摘要
可用输电能力(available transmission capability,ATC)反映了电网不同区域间的电能交换能力,为电网的稳定性评估提供了参考。随着电-气综合能源系统(electricity-gas integrated energy system,EGIES)的发展,天然气网络与电网进一步耦合,ATC的计算会更加复杂,从而影响ATC的计算效率。针对上述问题,文章提出了一种面向数字孪生(digital twin)理念的电-气综合能源系统的ATC计算方法。首先将数据驱动和模型驱动进行融合,构建数据-机理融合模型以满足数字孪生理念的指标要求。数据-机理融合模型可以充分挖掘隐藏在海量状态数据下的信息,进而简化传统物理模型迭代计算的过程,缩短计算时间;其次,构建数字虚拟模型以实时处理综合能源系统内不断更新的状态量数据,实现最大输电能力的在线计算并提取系统运行状态的特征;然后,利用提取出来的特征进行综合能源系统的ATC计算;最后,通过IEEE30-NGS10电-气综合能源系统验证了文章所提方法的有效性与高效性。
The available transmission capacity(ATC)reflects the power exchange capacity between different regions of a power grid and provides a reference for evaluating the stability of a power grid.With the development of integrated electrical energy systems and increased coupling of natural gas networks and power grids,ATC calculations will become more complex,affecting its calculation efficiency.To solve these problems,this study proposes an ATC calculation method for an electric gas-integrated energy system based on the digital twin concept.First,we integrate data-driven and modeldriven data and develop a data mechanism fusion model to satisfy the indicator requirements of the digital twin concept.The data mechanism fusion model can fully mine the information hidden in massive state data,thereby simplifying the iterative calculation process of traditional physical models and shortening the calculation time.The invented model is developed to process the constantly updated state data in the integrated energy system in real time to realize the online calculation of the maximum transmission capacity and extract the characteristics of the system operation state.The extracted features are then used to calculate the ATC of the integrated energy system.Finally,the effectiveness and efficiency of the proposed method are verified using the IEEE30-NGS10 electric gas integrated energy system.
作者
罗昊
王长江
王建国
LUO Hao;WANG Changjiang;WANG Jianguo(School of Electrical Engineering,Northeast Elecrtic Power University,Jilin 132012,Jilin Province,China;Jilin Power Supply Company,State Grid Jilin Electric Power Co.,Ltd.,Jilin 132012,Jilin Province,China)
出处
《电力建设》
CSCD
北大核心
2023年第11期113-127,共15页
Electric Power Construction
基金
国家自然科学基金项目(52077028)
国网吉林省电力有限公司吉林供电公司项目(SGJLJL00XTJS2301284)。
关键词
综合能源系统
深度学习
数字孪生
可用输电能力(ATC)计算
数据挖掘
integrated energy system
deep learning
digital twins
calculation of available transmission capacity(ATC)
data mining