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Genetic Algorithm-Based Optimization of Overcurrent Relay Coordination for Improved Protection of DFIG Operated Wind Farms

机译:基于遗传算法的过电流继电保护优化,以保护双馈风电场

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摘要

Rigorous protection of wind power plants is a critical aspect of the electrical power protection engineering. A proper protection scheme must be planned thoroughly while designing the wind plants to provide safeguarding for the power components in case of fault occurrence. One of the conventional protection apparatus is overcurrent relay (OCR), which is responsible for protecting power systems from impending faults. However, the operation time of OCRs is relatively long and accurate coordination between these relays is convoluted. Moreover, when a fault occurs in wind farm-based power system, several OCRs operate instead of a designated relay to that particular fault location, which could result in unnecessary power loss and disconnection of healthy feeders out of the plant. Therefore, this article proposes a novel genetic algorithm (GA)-based optimization technique for proper coordination of the OCRs in order to provide improved protection of the wind farms. The GA optimization technique has several advantages over other intelligent algorithms, such as high accuracy, fast response, and most importantly, it is capable of achieving optimal solutions considering nonlinear characteristics of OCRs. In this article, the improvement in protection of wind farm is achieved through optimizing the relay settings, reducing their operation time, time setting multiplier of each relay, improving the coordination between relays after implementation of IEC 60255-151:2009 standard. The developed algorithm is tested in simulation for a wind farm model under various fault conditions at random buses and the results are compared with the conventional nonlinear optimization method. It is found that the new approach achieves significant improvement 10.1109/TIA.2019.2939244 in the operation of OCRs for the wind farm and drastically reduces the accumulative operation time of the relays.
机译:严格保护风力发电厂是电力保护工程的关键方面。在设计风力发电厂时,必须彻底计划适当的保护方案,以在发生故障时为功率组件提供保护。常规保护装置之一是过电流继电器(OCR),它负责保护电力系统免受即将发生的故障的影响。但是,OCR的工作时间相对较长,并且这些继电器之间的精确协调令人费解。此外,当基于风电场的电力系统发生故障时,多个OCR会代替指定的继电器运行到该特定故障位置,这可能会导致不必要的功率损耗以及健康馈线从工厂中断开。因此,本文提出了一种新颖的基于遗传算法(GA)的优化技术,用于OCR的适当协调,以便为风电场提供更好的保护。与其他智能算法相比,GA优化技术具有多个优势,例如精度高,响应速度快,最重要的是,考虑到OCR的非线性特性,它可以实现最佳解决方案。在本文中,通过优化继电器设置,减少继电器的运行时间,每个继电器的时间设置倍数,提高继电器之间的协调性(IEC 60255-151:2009标准),可以实现对风电场保护的改进。在随机总线上的各种故障条件下,针对风电场模型在仿真中测试了开发的算法,并将结果与​​常规非线性优化方法进行了比较。发现该新方法在风电场的OCR运行中实现了10.1109 / TIA.2019.2939244的显着改进,并大大减少了继电器的累积运行时间。

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