High Reusability Verification Platform for Artificial Intelligence Applications in Power Grid Dispatching and Control Field

doi:10.11930/j.issn.1004-9649.202407038

Abstract

Abstract:

In recent years, the trend of intelligent development in the field of power grid dispatching and control has been obvious. However, due to the black box nature of Artificial Intelligence (AI) technology itself, correctness and reliability verification is becoming increasingly important. Constructing a reusable supporting platform that can support verification of various AI models is particularly urgent. A three-layer verification platform architecture including infrastructure, platform services, and application services is thus proposed based on an analysis of the needs and issues. The operation mode of AI model validation under this architecture is analyzed, and the key technologies such as case and sample reusing, containerization and mirroring, as well as multi framework and algorithm integration are studied. Finally, the related development and implementation are also carried out. This platform has achieved unified management and reuse of computing power and data resources, compatibility with different AI frameworks and algorithm libraries, dynamic generation of verification scenarios, etc., laying a foundation for the future promotion and application of AI technology in the field of power grid dispatching.

Key words: power grid dispatching and control, artificial intelligence (AI), machine learning, new power system, information and communication technology (ICT), energy management system (EMS)

Zhiyuan GAO, Weijin ZHUANG, Feng LI, Fang YU, Hong ZHANG, Yan WANG, Min XIA. High Reusability Verification Platform for Artificial Intelligence Applications in Power Grid Dispatching and Control Field[J]. Electric Power, 2025, 58(3): 142-150.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202407038

https://www.electricpower.com.cn/EN/Y2025/V58/I3/142

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References 30

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软件名称		主要功能
Docker		应用容器引擎
Kubernetes		容器编排平台
Robot Framework		可支持分布式异构环境的自动测试框架
Redis		可基于内存亦可持久化的数据库
GitLab		版本控制和项目管理工具
Pytorch		Facebook开发的深度学习框架
Tensorflow		Google开发的深度学习框架

软件名称		主要功能
Docker		应用容器引擎
Kubernetes		容器编排平台
Robot Framework		可支持分布式异构环境的自动测试框架
Redis		可基于内存亦可持久化的数据库
GitLab		版本控制和项目管理工具
Pytorch		Facebook开发的深度学习框架
Tensorflow		Google开发的深度学习框架

层级	接口名称	内容说明
应用级	在线标准规约	IEC 60870-5-103、104规约等
	独立文件	共享文件
	数据库数据	互斥读写的数据库数据
平台级	容器间通信	Docker自带通信机制或者第三方插件

层级	接口名称	内容说明
应用级	在线标准规约	IEC 60870-5-103、104规约等
	独立文件	共享文件
	数据库数据	互斥读写的数据库数据
平台级	容器间通信	Docker自带通信机制或者第三方插件

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