摘要
以福建省某县域西北部山区为示范区域,提出一种融合多时间尺度动态承载力评估、台区拓扑动态辨识、光伏柔性出力控制及虚拟储能协同优化的综合控制方法。通过在实际台区部署改进型BP神经网络与三相不平衡修正算法,评估高频率反向负载率;结合图卷积网络(GCN)与双向长短期记忆(LSTM)网络算法,动态识别复杂台区拓扑;在典型电压越限台区引入Q-V控制逆变器,并构建“台区-馈线-主变”三级分层调控体系;同时整合小水电与电动汽车储能资源,提升灵活可调的虚拟储能调节能力。经模拟环境下连续6个月的运行验证可知,10 kV线路反向负载率从90%降至78%,主变压器负载率从85%降至72%,末端电压偏差从+10.2%收敛至+6.5%,主网倒送功率下降65%。结果表明,该方法在提升配电网承载能力、缓解电压越限问题与优化源荷协调方面具有显著成效。
This paper takes a mountainous area in the northwest of a county in Fujian Province as a demonstration area and proposes a comprehensive control method that integrates multi-time-scale dynamic carrying capacity assessment,dynamic identification of transformer area topology,flexible photovoltaic output control,and collaborative optimization of virtual energy storage.By deploying an improved BP neural network and a three-phase unbalance correction algorithm in actual transformer areas,high-frequency reverse load rate assessment is achieved.Combined with Graph Convolutional Networks(GCN)and bidirectional Long Short-Term Memory(LSTM)network algorithms,the complex transformer area topology is dynamically identified.Q-V control inverters are introduced in typical voltage limit-exceeding transformer areas,and a three-level hierarchical control system of"transformer area-feeder-main transformer"is constructed.At the same time,small hydropower and electric vehicle energy storage resources are integrated to enhance a flexible and adjustable virtual energy storage regulation capacity.After continuous operation verification for six months in a simulation environment,there is a reduction in the reverse load rate of 10 kV lines from 90%to 78%,a decrease in the load rate of main transformers from 85%to 72%,a convergence of the terminal voltage deviation from+10.2%to+6.5%,and a 65%reduction in the reverse power flow of the main grid.The results show that this method has significant effects in enhancing the carrying capacity of distribution networks,alleviating voltage limit-exceeding issues,and optimizing the coordination of sources and loads.
作者
何维锋
HE Weifeng(Fujian Yongfu Power Engineering Co.,Ltd.,Fuzhou,Fujian 350108,China)
出处
《自动化应用》
2025年第21期125-128,共4页
Automation Application
关键词
高比例分布式光伏
承载能力评估
虚拟储能
反向负载率
high proportion of distributed photovoltaic
carrying capacity evaluation
virtual energy storage
reverse load rate
