Energy and maximum control signal of controllers.

Maintaining stable voltage levels is essential for power systems’ efficiency and reliability. Voltage fluctuations during load changes can lead to equipment damage and costly disruptions. Automatic voltage regulators (AVRs) are traditionally used to address this issue, regulating generator terminal voltage. Despite progress in control methodologies, challenges persist, including robustness and response time limitations. Therefore, this study introduces a novel approach to AVR control, aiming to enhance robustness and efficiency. A custom optimizer, the quadratic wavelet-enhanced gradient-based optimization (QWGBO) algorithm, is developed. QWGBO refines the gradient-based optimization (GBO) by introducing exploration and exploitation improvements. The algorithm integrates quadratic interpolation mutation and wavelet mutation strategy to enhance search efficiency. Extensive tests using benchmark functions demonstrate the QWGBO’s effectiveness in optimization. Comparative assessments against existing optimization algorithms and recent techniques confirm QWGBO’s superior performance. In AVR control, QWGBO is coupled with a cascaded real proportional-integral-derivative with second order derivative (RPIDD2) and fractional-order proportional-integral (FOPI) controller, aiming for precision, stability, and quick response. The algorithm’s performance is verified through rigorous simulations, emphasizing its effectiveness in optimizing complex engineering problems. Comparative analyses highlight QWGBO’s superiority over existing algorithms, positioning it as a promising solution for optimizing power system control and contributing to the advancement of robust and efficient power systems.

维持电压稳定对于电力系统的运行效率与可靠性至关重要。负载变化过程中产生的电压波动，可能引发设备损坏与代价高昂的供电中断事故。传统上，自动电压调节器（Automatic Voltage Regulators, AVRs）被广泛应用于解决该类问题，通过调节发电机端电压实现稳压目标。尽管控制方法领域已取得诸多进展，但仍存在鲁棒性不足、响应时延受限等挑战。为此，本研究提出一种面向自动电压调节器控制的新型优化方法，旨在提升系统鲁棒性与运行效率。研究开发了一款定制化优化器——二次小波增强型基于梯度优化（Quadratic Wavelet-enhanced Gradient-based Optimization, QWGBO）算法。QWGBO通过对全局探索与局部开发机制进行优化改进，对基于梯度的优化（Gradient-based Optimization, GBO）算法进行了升级优化。该算法融合了二次插值变异与小波变异策略，以提升全局搜索效率。通过大量基准测试函数实验，验证了QWGBO在优化任务中的有效性。与现有优化算法及前沿技术的对比评估结果表明，QWGBO的综合性能更具优势。在自动电压调节器控制场景中，QWGBO与带二阶导数的级联式实际比例-积分-微分（Cascaded Real Proportional-Integral-Derivative with Second Order Derivative, RPIDD2）控制器及分数阶比例-积分（Fractional-order Proportional-Integral, FOPI）控制器相结合，以实现控制精度高、稳定性强与响应快速的优化目标。通过严谨的仿真实验验证了该算法的实际性能，凸显其在解决复杂工程优化问题中的有效性。对比分析进一步证实QWGBO优于现有同类算法，使其成为优化电力系统控制的极具潜力的解决方案，有助于推动鲁棒且高效的现代电力系统的发展。