Grey wolf optimization-based fuzzy-PID controller for load frequency control in multi-area power systems

Md. Faiyaj Ahmed Limon , Rhydita Shahrin Upoma , Nomita Sinha , Shristi Roy Swarna , Bidyut Kanti Nath , Kulsuma Khanum , Md. Jubaer Rahman , Md. Shahid Iqbal
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Abstract

This study develops a GWO-optimized cascaded fuzzy-PID controller with triangular membership functions for load frequency control in interconnected power systems. The controller’s effectiveness is demonstrated on thermal–thermal and hybrid thermal–hydro–gas power systems. The controller parameters were tuned using the Integral Time Absolute Error (ITAE) objective function, which was also evaluated alongside other objective functions (IAE, ISE, and ITSE) to ensure high precision in frequency stabilization. To validate the effectiveness of the triangular membership function, comparisons were made with fuzzy-PID controllers employing trapezoidal and Gaussian membership functions. Performance metrics, including ITAE, settling time, overshoot, and undershoot of frequency deviation, as well as tie-line power deviation, were evaluated. Robustness was established through a comprehensive sensitivity analysis with TG, TT, and TR parameter variations (±50%), a non-linearity analysis incorporating Generation Rate Constraint (GRC) and Governor Deadband (GDB), a random Step Load Perturbation (SLP) over 0–100 s, and also Stability analysis of the proposed scheme is conducted using multiple approaches, including frequency-domain analysis, Lyapunov stability theory, and eigenvalue analysis. Additionally, the system incorporating thermal, hydro, and gas turbines, along with advanced components like CES and HVDC links, was analysed. Comparisons were conducted against controllers optimized using Modified Grasshopper Optimization Algorithm (MGOA), Honey Badger Algorithm (HBA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Spider Monkey Optimization (SMO) algorithms. Results demonstrate that the GWO-based fuzzy-PID controller outperforms the alternatives, exhibiting superior performance across all evaluated metrics. This highlights the potential of the proposed approach as a robust solution for load frequency control in complex and dynamic power systems.
基于灰狼优化的多区域电力系统负荷频率模糊pid控制
本文提出了一种三角隶属函数级联模糊pid控制器,用于互联电力系统的负荷频率控制。在热电-热电和热电-水气混合动力系统中验证了该控制器的有效性。控制器参数使用积分时间绝对误差(ITAE)目标函数进行调整,并与其他目标函数(IAE, ISE和ITSE)一起进行评估,以确保高精度的频率稳定。为了验证三角隶属函数的有效性,将其与采用梯形和高斯隶属函数的模糊pid控制器进行了比较。评估了性能指标,包括ITAE、稳定时间、频率偏差的超调和过调,以及连接线功率偏差。通过TG、TT和TR参数变化(±50%)的综合灵敏度分析,结合发电速率约束(GRC)和调控死带(GDB)的非线性分析,0-100 s的随机阶跃负载扰动(SLP),建立了鲁棒性,并使用频域分析、李雅普诺夫稳定性理论和特征值分析等多种方法对所提出的方案进行了稳定性分析。此外,还对该系统进行了分析,该系统包括热轮机、水力轮机和燃气轮机,以及像CES和HVDC链接这样的先进组件。与改进的Grasshopper Optimization Algorithm (MGOA)、Honey Badger Algorithm (HBA)、Particle Swarm Optimization (PSO)、Artificial Bee Colony (ABC)和Spider Monkey Optimization (SMO)算法优化的控制器进行了比较。结果表明,基于gwo的模糊pid控制器优于替代方案,在所有评估指标中表现出优异的性能。这突出了所提出的方法作为复杂和动态电力系统中负载频率控制的鲁棒解决方案的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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