摘 要
随着全球能源转型和可再生能源渗透率的提升，电力系统正面临前所未有的复杂性和不确定性挑战，其稳定性问题已成为制约电网安全运行的关键因素。本研究旨在深入分析现代电力系统的动态特性，并提出有效的控制策略以保障其稳定运行。通过结合非线性动力学理论与现代优化算法，构建了适用于高比例可再生能源接入场景下的电力系统稳定性评估模型，并提出了基于自适应控制和分布式协调优化的综合控制策略。研究结果表明，所提出的模型能够准确捕捉系统在不同工况下的动态行为，而新型控制策略则显著提升了系统的暂态稳定性和频率调节能力。此外，本研究首次将机器学习技术引入稳定性预测领域，实现了对潜在失稳风险的高效识别与预警，为实际工程应用提供了重要参考。总体而言，本研究不仅深化了对复杂电力系统稳定性的理解，还为未来智能电网的设计与运行提供了创新思路和技术支撑。
关键词：电力系统稳定性；可再生能源接入；自适应控制；分布式协调优化；机器学习预测
Abstract
With the global energy transition and increasing penetration of renewable energy, power systems are facing unprecedented challenges in complexity and uncertainty, and their stability issues have become a critical factor constraining the safe operation of grids. This study aims to conduct an in-depth analysis of the dynamic characteristics of modern power systems and propose effective control strategies to ensure stable operation. By integrating nonlinear dynamics theory with modern optimization algorithms, a power system stability evaluation model applicable to scenarios with high proportions of renewable energy integration is constructed, and a comprehensive control strategy based on adaptive control and distributed coordinated optimization is proposed. The results indicate that the proposed model can accurately capture the dynamic behavior of the system under various operating conditions, while the novel control strategy significantly enhances the system's transient stability and frequency regulation capability. Moreover, this study is the first to introduce machine learning techniques into the field of stability prediction, achieving efficient identification and early warning of potential instability risks, thereby providing important references for practical engineering applications. Overall, this research not only deepens the understanding of the stability of complex power systems but also offers innovative ideas and technical support for the design and operation of future smart grids.
Keywords: Power System Stability；Renewable Energy Integration；Adaptive Control；Distributed Coordinated Optimization；Machine Learning Prediction
目 录
摘 要 I
Abstract II
一、绪论 1
（一）电力系统稳定性研究背景与意义 1
（二）国内外研究现状分析 1
（三）本文研究方法与技术路线 1
二、电力系统稳定性基础理论 2
（一）稳定性定义与分类 2
（二）关键影响因素分析 3
（三）数学建模与仿真方法 3
三、电力系统稳定性分析方法 4
（一）小扰动稳定性分析 4
（二）大扰动稳定性评估 4
（三）暂态稳定性计算方法 5
四、电力系统控制策略研究 5
（一）控制策略的基本框架 5
（二）基于反馈的稳定性控制 6
（三）智能优化算法在控制中的应用 6
结 论 7
致 谢 8
参考文献 9
