摘 要
随着能源结构转型和可再生能源的广泛接入，电力系统运行环境日益复杂，传统调度方式已难以满足现代电网高效、灵活与安全的需求。为此，本文聚焦于智能调度系统的开发与应用，旨在通过融合先进的人工智能技术与优化算法，提升电力系统的运行效率与稳定性。研究以数据驱动为核心，结合深度学习、强化学习及多智能体协同等方法，构建了一种具备自适应能力的智能调度框架。该框架能够实时处理大规模电力数据，预测负荷波动，并优化发电机组的出力分配。实验结果表明，所提出的智能调度系统在降低系统运行成本、提高新能源消纳率以及增强电网抗扰动能力等方面表现出显著优势。相较于传统调度策略，其综合性能提升了约15%-20%。此外，本文创新性地引入了场景感知机制，使调度决策更加贴合实际运行需求，从而为复杂电力系统的智能化管理提供了新思路。研究成果不仅验证了智能调度技术的可行性和有效性，还为未来电力系统的升级与发展奠定了理论与实践基础。关键词：智能调度系统；电力系统优化；数据驱动方法；场景感知机制；新能源消纳率
Abstract
With the transformation of energy structures and the widespread integration of renewable energy, the operating environment of power systems has become increasingly complex, making traditional dispatching methods insufficient to meet the demands of modern grids for efficiency, flexibility, and security. In response, this study focuses on the development and application of intelligent dispatching systems, aiming to enhance the operational efficiency and stability of power systems by integrating advanced artificial intelligence technologies and optimization algorithms. Centered on a data-driven approach, the research combines deep learning, reinforcement learning, and multi-agent collaboration to construct an adaptive intelligent dispatching fr amework. This fr amework is capable of real-time processing of large-scale power data, forecasting load fluctuations, and optimizing the output allocation of generating units. Experimental results demonstrate that the proposed intelligent dispatching system exhibits significant advantages in reducing system operation costs, improving the accommodation rate of new energy, and enhancing the grid's disturbance resistance capability, with an overall performance improvement of approximately 15%-20% compared to conventional dispatching strategies. Furthermore, this paper innovatively introduces a scenario-aware mechanism, enabling dispatching decisions to better align with actual operational requirements and providing new insights into the intelligent management of complex power systems. The research not only verifies the feasibility and effectiveness of intelligent dispatching technology but also lays a theoretical and practical foundation for the future upgrading and development of power systems..
Key Words：Intelligent Scheduling System；Power System Optimization；Data-Driven Method；Scenario-Aware Mechanism；New Energy Accommodation Rate
目 录
摘 要 I
Abstract II
第1章 绪论 1
1.1 电力系统智能调度的研究背景 1
1.2 智能调度系统开发的意义与价值 1
1.3 国内外研究现状分析 2
1.4 本文研究方法与技术路线 2
第2章 智能调度系统的需求分析与设计框架 3
2.1 电力系统调度的核心需求 3
2.2 智能调度系统的功能定位 3
2.3 系统架构设计原则与方法 4
2.4 关键技术选型与实现路径 4
2.5 需求分析对系统设计的指导作用 5
第3章 智能调度算法与优化策略的研究 6
3.1 常见调度算法的比较与选择 6
3.2 智能优化算法在调度中的应用 6
3.3 数据驱动的调度模型构建 7
3.4 实时调度与预测调度的融合机制 7
3.5 算法性能评估与改进方向 8
第4章 智能调度系统的实施与效果评估 9
4.1 系统开发与部署流程 9
4.2 实际案例中的应用分析 9
4.3 调度效率与经济性的提升效果 10
4.4 系统运行中的问题与解决方案 10
4.5 智能调度系统的未来发展方向 11
结 论 11
参考文献 13
致 谢 14
