基于图模型的电力系统碳流计算优化研究

doi:10.11959/j.issn.2096-0271.2024027

大数据 ›› 2024, Vol. 10 ›› Issue (2): 179-191.doi: 10.11959/j.issn.2096-0271.2024027

• 专栏：信息技术应用创新：系统与软件 • 上一篇

基于图模型的电力系统碳流计算优化研究

朱广新, 周春雷, 李俊妮, 宋继勐, 史昕, 沈子奇

国家电网有限公司大数据中心，北京 100053

出版日期:2024-03-01 发布日期:2024-03-01
作者简介:朱广新（1981- ），男，国家电网有限公司大数据中心教授级高级工程师，主要从事电力数字化建设、电力大数据分析应用等工作，科研成果多次获得国家电网公司科技进步奖一/二等奖。
周春雷（1980- ），男，国家电网有限公司大数据中心高级工程师，主要从事电力大数据、信息化建设工作。
李俊妮（1982- ），女，国家电网有限公司大数据中心中级经济师，主要从事能源大数据应用和标准工作。
宋继勐（1981- ），男，国家电网有限公司大数据中心高级工程师，主要从事数字化建设、能源大数据管理及应用等工作。
史昕（1991- ），女，国家电网有限公司大数据中心高级工程师，主要从事电力大数据应用、电力系统分析等工作。
沈子奇（1985- ），男，国家电网有限公司大数据中心高级工程师，主要从事大数据管理、数据分析应用、能源大数据中心等专业领域工作。
基金资助:
国网大数据中心科技项目(SGSJ0000SJJS2100158)

Research on power system carbon flow calculation based on graph database and graph computing engine

Guangxin ZHU, Chunlei ZHOU, Junni LI, Jimeng SONG, Xin SHI, Ziqi SHEN

Big Data Center of State Grid Corporation of China, Beijing 100053, China

Online:2024-03-01 Published:2024-03-01
Supported by:
Technology Project of State Grid Big Data Center(SGSJ0000SJJS2100158)

摘要/Abstract

摘要：

首先介绍了图数据模型、图数据库和图计算的基本原理，包括图数据库的数据模型、查询语言以及常见图计算方法等。然后详细阐述了电力系统的图数据模型构建方法，将系统组件表示为节点，组件间关系表示为边。最后设计了碳流计算的图算法流程，利用AtlasGraph图数据库及图计算组件进行碳流传递迭代计算。该方法充分利用图数据库和图算法的优势，实现了对电力系统碳流的精确高效计算。该研究为电力系统碳排放的监测、分析和优化提供了有力支持，对于推动电力系统绿色低碳发展具有重要意义。

关键词: 图数据库, 图计算引擎, 电力系统, 碳流计算, 绿色低碳发展

Abstract:

Firstly, the basic principles of graph database and graph algorithms are introduced, including the data model of graph database, query language, and common graph algorithms.Then, the method of constructing the graph model of the power system is elaborated, where system components are represented as nodes and component relationships are represented as edges.Finally, the graph algorithm process of carbon flow calculation is designed, using the AtlasGraph graph database and graph computing components to perform carbon flow iterative calculation.This method makes full use of the advantages of graph database and graph algorithms, achieving accurate and efficient calculation of power system carbon flow.This research provides strong support for monitoring, analyzing, and optimizing carbon emissions in power systems, and is of great significance for promoting the green and low-carbon development of power systems.

Key words: graph database, graph computing engine, power system, carbon flow calculation, green and low-carbon development

中图分类号:

TM71

朱广新, 周春雷, 李俊妮, 宋继勐, 史昕, 沈子奇. 基于图模型的电力系统碳流计算优化研究[J]. 大数据, 2024, 10(2): 179-191.

Guangxin ZHU, Chunlei ZHOU, Junni LI, Jimeng SONG, Xin SHI, Ziqi SHEN. Research on power system carbon flow calculation based on graph database and graph computing engine[J]. Big Data Research, 2024, 10(2): 179-191.

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基于图模型的电力系统碳流计算优化研究

Research on power system carbon flow calculation based on graph database and graph computing engine

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