摘 要
随着可再生能源大规模接入和电力电子设备广泛应用，智能电网面临保护与控制的重大挑战。本研究针对传统保护系统难以适应新型电力系统动态特性的问题，提出了一种基于多源信息融合的自适应保护与协调控制策略。通过构建包含分布式电源、储能系统和负荷的典型配电网模型，采用改进的深度强化学习算法实现保护定值的自适应整定，并设计了基于模糊逻辑的协调控制器以优化系统运行状态。研究结果表明，所提出的策略能够有效识别故障类型并快速隔离故障区域，在多种运行场景下均表现出良好的适应性，与传统方法相比故障处理时间缩短约35%，系统可靠性提升22%。
关键词：智能电网 自适应保护 多源信息融合
Abstract
With the large-scale access of renewable energy and the widespread application of power electronic equipment, smart grids face major challenges in protection and control. Aiming at the traditional protection system is difficult to adapt to the dynamic characteristics of the new power system, we propose an adaptive protection and coordination control strategy based on multi-source information fusion. By constructing a typical distribution network model including distributed power supply, energy storage system and load, the improved deep reinforcement learning algorithm is adopted to realize the adaptive setting of fixed protection value, and the coordination controller based on fuzzy logic is designed to optimize the operation state of the system. The results show that the proposed strategy can effectively identify the fault types and quickly isolate the fault areas, and shows good adaptability in various operation scenarios. Compared with the traditional method, the fault handling time is shortened by about 35%, and the system reliability is improved by 22%.
Keyword: Smart grid Adaptive protection Multi-source information fusion
目 录
1绪论 1
1.1研究背景与意义 1
1.2研究现状 1
1.3本文研究方法与技术路线 1
2智能电网故障特征分析与识别方法 2
2.1智能电网典型故障特征分析 2
2.2基于深度学习的故障识别方法 2
2.3多源信息融合的故障诊断策略 3
3自适应保护系统架构与实现机制 4
3.1自适应保护系统总体架构设计 4
3.2保护定值在线整定算法研究 4
3.3保护动作特性自适应调整策略 5
4协调控制策略优化与性能评估 6
4.1多级保护协同工作机制研究 6
4.2基于博弈论的协调控制优化方法 6
4.3系统性能评估指标体系构建 7
5结论 7
参考文献 9
致谢 10
随着可再生能源大规模接入和电力电子设备广泛应用，智能电网面临保护与控制的重大挑战。本研究针对传统保护系统难以适应新型电力系统动态特性的问题，提出了一种基于多源信息融合的自适应保护与协调控制策略。通过构建包含分布式电源、储能系统和负荷的典型配电网模型，采用改进的深度强化学习算法实现保护定值的自适应整定，并设计了基于模糊逻辑的协调控制器以优化系统运行状态。研究结果表明，所提出的策略能够有效识别故障类型并快速隔离故障区域，在多种运行场景下均表现出良好的适应性，与传统方法相比故障处理时间缩短约35%，系统可靠性提升22%。
关键词：智能电网 自适应保护 多源信息融合
Abstract
With the large-scale access of renewable energy and the widespread application of power electronic equipment, smart grids face major challenges in protection and control. Aiming at the traditional protection system is difficult to adapt to the dynamic characteristics of the new power system, we propose an adaptive protection and coordination control strategy based on multi-source information fusion. By constructing a typical distribution network model including distributed power supply, energy storage system and load, the improved deep reinforcement learning algorithm is adopted to realize the adaptive setting of fixed protection value, and the coordination controller based on fuzzy logic is designed to optimize the operation state of the system. The results show that the proposed strategy can effectively identify the fault types and quickly isolate the fault areas, and shows good adaptability in various operation scenarios. Compared with the traditional method, the fault handling time is shortened by about 35%, and the system reliability is improved by 22%.
Keyword: Smart grid Adaptive protection Multi-source information fusion
目 录
1绪论 1
1.1研究背景与意义 1
1.2研究现状 1
1.3本文研究方法与技术路线 1
2智能电网故障特征分析与识别方法 2
2.1智能电网典型故障特征分析 2
2.2基于深度学习的故障识别方法 2
2.3多源信息融合的故障诊断策略 3
3自适应保护系统架构与实现机制 4
3.1自适应保护系统总体架构设计 4
3.2保护定值在线整定算法研究 4
3.3保护动作特性自适应调整策略 5
4协调控制策略优化与性能评估 6
4.1多级保护协同工作机制研究 6
4.2基于博弈论的协调控制优化方法 6
4.3系统性能评估指标体系构建 7
5结论 7
参考文献 9
致谢 10
