基于异构数据模型的电-气耦合网络状态感知方法研究  

Research on situation awareness of electricity-gas coupling network based on a heterogeneous data model

作　　者：胡旭光 张化光[1,2] 孙秋野 王睿[1] 马大中 HU XuGuang;ZHANG HuaGuang;SUN QiuYe;WANG Rui;MA DaZhong(College of Information Science and Engineering,Northeastern University,Shenyang 110819,China;State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University,Shenyang 110819,China)

机构地区：[1]东北大学信息科学与工程学院,沈阳110819 [2]东北大学流程工业综合自动化国家重点实验室,沈阳110819

出　　处：《中国科学：技术科学》2020年第3期346-360,共15页Scientia Sinica(Technologica)

基　　金：国家重点研发计划(编号:2018YFA0702200);辽宁省“兴辽英才计划”项目(编号:XLYC1801005,XLYC1807009);国家自然科学基金创新研究群体项目(编号:61621004);国家自然科学基金(批准号:61433004,61773109,61573094)资助。

摘　　要：随着电力、天然气网络开放互联,多能流耦合在实现能源科学管理与优化调度的同时,彼此间能量转换使得原本独立能源网络的状态感知复杂度增加.因此,在实现快速分析及考虑耦合网络特性的基础上,本文提出一种针对多维电-气耦合网络的异构数据模型状态感知方法.首先,针对子网络交互影响以及相应检测变量变化过程,构建出刻画不同子网络时间响应特性的异构数据模型.然后将构造的模型通过归一化及函数转换得到对应的协方差矩阵提高节点数据变化灵敏度,并且将状态感知判断转化为随机矩阵谱差异值变化程度的分析.在确定网络状态改变的前提下,根据谱分布对应的最大特征向量得到发生变化的网络节点,从而完成整个耦合网络状态感知过程.最后对不同电-气耦合网络状态改变情况进行仿真,仿真结果验证了本文所提方法的可行性与有效性.Open interaction between the power system and the natural gas network, realizing the multi-energy flow, not only brings scientific management and optimal operation of energy but also increases the complexity of situation awareness due to energy conversion between independent energy networks. Therefore, this paper proposes a heterogeneous data model-based method embedding the characteristics of a coupling network for situation awareness of the multi-dimensional electricity-gas coupling network to achieve rapid analysis. First, considering the interaction between subnetworks and the change in the corresponding detection variables, the heterogeneous data model is developed to depict the time response characteristics of different subnetworks. Then, by the normalization and functional transform by the proposed model, a covariance matrix is obtained to improve the sensitivity to the nodedata change. Furthermore, the situation awareness of a coupling network is transformed into the degree analysis regarding the spectral difference value of a random matrix. Moreover, the changed node is obtained from the maximum eigenvector value of spectral distribution using the network situation change, completing the process of situation awareness. Finally, the feasibility and effectiveness of the proposed method are verified by different situation changes in the electricity-gas coupling network.

关 键 词：电-气耦合网络 多时间尺度 异构数据模型 数据驱动 谱分析 

分 类 号：TK018[动力工程及工程热物理] TM73[电气工程—电力系统及自动化]