

浏览全部资源
扫码关注微信
1.合肥工业大学电气与自动化工程学院,安徽省合肥市 230009
2.工业自动化安徽省工程技术研究中心,安徽省合肥市 230009
3.山东科汇电力自动化股份有限公司,山东省淄博市 255087
Received:31 May 2021,
Revised:2021-11-05,
Published Online:21 December 2021,
Published:10 March 2022
移动端阅览
孙伟,朱世睿,杨建平等.基于图卷积网络的微电网拓扑辨识[J].电力系统自动化,2022,46(5):71-77.
SUN Wei,ZHU Shirui,YANG Jianping,et al.Topology Identification of Microgrid Based on Graph Convolutional Network[J].Automation of Electric Power Systems,2022,46(5):71-77.
孙伟,朱世睿,杨建平等.基于图卷积网络的微电网拓扑辨识[J].电力系统自动化,2022,46(5):71-77. DOI: 10.7500/AEPS20210531005.
SUN Wei,ZHU Shirui,YANG Jianping,et al.Topology Identification of Microgrid Based on Graph Convolutional Network[J].Automation of Electric Power Systems,2022,46(5):71-77. DOI: 10.7500/AEPS20210531005.
微电网控制器需要及时获取正确的网络拓扑结构,以调整其控制策略,保证微电网稳定安全运行。针对现有电网拓扑辨识方法中辨识准确度低和实时性差的问题,文中提出了一种基于图卷积网络的微电网拓扑辨识方法。首先
将微电网拓扑抽象成线图。然后,根据微电网拓扑的节点特征提取微电网线路的边特征,作为线图的节点特征。进而,利用抽象后线图的邻接矩阵和节点特征训练图卷积网络,得到微电网拓扑辨识模型。最后,通过实验数据验证了所提拓扑辨识方法的有效性。
The microgrid controller needs to obtain the correct network topology in time to adjust its control strategy and ensure the stable and safe operation of the microgrid. Aiming at the problems of low identification accuracy and poor real-time performance in the existing power grid topology identification methods
this paper proposes a microgrid topology identification method based on graph convolutional network. First
the microgrid topology is abstracted into a line graph. Then
the edge features of the microgrid lines are extracted according to the node feature of the microgrid topology as the node features of the line graph. Furthermore
the adjacency matrix and the bus feature of the abstracted line graph are used to train graph convolutional network to obtain the microgrid topology identification model. Finally
the effectiveness of the proposed topology identification method is verified by experimental data.
张凡 , 牟龙华 , 王子豪 , 等 . 主从控制孤岛微电网的优化故障控制策略 [J]. 中国电机工程学报 , 2020 , 40 ( 4 ): 1241 - 1248 .
ZHANG Fan , MU Longhua , WANG Zihao , et al . Optimal fault control strategy of master-slave controlled islanding microgrid [J]. Proceedings of the CSEE , 2020 , 40 ( 4 ): 1241 - 1248 .
赵梓杉 , 蒙志全 , 章雷其 , 等 . 含异构分布式电源的微电网无功功率分散分层控制策略 [J]. 电力系统自动化 , 2019 , 43 ( 11 ): 59 - 67 .
ZHAO Zishan , MENG Zhiquan , ZHANG Leiqi , et al . Decentralized and hierarchical reactive power control strategy for microgrid with heterogeneous distributed generators [J]. Automation of Electric Power Systems , 2019 , 43 ( 11 ): 59 - 67 .
王聪 , 颜伟 , 户秀琼 . 考虑频率波动的孤岛微电网在线三相概率潮流计算方法 [J]. 电力自动化设备 , 2020 , 40 ( 2 ): 109 - 118 .
WANG Cong , YAN Wei , HU Xiuqiong . Online three-phase probabilistic power flow calculation method for islanded microgrid considering frequency fluctuation [J]. Electric Power Automation Equipment , 2020 , 40 ( 2 ): 109 - 118 .
喻思 , 米阳 , 马宇辰 , 等 . 自适应高通滤波下垂控制的孤岛直流微电网功率分配控制 [J]. 电力系统保护与控制 , 2020 , 48 ( 18 ): 19 - 26 .
