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Automatic Generation Control of Multi-area Power System with Network Constraints and Communication Delays

机译:网络约束和通信延迟多区电力系统的自动生成控制

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摘要

Newly proposed power system control methodologies combine economic dispatch (ED) and automatic generation control (AGC) to achieve the steady-state cost-optimal solution under stochastic operation conditions. However, a real power system is subjected to continuous demand disturbance and system constraints due to the input saturation, communication delays and unmeasurable feed-forward load disturbances. Therefore, optimizing the dynamic response under practical conditions is equally important. This paper proposes a state constrained distributed model predictive control (SCDMPC) scheme for the optimal frequency regulation of an interconnected power system under actual operation conditions, which exist due to the governor saturation, generation rate constraints (GRCs), communication delays, and unmeasured feed-forward load disturbances. In addition, it proposes an algorithm to handle the solution infeasibility within the SCDMPC scheme, when the input and state constraints are conflicting. The proposed SCDMPC scheme is then tested with numerical studies on a three-area interconnected network. The results show that the proposed scheme gives better control and cost performance for both steady state and dynamic state in comparison to the traditional distributed model predictive control (MPC) schemes.
机译:新建的电力系统控制方法组合经济调度(ED)和自动化控制(AGC)在随机操作条件下实现稳态成本最佳解决方案。然而,由于输入饱和,通信延迟和不可衡量的前载负载干扰,实际电力系统受到连续需求干扰和系统约束。因此,在实际条件下优化动态响应同样重要。本文提出了一种用于在实际操作条件下实现互连电力系统的最佳频率调节的状态约束分布式模型预测控制(SCDMPC)方案,这是由于调速器饱和度,产生速率约束(GRC),通信延迟和未测量馈送所存在的 - 加速负载干扰。此外,它提出了一种算法在输入和状态约束冲突时处理SCDMPC方案内的解决方案的算法。然后测试所提出的SCDMPC方案,用关于三个区域互连网络的数值研究进行测试。结果表明,与传统的分布式模型预测控制(MPC)方案相比,该方案为稳态和动态状态提供了更好的控制和成本性能。

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