Mishra Akhilesh Kumar, Mishra Puneet, Mathur H D
Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, Pilani Campus, Rajasthan, 333031, India.
ISA Trans. 2023 Nov;142:20-39. doi: 10.1016/j.isatra.2023.07.009. Epub 2023 Jul 12.
The wind turbine generators (WTG's) incapability of primary frequency support during system contingencies due to its decoupled nature from the system frequency causes profound integration and stability issues. The present study focuses on resolving such issues by enabling the WTGs to participate in long-term frequency support under the derated operation of WTGs. The deloading operation of WTGs can provide a specific reserve power margin by reducing its rotor speed, which can be utilized during system contingencies. In literature, linear and quadratic deloading techniques have been proposed but these fail to replicate the nonlinear characteristics of the WTG accurately, thereby making deloading ineffective. To effectively implement the deloading, this work uses a more-accurate higher-order Newton's interpolation polynomial (HNIP), to cope with the highly nonlinear characteristics of WTG. The proposed deloading approach is also augmented with a fuzzy-based intelligent supplementary control structure to handle the inherent and incorporated nonlinearities in WTG. The microgrid system, consisting of a conventional energy source with WTG, has been considered as system under investigation. The integral time absolute error for step wind profile and variable speed wind profile was found to be improved by 97.65% and 97.29%, respectively, with the proposed novel deloading technique with fuzzy-PID compared to PID. Further, to ensure the implementation viability of the proposed control scheme, real-time validation of the same is carried out on OPAL-RT 4510, having a Xilinx Kintex-7 FPGA board. It was found that for all the scenarios considered for real-time digital simulation purposes, the results unerringly matched with MATLAB/Simulink.
由于风力发电机组（WTG）与系统频率解耦，在系统突发事件期间无法提供一次频率支持，这引发了严重的并网和稳定性问题。本研究致力于通过使风力发电机组在降额运行状态下参与长期频率支持来解决此类问题。风力发电机组的卸载运行可通过降低其转子速度提供特定的备用功率裕度，该功率裕度可在系统突发事件期间加以利用。在文献中，已提出线性和二次卸载技术，但这些技术无法准确再现风力发电机组的非线性特性，从而导致卸载无效。为有效实施卸载，本工作采用更精确的高阶牛顿插值多项式（HNIP）来应对风力发电机组的高度非线性特性。所提出的卸载方法还增加了基于模糊的智能辅助控制结构，以处理风力发电机组固有的和引入的非线性。由带有风力发电机组的传统能源组成的微电网系统被视为研究对象。与PID相比，采用所提出的带有模糊-PID的新型卸载技术时，阶跃风速剖面和变速风速剖面的积分时间绝对误差分别提高了97.65%和97.29%。此外，为确保所提出控制方案的实施可行性，在配备Xilinx Kintex-7 FPGA板的OPAL-RT 4510上对其进行了实时验证。结果发现，对于所有用于实时数字仿真的场景，结果与MATLAB/Simulink完全匹配。
