基于形状约束语言的电网模型知识图谱验证方法

doi:10.11930/j.issn.1004-9649.202107093

中国电力 ›› 2022, Vol. 55 ›› Issue (1): 119-125,228.DOI: 10.11930/j.issn.1004-9649.202107093

• 人工智能在新型电力系统中的应用 • 上一篇下一篇

基于形状约束语言的电网模型知识图谱验证方法

李晓露¹, 左璇¹, 刘日亮², 陆一鸣³, 李聪利⁴, 林顺富¹

1. 上海电力大学电气工程学院, 上海 200093;
2. 国家电网有限公司, 北京 100031;
3. 国网上海能源互联网研究院, 上海 201210;
4. 国网天津市电力公司, 天津 300010

收稿日期:2021-07-21 修回日期:2021-12-08 出版日期:2022-01-28 发布日期:2022-01-20
作者简介:李晓露(1971-),女,博士,副教授,从事电力企业信息集成、电力调度自动化、配电自动化、综合能源系统研究,E-mail:lixiaolu_sh@163.com;左璇(1997-),女,硕士研究生,从事配电自动化及综合能源系统优化运行研究,E-mail:1021429256@qq.com;刘日亮(1982-),男,高级工程师,从事配电自动化、信息化、智能化研究,E-mail:riliang-liu@sgcc.com.cn;陆一鸣(1981-),男,高级工程师,从事智能电网信息模型与互操作技术研究,E-mail:luyiming@epri.sgcc.com.cn;李聪利(1974-),男,高级工程师,从事配网运维检修技术研究,E-mail:congli.li@tj.sgcc.com.cn;林顺富(1981-),男,教授,从事电能质量、智能配用电研究,E-mail:shunfulin@shiep.edu.cn
基金资助:
国家电网有限公司科技项目（营配调信息模型边界建模及其一致性检测技术研究， SGTJDK00DWJS1900100）；国家自然科学基金资助项目(促进新能源灵活消纳的集群多元可控负荷协调控制方法，51977127)。

SHACL-Based Validation Method of Knowledge Graph for Power System Model

LI Xiaolu¹, ZUO Xuan¹, LIU Riliang², LU Yiming³, LI Congli⁴, LIN Shunfu¹

1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. State Grid Corporation of China, Beijing 100031, China;
3. State Grid Shanghai Energy Interconnection Research Institute, Shanghai 201210, China;
4. State Grid Tianjin Electric Power Company, Tianjin 300010, China

Received:2021-07-21 Revised:2021-12-08 Online:2022-01-28 Published:2022-01-20
Supported by:
This work is supported by Science and Technology Project of SGCC (Research on Boundary Modeling for Electricity Marketing Management System, Distribution Management System and Energy Management System and Information Model Conformance Testing Technology, No.SGTJDK00 DWJS1900100) and National Natural Science Foundation of China (Coordinated Control Method for Aggregated Multiple Controllable Loads to Promote Flexible Consumption of Renewable Energy, No.51977127).

摘要/Abstract

摘要： 随着电网规模的扩大、分布式能源的高比例渗透，电网分析决策对电网模型的全面性和准确性提出了更高的要求。针对交换模型所依赖的公共信息模型（common information model, CIM）存在版本变化频繁、自定义扩展不可避免以及模型质量要求动态演化的问题，提出基于形状约束语言（shapes constraint language, SHACL）的电网模型知识图谱验证方法。基于CIM构建电网模型的概念图谱和实体图谱，设计了电网模型验证的CIM模式一致性形状和基于简单协议和资源描述框架查询语言（simple protocol and RDF query language，SPARQL）的跨类、跨属性一致性形状。基于SHACL的电网模型知识图谱验证方法无需对验证规则进行硬编码，提升了电网模型质量验证的灵活性，满足应用对模型质量要求的动态演化。

关键词: 电网模型, 公共信息模型, 知识图谱, 模型验证, 形状约束语言

Abstract: With the expansion of the power grid and the high penetration of distributed energy resources, the power system analysis and decision-making have put forward higher requirements for comprehensive and accurate power grid models. With respect to frequent version updates of the Common Information Model (CIM) on which the exchange model depends, the inevitable self-defined extension of CIM, and the dynamic evolution of model quality requirements, a method for validating the knowledge graph of the power system model based on the shapes constraint language (SHACL) is proposed. The CIM-based concept graph and entity graph of the power system model are established, the CIM schema consistency shapes, and the cross-class and cross-property consistency shapes based on simple protocol and RDF query language (SPARQL) for validating the power system model are designed. The SHACL-based knowledge graph validation for the power system model does not need to hard-code the validation rules, and then the flexibility of power system model quality validation can be improved and the dynamic evolution of model quality requirements can be satisfied.

Key words: power system model, common information model, knowledge graph, model validation, shapes constraint language

李晓露, 左璇, 刘日亮, 陆一鸣, 李聪利, 林顺富. 基于形状约束语言的电网模型知识图谱验证方法[J]. 中国电力, 2022, 55(1): 119-125,228.

LI Xiaolu, ZUO Xuan, LIU Riliang, LU Yiming, LI Congli, LIN Shunfu. SHACL-Based Validation Method of Knowledge Graph for Power System Model[J]. Electric Power, 2022, 55(1): 119-125,228.

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基于形状约束语言的电网模型知识图谱验证方法

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