摘要
“双碳”目标下,大规模分布式新能源接入增加了城市配电网在极端事件下的不确定性与控制复杂度,亟须提出相适应的灾后负荷恢复方法,保障城市配电网的安全运行。现有灾后负荷恢复方法未充分考虑运行层面下动态变化的不确定性、动态微电网边界变化、频率电压控制等实际因素,影响了负荷恢复策略在实际配电网中的可行性。为此,文中首先通过C-Vine Copula和条件概率准确刻画新能源和负荷的动态不确定性。其次,建立了考虑动态微电网划分和频率电压控制的灾后负荷恢复优化模型,并提出了高效的两阶段求解算法。最后,面向实时调度,搭建了城市配电网在线负荷恢复框架,实现灾后负荷恢复策略的滚动更新。文中所提方法的有效性在改进的IEEE 37节点馈线系统中得到了验证。
For the carbon emission peak and carbon neutrality,the large-scale penetration of distributed renewable energy resources increases the uncertainty and control complexity of urban distribution networks under extreme events.An adaptive post-disaster load restoration method is urgently needed to ensure safe operation of urban distribution networks.The current post-disaster load restoration methods do not fully consider the uncertainty of dynamic changes at the operational level,dynamic microgrid boundary changes,frequency-voltage control,and other practical factors,which affects the feasibility of the load restoration method in the actual distribution network.For this purpose,first,this paper accurately characterizes the dynamic uncertainty of renewable energy resources and load with the C-Vine Copula and conditional probability.Then,a post-disaster load restoration optimization model is proposed considering dynamic microgrid partition and frequency-voltage control,and an efficient two-stage solving algorithm is also proposed.Finally,an online load restoration framework for urban distribution networks is built for real-time dispatching to realize rolling updates of post-disaster load restoration strategies.The effectiveness of the proposed method is verified in an modified IEEE 37-bus feeder system.
作者
林超凡
陈晨
别朝红
李更丰
LIN Chaofan;CHEN Chen;BIE Zhaohong;LI Gengfeng(State Key Laboratory of Electrical Insulation and Power Equipment,Xi'an 710049,China;Institute of Power System and Its Resilience,Xi'an Jiaotong University,Xi'an 710049,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2022年第17期56-64,共9页
Automation of Electric Power Systems
基金
国家电网公司科技项目(SGSNKY00DWJS2100278)。
关键词
配电网
城市能源系统
新能源
概率建模
负荷恢复
频率电压控制
随机优化
distribution network
urban energy system
renewable energy resource
probabilistic modeling
load restoration
frequency-voltage control
stochastic optimization