YU Si , MI Yang , MA Yuchen , et al . Power distribution control of an island DC microgrid based on adaptive high-pass filter droop control [J]. Power System Protection and Control , 2020 , 48 ( 18 ): 19 - 26 .
XU Y L , SUN H B , GU W , et al . Optimal distributed control for secondary frequency and voltage regulation in an islanded microgrid [J]. IEEE Transactions on Industrial Informatics , 2019 , 15 ( 1 ): 225 - 235 .
于国星 , 侯睿 , 汪任潇 , 等 . 孤岛微网分层分布式频率调节及功率优化控制 [J]. 电力系统自动化 , 2020 , 44 ( 7 ): 53 - 60 .
YU Guoxing , HOU Rui , WANG Renxiao , et al . Hierarchical distributed frequency regulation and power optimization control for islanded microgrid [J]. Automation of Electric Power Systems , 2020 , 44 ( 7 ): 53 - 60 .
CUCUZZELLA M , INCREMONA G P , FERRARA A . Decentralized sliding mode control of islanded AC microgrids with arbitrary topology [J]. IEEE Transactions on Industrial Electronics , 2017 , 64 ( 8 ): 6706 - 6713 .
王贺飞 , 李洪涛 , 余昆 , 等 . 基于DSCADA和μPMU数据融合的配电网运行拓扑辨识 [J]. 电力建设 , 2019 , 40 ( 6 ): 123 - 131 .
WANG Hefei , LI Hongtao , YU Kun , et al . Identification of distribution network operation topology based on DSCADA and μPMU telemetry data fusion [J]. Electric Power Construction , 2019 , 40 ( 6 ): 123 - 131 .
郭帅文 , 燕跃豪 , 蒋建东 , 等 . 基于邻接矩阵的网络拓扑辨识算法 [J]. 电力系统保护与控制 , 2018 , 46 ( 12 ): 50 - 56 .
GUO Shuaiwen , YAN Yuehao , JIANG Jiandong , et al . Network topology identification algorithm based on adjacency matrix [J]. Power System Protection and Control , 2018 , 46 ( 12 ): 50 - 56 .
JAFARIAN M , SOROUDI A , KEANE A . Distribution system topology identification for DER management systems using deep neural networks [C]// 2020 IEEE Power & Energy Society General Meeting (PESGM) , August 2-6 , 2020 , Montreal, Canada .
ZHAO L , LIU Y B , ZHAO J B , et al . Robust PCA-deep belief network surrogate model for distribution system topology identification with DERs [J]. International Journal of Electrical Power & Energy Systems , 2021 , 125 : 106441 .
彭寒梅 , 郭颖聪 , 昌玲 , 等 . 主从控制孤岛运行微电网的短期可靠性评估 [J]. 电网技术 , 2018 , 42 ( 2 ): 463 - 472 .
PENG Hanmei , GUO Yingcong , CHANG Ling , et al . Short-term reliability assessment of islanded microgrid under master-slave control [J]. Power System Technology , 2018 , 42 ( 2 ): 463 - 472 .
ZHAO C J , SUN W , WANG J P , et al . Distributed cooperative secondary control for islanded microgrid with Markov time-varying delays [J]. IEEE Transactions on Energy Conversion , 2019 , 34 ( 4 ): 2235 - 2247 .
程启明 , 褚思远 , 程尹曼 , 等 . 基于改进型下垂控制的微电网多主从混合协调控制 [J]. 电力系统自动化 , 2016 , 40 ( 20 ): 69 - 75 .
CHENG Qiming , CHU Siyuan , CHENG Yinman , et al . Multiple master-slave mixed coordinated control for microgrid based on improved droop control [J]. Automation of Electric Power Systems , 2016 , 40 ( 20 ): 69 - 75 .
苏宏升 , 江昆 , 杨祯 , 等 . 基于虚拟同步发电机的微网频率与电压综合控制策略 [J]. 电力自动化设备 , 2020 , 40 ( 3 ): 21 - 28 .
