Intra-day scheduling computing of coordinated generation-grid- load-storage based on graph database and graph computing
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    Abstract:

    The new power system requires cooperative and optimized scheduling in the integration of Generation-Grid-Load-Storage (GGLS).At present,the scheduling automation system employs a relational database that relies on multiple associated tables for data query and storage,making it difficult to meet the rapid computation demands.Here,we propose a graph-based computing method for intra-day scheduling of coordinated GGLS.Firstly,the graph database is used to integrate the spatiotemporal data from power generation,grid,loads,and storage.Secondly,a comprehensive optimization model of intra-day scheduling of coordinated GGLS is formulated,taking into account various resources such as thermal power units,adjustable loads,and energy storage.Thirdly,a graph-based power flow calculation approach is proposed to quickly perform system security checks.Finally,based on the security check results,the system operating status is corrected until all operational constraints are satisfied.Through analysis of improved examples on the IEEE118-node and IEEE1354-node systems,it is verified that the proposed coordinated optimization strategy for GGLS can improve computational efficiency.

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WANG Zhenyi, GAO Daochun, MO Xi, GE Benxing, LU Xuegang, QIE Jingbiao, XIE Hua, ZHANG Pei. Intra-day scheduling computing of coordinated generation-grid- load-storage based on graph database and graph computing[J]. Journal of Nanjing University of Information Science & Technology,2024,16(6):838-845

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History
  • Received:March 11,2024
  • Online: January 06,2025
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