基于软件定义技术的微电网优化运行研究

Optimization Operation of Microgrids Based on Software-Defined Technology

摘要

在“双碳”目标与新型电力系统建设的双重驱动下，微电网研究亟需探究微电网多元分层协同运行新模式，提高动态电价响应与碳减排协同优化．为此，本文提出基于软件定义技术的微电网分层优化调度框架，通过“动态电价-阶梯碳交易”联合模型与改进智能算法，实现低碳经济运行．构建软件定义分层架构：变换设备层建立风、光、储精细化模型，制订微网各分布式电源(DER)控制策略；控制功能层设计 RS-485 与 MODBUS 协议实时通信系统，保障微网稳定运行、调度指令可靠传输；协同运行层融合动态电价与阶梯碳成本约束，建立以运行成本与碳排放最小化为目标的多目标优化模型，集成功率平衡、储能约束等条件，并提出改进多目标粒子群优化(PSO)算法，形成经济-低碳双重激励机制，同时设计上位机界面，提供可视化的监控和操作界面．仿真结果表明：动态电价与阶梯碳交易协同机制使微电网运行成本降低 44.9%，碳排放减少 16.3%；改进 PSO 算法在收敛速度提升 42%的同时，求解精度和稳定性显著提高．Simulink 底层仿真验证了风、光、储出力对优化指令的精准跟踪能力，人机交互界面对 DER 实时出力检测，证实软件定义架构的物理可行性．该研究为新型电力系统下微电网低碳经济调度提供了兼具理论与实用价值的解决方案，助力能源互联网多能协同优化．

Abstract

Under the drivers of the “dual-carbon” goals and the construction of a new power system，research on microgrids must urgently explore novel，multi-level collaborative operation modes to enhance synergy between dynamic electricity price response and carbon emission reduction. For this purpose，this paper proposes a hierarchical optimal scheduling framework for microgrids based on software-defined technology，achieving low-carbon and low-cost operations through a joint “dynamic electricity price-tiered carbon trading” model and improved intelligent algorithms. A software-defined hierarchical architecture is constructed as follows. Conversion device layer：in this layer，detailed models for wind，photovoltaic(PV)，and storage systems are established and control strategies for distributed energy resources(DER) in the microgrid are formulated. Control function layer：in this layer，a real-time communication system based on the RS-485 and MODBUS protocols is designed to ensure stable microgrid operations and reliable transmission of scheduling commands. Collaborative operation layer：in this layer，dynamic electricity price and tiered carbon cost constraints are integrated to establish a multi-objective optimization model aimed at minimizing operation costs and carbon emissions. Power balance，energy storage constraints，and other operation conditions are incorporated，and an improved multi-objective particle swarm optimization(PSO) algorithm is proposed as a dual economic-low-carbon incentive mechanism. Additionally，an upper computer interface is designed to provide a visual monitoring and operation platform. The simulation results indicate that synergy between dynamic electricity price and tiered carbon trading reduces microgrid operation costs by 44.9% and carbon emissions by 16.3%. The improved PSO algorithm achieves a 42% increase in convergence speed while significantly enhancing solution accuracy and stability. Further，Simulink-based simulations verify the precise tracking capability of wind，PV，and storage output to optimization commands，whereas the human-machine interface enables real-time monitoring of DER outputs，confirming the physical feasibility of the software-defined architecture. This study provides a theoretically and practically viable solution for low-carbon and economic scheduling of microgrids in the context of new power systems，contributing to multi-energy collaborative optimization within the energy internet.

关键词

微电网 / 动态电价 / 碳交易机制 / 软件定义 / 能量管理

Key words

microgrid / dynamic electricity price / carbon trading mechanism / software definition / energy management

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基金资助

国家自然科学基金重点项目(U23A20654)