能量容量,额定功率,充电/放电系数和时间常数中的分布式贝塞尔控制的有效性;和收费状态(SOC)。

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