SG-CIM Model Verification and Validation Framework in Business Middle Platform
Рамочная модель верификации и валидации модели SG-CIM на бизнес-посреднической платформе
2023-09-16
SCID: 54.1/795j42x4
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SG-CIM model validationSG-CIM model verificationState Grid middle platforminput checkssensitivity analysis
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Abstract (AI)
With the continuous development of State Grid middle platforms and expansion of power grid applications, SG-CIM model verification has received increasing attention. It plays a crucial role in ensuring the data accuracy and consistency for information applications tailored to the needs of different professional departments in the power industry. This paper provides an overview of the SG-CIM middle platform, emphasizing its crucial role in supporting data sharing and analysis applications between different professional and operational units. We outline key steps involved in the verification and validation process for SG-CIM models, including input checks, model validation, sensitivity analysis, and model evaluation modules. Furthermore, the paper also highlights how this framework fosters collaboration between different parts of an organization by ensuring that data used in these applications is accurate and consistent across different business processes.
Key Findings
1
Implementing this V&V framework improves collaboration across organizational units by ensuring data accuracy and consistency for business processes.
2
SG-CIM model verification is increasingly important for State Grid middle platforms due to expanding power grid applications.
3
The SG-CIM middle platform is crucial for supporting data sharing and analysis between different professional and operational units.
4
The proposed verification and validation process includes input checks, model validation, sensitivity analysis, and model evaluation modules.
Research Object
SG-CIM model within the State Grid business middle platform
Research Subject
Verification and validation framework for ensuring data accuracy, consistency, and interoperability through input checks, model validation, sensitivity analysis, and model evaluation to support cross-departmental data sharing and applications
Publication Details
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2023-09-16
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