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利用异构发电源和储能集成辅助的非线性控制,对孤岛海洋微电网进行前瞻性频率管理。

Forward-thinking frequency management in islanded marine microgrid utilizing heterogeneous source of generation and nonlinear control assisted by energy storage integration.

作者信息

P Odelu, Shiva Chandan Kumar, Sen Sachidananda, Basetti Vedik, Reddy Chandra Sekhar

机构信息

Department of Electrical and Electronics Engineering, SR University, Warangal, Telangana, 506371, India.

Department of Electrical Power and Control Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, Adama, Ethiopia.

出版信息

Sci Rep. 2025 Apr 21;15(1):13794. doi: 10.1038/s41598-025-97592-1.

Abstract

The increasing environmental challenges and global warming concerns have driven a shift towards renewable energy-based power generation, particularly in microgrids. However, marine microgrids face challenges in load-frequency regulation due to renewable energy intermittency, unpredictable load variations, and nonlinear system dynamics. Conventional control strategies often struggle with poor convergence, limited adaptability, and suboptimal frequency stabilization. Addressing these challenges requires an advanced control optimization technique for robust frequency regulation and system stability in dynamic marine environments. This study proposes a Chaotic Chimp-Mountain Gazelle Optimizer (CCMGO) for optimizing fractional-order proportional-integral-derivative (FOPID) controllers, enhancing load-frequency regulation in a multi-source marine microgrid. The system integrates wave energy, wind turbines, solar towers, and photovoltaic energy, along with controlled biogas turbines, micro hydro turbines, and bio-diesel engine generation. To improve frequency stability and grid flexibility, battery energy storage systems, ultra-capacitors, and electric vehicles are incorporated for dynamic compensation. The CCMGO algorithm combines the exploration strength of the mountain gazelle optimizer with solution diversity enhancements from chaotic mapping and chimp optimization algorithm, preventing premature convergence and improving control efficiency. The performance of CCMGO-optimized controllers (PID, PD-PID, FOPI-FOPID, and FOPID) is evaluated under various load conditions, including impulse, ramp, and stochastic disturbances, to test robustness and adaptability. Simulation results demonstrate that CCMGO-based FOPID controllers outperform conventional strategies, achieving lower frequency deviations, faster settling times, and enhanced transient response. These findings establish CCMGO-FOPID as a powerful tool for optimizing control performance in marine microgrids, ensuring greater resilience, stability, and energy efficiency.

摘要

日益严峻的环境挑战和对全球变暖的担忧推动了向基于可再生能源的发电方式转变,特别是在微电网领域。然而,由于可再生能源的间歇性、不可预测的负荷变化以及非线性系统动态特性,海洋微电网在负荷频率调节方面面临挑战。传统控制策略往往在收敛性差、适应性有限和频率稳定效果欠佳等方面存在困难。应对这些挑战需要一种先进的控制优化技术,以实现动态海洋环境中的鲁棒频率调节和系统稳定性。本研究提出了一种混沌黑猩猩 - 瞪羚优化器(CCMGO),用于优化分数阶比例积分微分(FOPID)控制器,增强多源海洋微电网中的负荷频率调节。该系统集成了波浪能、风力涡轮机、太阳能塔和光伏能源,以及可控沼气轮机、微型水轮机和生物柴油发动机发电。为提高频率稳定性和电网灵活性,还纳入了电池储能系统、超级电容器和电动汽车进行动态补偿。CCMGO算法将瞪羚优化器的探索能力与混沌映射和黑猩猩优化算法带来的解多样性增强相结合,防止过早收敛并提高控制效率。在包括脉冲、斜坡和随机干扰等各种负荷条件下,评估了CCMGO优化的控制器(PID、PD - PID、FOPI - FOPID和FOPID)的性能,以测试其鲁棒性和适应性。仿真结果表明,基于CCMGO的FOPID控制器优于传统策略,实现了更低的频率偏差、更快的调节时间和增强的瞬态响应。这些发现确立了CCMGO - FOPID作为优化海洋微电网控制性能的强大工具,确保了更高的弹性、稳定性和能源效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5095/12012169/7c5086bb4f93/41598_2025_97592_Fig1_HTML.jpg

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