摘 要
随着现代电力系统规模的不断扩大和分布式能源的广泛接入，传统集中式控制方法在应对复杂动态环境时逐渐暴露出局限性，因此基于多智能体系统的协同控制成为解决这一问题的有效途径本研究以提升电力系统运行效率与稳定性为目标，提出了一种基于多智能体系统的协同控制框架，通过将电力系统划分为多个自治区域并设计相应的智能体模型，实现了局部决策与全局优化的有机结合具体而言，研究采用强化学习算法对智能体进行训练，使其能够根据实时运行状态自主调整控制策略同时，引入通信机制以促进智能体间的信息共享，从而增强整体系统的协同能力仿真结果表明，所提出的控制方法能够在多种工况下显著提高系统的频率稳定性和负荷平衡性能此外，该方法还展现出较强的鲁棒性和适应性，可有效应对不确定性因素的影响。
关键词：多智能体系统 协同控制 强化学习
Abstract
With the increasing scale of modern power systems and the wide access of distributed energy sources, Traditional centralized control methods gradually expose their limitations in response to complex and dynamic environments, Therefore, the collaborative control based on multi-agent systems has become an effective way to solve this problem. This study aims at improving the operation efficiency and stability of the power system, Proposed a cooperative control fr amework based on multi-agent systems, By dividing the power system into multiple autonomous regions and designing the corresponding agent models, Realize the organic combination of local decision and global optimization specifically, Study uses reinforcement learning algorithms to train the agents, Enable it to independently adjust the control strategy according to the real-time running state and simultaneously, Introducing communication mechanisms to facilitate information sharing among agents, Thus enhancing the synergistic ability of the overall system, the simulation results show that, The proposed control method can significantly improve the frequency stability and load balance performance of the system under multiple working conditions. In addition, The method also demonstrated strong robustness and adaptability, Can effectively affect the uncertainty factors.
Keyword:Multi-Agent System Collaborative Control Reinforcement Learning
目 录
引言 1
1多智能体系统基础理论研究 1
1.1多智能体系统的基本概念 1
1.2多智能体系统的架构分析 2
1.3多智能体通信机制研究 2
1.4多智能体协同控制原理 3
2电力系统协同控制需求分析 3
2.1电力系统运行特性概述 3
2.2协同控制在电力系统中的作用 4
2.3电力系统协同控制的关键挑战 4
2.4多智能体技术的应用潜力 4
3基于多智能体的协同控制策略设计 5
3.1协同控制目标与约束条件 5
3.2分布式控制算法设计 5
3.3智能体决策模型构建 6
3.4控制策略的优化方法 6
4多智能体协同控制的仿真与验证 7
4.1仿真平台搭建与参数设置 7
4.2典型场景下的协同控制测试 7
4.3性能评估指标体系设计 8
4.4实验结果分析与讨论 8
结论 8
参考文献 10
致谢 11
