摘 要
随着全球能源需求的持续增长和环境问题的日益严峻，智能电网作为现代电力系统的重要发展方向，为分布式能源的有效管理和高效利用提供了关键技术支撑。本研究旨在探索基于智能电网的分布式能源管理技术，以实现能源优化配置、提升系统运行效率及促进可再生能源的高比例接入。研究结合先进的信息通信技术和控制策略，提出了一种多层级分布式能源管理系统架构，通过数据采集与监控、负荷预测以及优化调度等核心功能模块的设计，实现了对分布式能源的精细化管理。在方法层面，引入了机器学习算法以提高负荷预测精度，并采用多目标优化模型解决分布式能源系统的复杂调度问题。实验结果表明，该系统能够显著降低能源损耗，提升可再生能源利用率，并有效平衡供需关系。研究的主要创新点在于将智能化技术与分布式能源管理深度融合，提出了适应性强且灵活性高的解决方案，为推动智能电网背景下的能源转型提供了重要参考。研究成果不仅验证了技术可行性，还为未来分布式能源管理技术的发展奠定了理论基础和实践依据。
关键词：智能电网；分布式能源管理；多目标优化；机器学习；负荷预测
Abstract
With the continuous growth of global energy demand and the increasing severity of environmental issues, smart grids, as a crucial development direction for modern power systems, provide key technological support for the effective management and efficient utilization of distributed energy resources. This study aims to explore distributed energy management technologies based on smart grids to achieve optimal energy allocation, enhance system operational efficiency, and facilitate high-proportion integration of renewable energy sources. By integrating advanced information and communication technologies with control strategies, a multi-level distributed energy management system architecture is proposed, which realizes refined management of distributed energy through the design of core functional modules such as data acquisition and monitoring, load forecasting, and optimized scheduling. At the methodological level, machine learning algorithms are introduced to improve the accuracy of load forecasting, and a multi-ob jective optimization model is employed to address complex scheduling problems in distributed energy systems. Experimental results demonstrate that the system can significantly reduce energy losses, increase the utilization rate of renewable energy, and effectively balance supply and demand relationships. The primary innovation of this research lies in the deep integration of intelligent technologies with distributed energy management, proposing a solution with strong adaptability and high flexibility, thereby providing significant reference for promoting energy transition under the context of smart grids. The research not only verifies the technical feasibility but also lays a theoretical foundation and practical basis for the future development of distributed energy management technologies.
Keywords: Smart Grid；Distributed Energy Management；Multi-ob jective Optimization；Machine Learning；Load Forecasting
目 录
摘 要 I
Abstract II
一、绪论 1
（一）智能电网与分布式能源管理的背景 1
（二）国内外研究现状分析 1
（三）本文研究方法与技术路线 2
二、智能电网中分布式能源接入技术 2
（一）分布式能源接入的关键技术 2
（二）接入技术对智能电网的影响 3
（三）典型分布式能源接入案例分析 3
三、分布式能源优化调度策略研究 4
（一）优化调度的基本原理与目标 4
（二）基于智能算法的调度模型构建 4
（三）实时调度与预测技术的结合 5
四、智能电网下分布式能源管理平台设计 5
（一）管理平台的功能需求分析 5
（二）数据采集与处理技术实现 6
（三）平台架构设计与性能评估 7
结 论 7
致 谢 9
参考文献 10
