摘 要
电力系统稳定性是保障现代能源供应安全可靠运行的关键问题，随着新能源接入比例增加及电网规模不断扩大，传统控制方法面临挑战。为此，本文聚焦电力系统稳定性分析与智能控制策略研究，旨在构建适应复杂电网环境的稳定控制体系。通过引入深度学习算法与强化学习模型，提出一种基于数据驱动的智能预测与优化控制框架，实现对电力系统动态行为的精准建模与实时调控。研究结果表明，所提出的智能控制策略能够有效提升系统的暂态稳定性和电压稳定性，在大规模风电接入场景下展现出优越性能。该方法不仅克服了传统控制手段依赖精确数学模型的局限性，还实现了对不确定因素的有效应对，为未来智能电网建设提供了理论依据和技术支持，具有重要的工程应用价值和广阔的发展前景。
关键词：电力系统稳定性；智能控制；深度学习
Abstract
The stability of the power system is a key issue to ensure the safe and reliable operation of the modern energy supply. With the increase of the proportion of new energy access and the continuous expansion of the power grid scale, the traditional control methods are facing challenges. Therefore, this paper focuses on the stability analysis of power system and intelligent control strategy research, aiming to build a stable control system adapted to the complex power grid environment. By introducing the deep learning algorithm and reinforcement learning model, a data-driven intelligent prediction and optimization control fr amework is proposed to realize the accurate modeling and real-time regulation of the dynamic behavior of the power system. The results show that the proposed intelligent control strategy can effectively improve the transient stability and voltage stability of the system, and show superior performance in large-scale wind power access scenarios. This method not only overcomes the limitations of the traditional control means relying on the precise mathematical model, but also realizes the effective response of the uncertain factors, provides theoretical basis and technical support for the future construction of smart grid, and has important engineering application value and broad development prospect.
Keywords: Power system stability; intelligent control; deep learning
目 录
1 引言 1
2 电力系统稳定性基础理论 1
2.1 稳定性定义与分类 1
2.2 小扰动稳定性分析 1
2.3 大扰动稳定性研究 2
3 电力系统建模与仿真 3
3.1 系统数学模型构建 3
3.2 暂态稳定仿真分析 3
3.3 动态特性模拟研究 3
4 智能控制策略设计 4
4.1 控制算法原理探讨 4
4.2 基于AI的控制方法 5
4.3 实时控制策略优化 5
5 稳定性评估与应用实例 6
5.1 评估指标体系建立 6
5.2 工程案例分析研究 6
5.3 应用效果综合评价 6
6 结论 7
致 谢 8
参考文献 9
电力系统稳定性是保障现代能源供应安全可靠运行的关键问题，随着新能源接入比例增加及电网规模不断扩大，传统控制方法面临挑战。为此，本文聚焦电力系统稳定性分析与智能控制策略研究，旨在构建适应复杂电网环境的稳定控制体系。通过引入深度学习算法与强化学习模型，提出一种基于数据驱动的智能预测与优化控制框架，实现对电力系统动态行为的精准建模与实时调控。研究结果表明，所提出的智能控制策略能够有效提升系统的暂态稳定性和电压稳定性，在大规模风电接入场景下展现出优越性能。该方法不仅克服了传统控制手段依赖精确数学模型的局限性，还实现了对不确定因素的有效应对，为未来智能电网建设提供了理论依据和技术支持，具有重要的工程应用价值和广阔的发展前景。
关键词：电力系统稳定性；智能控制；深度学习
Abstract
The stability of the power system is a key issue to ensure the safe and reliable operation of the modern energy supply. With the increase of the proportion of new energy access and the continuous expansion of the power grid scale, the traditional control methods are facing challenges. Therefore, this paper focuses on the stability analysis of power system and intelligent control strategy research, aiming to build a stable control system adapted to the complex power grid environment. By introducing the deep learning algorithm and reinforcement learning model, a data-driven intelligent prediction and optimization control fr amework is proposed to realize the accurate modeling and real-time regulation of the dynamic behavior of the power system. The results show that the proposed intelligent control strategy can effectively improve the transient stability and voltage stability of the system, and show superior performance in large-scale wind power access scenarios. This method not only overcomes the limitations of the traditional control means relying on the precise mathematical model, but also realizes the effective response of the uncertain factors, provides theoretical basis and technical support for the future construction of smart grid, and has important engineering application value and broad development prospect.
Keywords: Power system stability; intelligent control; deep learning
目 录
1 引言 1
2 电力系统稳定性基础理论 1
2.1 稳定性定义与分类 1
2.2 小扰动稳定性分析 1
2.3 大扰动稳定性研究 2
3 电力系统建模与仿真 3
3.1 系统数学模型构建 3
3.2 暂态稳定仿真分析 3
3.3 动态特性模拟研究 3
4 智能控制策略设计 4
4.1 控制算法原理探讨 4
4.2 基于AI的控制方法 5
4.3 实时控制策略优化 5
5 稳定性评估与应用实例 6
5.1 评估指标体系建立 6
5.2 工程案例分析研究 6
5.3 应用效果综合评价 6
6 结论 7
致 谢 8
参考文献 9
