Graph Neural Network Based Column Generation for Energy Management in Networked Microgrid  

作　　者：Yuchong Huo Zaiyu Chen Qun Li Qiang Li Minghui Yin 

机构地区：[1]the School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China [2]the State Grid Jiangsu Electric Power Co.,Ltd.Research Institute,Nanjing 211103,China

出　　处：《Journal of Modern Power Systems and Clean Energy》2024年第5期1506-1519,共14页现代电力系统与清洁能源学报（英文）

基　　金：supported in part by the National Science Foundation of China(No.51977111);the Jiangsu Qinglan Project;the State Grid Corporation Science and Technology Project“Key technologies of active frequency support for mid and long distance offshore wind farm with multiple grid-forming converter connected via VSC-HVDC”(No.5108-202218280A-2-241-XG)。

摘　　要：In this paper,we apply a model predictive control based scheme to the energy management of networked microgrid,which is reformulated based on column generation.Although column generation is effective in alleviating the computational intractability of large-scale optimization problems,it still suffers from slow convergence issues,which hinders the direct real-time online implementation.To this end,we propose a graph neural network based framework to accelerate the convergence of the column generation model.The acceleration is achieved by selecting promising columns according to certain stabilization method of the dual variables that can be customized according to the characteristics of the microgrid.Moreover,a rigorous energy management method based on the graph neural network accelerated column generation model is developed,which is able to guarantee the optimality and feasibility of the dispatch results.The computational efficiency of the method is also very high,which is promising for real-time implementation.We conduct case studies to demonstrate the effectiveness of the proposed energy management method.

关 键 词：Column generation energy management graph neural network machine learning MICROGRID 

分 类 号：TM727[电气工程—电力系统及自动化] TP183[自动化与计算机技术—控制理论与控制工程]