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面向时延与网络故障的交流微电网分布式多尺度注意力与预测器协同控制

Distributed Multi-scale Attention and Predictor-based Control for AC Microgrids with Time Delays and Cyber Failures

作者
期刊 现代电力系统通用与清洁能源学报
出版日期 2025年9月
卷/期 第 2025 卷 第 5 期
技术分类 控制与算法
技术标签 微电网 模型预测控制MPC 深度学习 下垂控制
相关度评分 ★★★★ 4.0 / 5.0
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中文摘要

本文提出分布式多尺度注意力与预测器协同控制(DMAPC)策略,应对微电网中虚假数据注入攻击、丢包及通信时延问题;通过多尺度注意力机制动态加权邻居状态,结合数据驱动预测器补偿丢失信息,系统被证明一致最终有界。

English Abstract

Distributed secondary control has been proposed to maintain frequency/voltage synchronization and power sharing for distributed energy sources in AC microgrids(MGs).The cy-ber layer is susceptible to time delays and cyber failures and thus,a distributed resilient secondary control should be investi-gated.This paper proposes a distributed multi-scale attention and predictor-based control(DMAPC)strategy to address false data injection attacks and packet loss failures with time delays.The multi-scale attention mechanism enables the system to selec-tively focus on neighbors' states with higher confidence evaluat-ed in different time scales,while the data-driven predictor com-pensates for lost neighbors' states in the nonlinear controller.The DMAPC does not impose strict limitations on the number of false communication links or upper bound for false data.Be-sides,the DMAPC is formulated as an uncertain system with time delays and is proven to be uniformly ultimately bounded.Extensive experiments on a hardware-in-the-loop MG testbed have validated the effectiveness of DMAPC,which successfully relaxes restrictions on cyber failures compared to existing strat-egies.
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SunView 深度解读

该研究对阳光电源ST系列储能变流器(PCS)及PowerTitan大型储能系统的微电网级协同控制具有重要参考价值。其DMAPC算法可增强iSolarCloud平台在弱通信条件下的多机协调鲁棒性,尤其适用于偏远地区光储微网或离网场景。建议将多尺度注意力机制嵌入ST-125K/250K PCS的二次调频模块,并与PowerTitan的EMS联合验证,提升其在高时延、低可靠通信环境(如4G/LoRa)下的故障自愈能力。