摘 要
随着分布式能源和储能技术的发展，微电网作为智能电网的重要组成部分，在提高电力系统灵活性、可靠性和经济性方面具有重要意义。本研究针对微电网能量管理系统的优化设计展开深入探讨，旨在构建高效、稳定的能量管理系统以实现微电网的最优运行。通过引入多目标优化算法，结合预测模型与实时控制策略，提出了一种基于混合整数线性规划的能量管理框架，该框架能够同时考虑经济成本最小化和环境效益最大化。研究创新性地将深度学习算法应用于负荷预测及可再生能源出力预测中，显著提高了预测精度。仿真结果表明，所提出的优化算法在不同工况下均能有效降低运营成本约15%，并减少碳排放量达20%以上。此外，本研究还开发了适用于多种应用场景的通用型能量管理平台，为微电网的实际应用提供了强有力的技术支持，对推动微电网技术发展具有重要价值。
关键词：微电网能量管理；多目标优化算法；混合整数线性规划
Abstract
With the development of distributed energy and energy storage technologies, microgrids, as a crucial component of smart grids, play a significant role in enhancing the flexibility, reliability, and economic efficiency of power systems. This study delves into the optimal design of microgrid energy management systems (EMS) to establish an efficient and stable EMS for optimal microgrid operation. By introducing multi-ob jective optimization algorithms and integrating predictive models with real-time control strategies, a hybrid integer linear programming-based energy management fr amework is proposed, which simultaneously considers minimizing economic costs and maximizing environmental benefits. Innovatively, deep learning algorithms are applied to load forecasting and renewable energy output prediction, significantly improving prediction accuracy. Simulation results demonstrate that the proposed optimization algorithm effectively reduces operational costs by approximately 15% and decreases carbon emissions by over 20% across various operating conditions. Furthermore, this research develops a versatile energy management platform applicable to multiple scenarios, providing robust technical support for practical microgrid applications and contributing significantly to the advancement of microgrid technology.
Keywords: Microgrid Energy Management；Multi-ob jective Optimization Algorithm；Mixed-Integer Linear Programming
目 录
引言 1
一、微电网能量管理基础理论 1
（一）微电网系统架构分析 1
（二）能量管理基本原理 2
（三）关键技术综述 2
二、能量管理系统设计方法 2
（一）设计目标与约束条件 3
（二）系统架构设计原则 3
（三）关键模块功能设计 4
三、优化算法研究与应用 4
（一）常用优化算法比较 4
（二）算法适应性分析 5
（三）优化模型构建 5
四、系统性能评估与验证 6
（一）评估指标体系建立 6
（二）实验平台搭建 6
（三）测试结果分析 7
结 论 7
致 谢 9
参考文献 10
随着分布式能源和储能技术的发展，微电网作为智能电网的重要组成部分，在提高电力系统灵活性、可靠性和经济性方面具有重要意义。本研究针对微电网能量管理系统的优化设计展开深入探讨，旨在构建高效、稳定的能量管理系统以实现微电网的最优运行。通过引入多目标优化算法，结合预测模型与实时控制策略，提出了一种基于混合整数线性规划的能量管理框架，该框架能够同时考虑经济成本最小化和环境效益最大化。研究创新性地将深度学习算法应用于负荷预测及可再生能源出力预测中，显著提高了预测精度。仿真结果表明，所提出的优化算法在不同工况下均能有效降低运营成本约15%，并减少碳排放量达20%以上。此外，本研究还开发了适用于多种应用场景的通用型能量管理平台，为微电网的实际应用提供了强有力的技术支持，对推动微电网技术发展具有重要价值。
关键词：微电网能量管理；多目标优化算法；混合整数线性规划
Abstract
With the development of distributed energy and energy storage technologies, microgrids, as a crucial component of smart grids, play a significant role in enhancing the flexibility, reliability, and economic efficiency of power systems. This study delves into the optimal design of microgrid energy management systems (EMS) to establish an efficient and stable EMS for optimal microgrid operation. By introducing multi-ob jective optimization algorithms and integrating predictive models with real-time control strategies, a hybrid integer linear programming-based energy management fr amework is proposed, which simultaneously considers minimizing economic costs and maximizing environmental benefits. Innovatively, deep learning algorithms are applied to load forecasting and renewable energy output prediction, significantly improving prediction accuracy. Simulation results demonstrate that the proposed optimization algorithm effectively reduces operational costs by approximately 15% and decreases carbon emissions by over 20% across various operating conditions. Furthermore, this research develops a versatile energy management platform applicable to multiple scenarios, providing robust technical support for practical microgrid applications and contributing significantly to the advancement of microgrid technology.
Keywords: Microgrid Energy Management；Multi-ob jective Optimization Algorithm；Mixed-Integer Linear Programming
目 录
引言 1
一、微电网能量管理基础理论 1
（一）微电网系统架构分析 1
（二）能量管理基本原理 2
（三）关键技术综述 2
二、能量管理系统设计方法 2
（一）设计目标与约束条件 3
（二）系统架构设计原则 3
（三）关键模块功能设计 4
三、优化算法研究与应用 4
（一）常用优化算法比较 4
（二）算法适应性分析 5
（三）优化模型构建 5
四、系统性能评估与验证 6
（一）评估指标体系建立 6
（二）实验平台搭建 6
（三）测试结果分析 7
结 论 7
致 谢 9
参考文献 10