SU Hongsheng , JIANG Kun , YANG Zhen , et al . Comprehensive control strategy of microgrid frequency and voltage based on virtual synchronous generator [J]. Electric Power Automation Equipment , 2020 , 40 ( 3 ): 21 - 28 .
孟润泉 , 杜毅 , 韩肖清 , 等 . 可变拓扑的改进型交直流混合微电网 [J]. 电力系统自动化 , 2020 , 44 ( 18 ): 147 - 154 .
MENG Runquan , DU Yi , HAN Xiaoqing , et al . An improved hybrid AC/DC microgrid with variable topology [J]. Automation of Electric Power Systems , 2020 , 44 ( 18 ): 147 - 154 .
KIPF T , WELLING M . Semi-supervised classification with graph convolutional networks [EB/OL]. [ 2021-05-31 ]. https://arxiv.org/abs/1609.02907 https://arxiv.org/abs/1609.02907 .
DEFFERRARD M , BRESSON X , VANDERGHEYNST P . Convolutional neural networks on graphs with fast localized spectral filtering [J]. Advances in Neural Information Processing Systems , 2016 , 29 : 3844 - 3852 .
PAN S R , WU J , ZHU X Q , et al . Joint structure feature exploration and regularization for multi-task graph classification [J]. IEEE Transactions on Knowledge and Data Engineering , 2016 , 28 ( 3 ): 715 - 728 .
JAIN A , ZAMIR A R , SAVARESE S , et al . Structural-RNN: deep learning on spatio-temporal graphs [C]// 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 27-30 , 2016 , Las Vegas, USA : 5308 - 5317 .
徐冰冰 , 岑科廷 , 黄俊杰 , 等 . 图卷积神经网络综述 [J]. 计算机学报 , 2020 , 43 ( 5 ): 755 - 780 .
XU Bingbing , CEN Keting , HUANG Junjie , et al . A survey on graph convolutional neural network [J]. Chinese Journal of Computers , 2020 , 43 ( 5 ): 755 - 780 .
杨华 , 李喜旺 , 司志坚 , 等 . 基于图神经网络的配电网故障预测 [J]. 计算机系统应用 , 2020 , 29 ( 9 ): 131 - 135 .
YANG Hua , LI Xiwang , SI Zhijian , et al . Accident prediction of power distribution network based on graph neural network [J]. Computer Systems & Applications , 2020 , 29 ( 9 ): 131 - 135 .
GANIE H A , CHAT B A , PIRZADA S . Signless Laplacian energy of a graph and energy of a line graph [J]. Linear Algebra and Its Applications , 2018 , 544 : 306 - 324 .
WANG H R , WANG K , YANG J C , et al . GCN-RL circuit designer: transferable transistor sizing with graph neural networks and reinforcement learning [C]// 2020 57th ACM/IEEE Design Automation Conference (DAC) , July 20-24 , 2020 , San Francisco, USA : 1 - 6 .
王晨 , 寇鹏 . 基于卷积神经网络和简单循环单元集成模型的风电场内多风机风速预测 [J]. 电工技术学报 , 2020 , 35 ( 13 ): 2723 - 2735 .
WANG Chen , KOU Peng . Wind speed forecasts of multiple wind turbines in a wind farm based on integration model built by convolutional neural network and simple recurrent unit [J]. Transactions of China Electrotechnical Society , 2020 , 35 ( 13 ): 2723 - 2735 .
裴宇婷 , 秦超 , 余贻鑫 . 基于LightGBM和DNN的智能配电网在线拓扑辨识 [J]. 天津大学学报(自然科学与工程技术版) , 2020 , 53 ( 9 ): 939 - 950 .
PEI Yuting , QIN Chao , YU Yixin . Online topology identification for smart distribution grids based on LightGBM and deep neural networks [J]. Journal of Tianjin University (Science and Technology) , 2020 , 53 ( 9 ): 939 - 950 .
0
Views
0
下载量
13
CSCD
Publicity Resources
Related Articles
Related Author
Related Institution
京公网安备11010802024621