摘 要
随着分布式能源在电力系统中的渗透率不断提高，传统集中式负荷优化方法难以适应新的运行需求。为解决这一问题，本文提出一种基于多代理系统的分布式能源协调控制方法，旨在实现电力系统负荷的高效优化。该方法通过构建包含多个代理节点的网络架构，每个代理负责特定区域内的分布式能源管理，并通过信息交互实现全局协同优化。研究采用改进的粒子群算法对各代理节点进行参数优化，确保系统整体性能最优。仿真结果表明，在不同工况下，所提方法能够有效降低系统峰谷差，提高可再生能源消纳能力，减少弃风弃光现象。与传统方法相比，该方法不仅提高了系统运行效率，还增强了系统的灵活性和鲁棒性。创新点在于首次将多代理系统与分布式能源优化相结合，提出了适用于复杂电网环境的新型协调控制策略，为未来智能电网的发展提供了理论支持和技术参考。通过对实际案例的分析验证了该方法的有效性和实用性，为分布式能源的大规模接入提供了可靠的解决方案，推动了电力系统向更加智能化、绿色化方向发展。
关键词：分布式能源优化 多代理系统 粒子群算法
Abstract
With the increasing penetration of distributed energy resources (DERs) in power systems, traditional centralized load optimization methods struggle to meet new operational requirements. To address this challenge, this paper proposes a multi-agent system (MAS)-based coordinated control method for DERs, aiming to achieve efficient load optimization in power systems. This approach constructs a network architecture comprising multiple agent nodes, where each agent is responsible for managing DERs within its designated area and achieves global协同 optimization through information exchange. The study employs an improved particle swarm optimization (PSO) algorithm to optimize parameters for each agent node, ensuring optimal overall system performance. Simulation results demonstrate that under various operating conditions, the proposed method effectively reduces peak-to-valley differences, enhances renewable energy accommodation, and minimizes curtailment of wind and solar power. Compared with traditional methods, this approach not only improves system operational efficiency but also enhances flexibility and robustness. The innovation lies in the first integration of MAS with DER optimization, proposing a novel coordinated control strategy suitable for complex grid environments, providing theoretical support and technical reference for the development of future smart grids. Analysis of practical cases verifies the effectiveness and practicality of this method, offering a reliable solution for large-scale integration of DERs and promoting the development of power systems towards more intelligent and greener directions.
Keyword:Distributed Energy Optimization Multi-Agent System Particle Swarm Algorithm
目 录
1绪论 1
1.1电力系统负荷优化背景与意义 1
1.2分布式能源协调控制研究现状 1
1.3本文研究方法概述 2
2分布式能源接入对负荷特性的影响 2
2.1分布式电源出力特性分析 2
2.2负荷需求响应机制探讨 3
2.3分布式能源与负荷互动模式 3
3分布式能源协调控制策略设计 4
3.1控制目标与约束条件 4
3.2多时间尺度协调控制框架 5
3.3关键控制算法研究 5
4分布式能源协调控制应用案例 6
4.1实际系统建模与仿真 6
4.2案例分析与结果评价 6
4.3策略优化与改进建议 7
结论 8
参考文献 9
致谢 10
