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Sub-synchronous resonance damping using high penetration PV plant

机译：使用高渗透率光伏电站的次同步共振阻尼

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摘要

The growing need to the clean and renewable energy has led to the fast development of transmission voltage-level photovoltaic (PV) plants all over the world. These large scale PV plants are going to be connected to power systems and one of the important subjects that should be investigated is the impact of these plants on the power system stability. Can large scale PV plants help to damp sub-synchronous resonance (SSR) and how? In this paper, this capability of a large scale PV plant is investigated. The IEEE Second Benchmark Model aggregated with a PV plant is utilized as the case study. A Wide Area Measurement System (WAMS) based conventional damping controller is designed and added to the main control loop of PV plant in order to damp the SSR and also investigation of the destructive effect of time delay in remote feedback signal. A new optimization algorithm called teaching-learning-based-optimization (TLBO) algorithm has been used for managing the optimization problems. Fast Furrier Transformer (FFT) analysis and also transient simulations of detailed nonlinear system are considered to investigate the performance of the controller. Robustness of the proposed system has been analyzed by facing the system with disturbances leading to significant changes in generator and power system operating point, fault duration time and PV plant generated power. All the simulations are carried out in MATLAB/SIMULINK environment.
机译：对清洁和可再生能源的日益增长的需求已导致全世界传输电压级光伏（PV）工厂的快速发展。这些大型光伏电站将与电力系统连接，应研究的重要课题之一是这些电站对电力系统稳定性的影响。大型光伏电站能否帮助抑制次同步谐振（SSR）？如何实现？本文研究了大型光伏电站的这种能力。将与光伏电站集成的IEEE第二基准模型作为案例研究。设计了基于广域测量系统（WAMS）的传统阻尼控制器，并将其添加到光伏电站的主控制回路中，以阻尼SSR并研究远程反馈信号中的时间延迟的破坏性影响。一种新的优化算法，称为基于教学学习的优化（TLBO）算法，已用于管理优化问题。考虑使用快速傅立叶变压器（FFT）分析以及详细非线性系统的瞬态仿真来研究控制器的性能。通过对系统进行干扰来分析所提出系统的鲁棒性，该干扰会导致发电机和电力系统的工作点，故障持续时间以及光伏电站的发电量发生重大变化。所有仿真均在MATLAB / SIMULINK环境中进行。

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