Network Model Version Control via Segmented Database Areas
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Solution Overview
Problem
Existing electric utility systems face challenges in managing and synchronizing network data across different systems, such as GIS, DMS, and OMS, particularly in transforming and version-controlling frequently changing network information for efficient integration and deployment.
Innovation Solution
A method and apparatus for providing version control of an electrical network model using a database divided into logical areas, including a working model, full model, and permanent model areas, with timestamp-based versioning and validation, enabling efficient data import, validation, and export using the CIM standard for integration and communication between systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If network data is frequently updated and transformed between GIS and operational systems, then data currency and relevance are improved, but data integrity and consistency deteriorate
Solution Approach 1:
The system performs preliminary validation of incremental change data against the full model before merging, ensuring data integrity is maintained proactively. Version control mechanisms are established in advance with timestamp-based tracking, allowing the system to prevent inconsistent data from being integrated into the operational model.
Solution Approach 2:
A model management gateway acts as an intermediary between GIS and operational systems (DMS/OMS). This gateway validates, transforms, and coordinates data exchanges, ensuring that frequent updates maintain consistency across systems. The gateway uses validation rules and version control to mediate between the need for frequent updates and the requirement for data integrity.
2Adaptability or versatility
If network data is transformed from geographic to schematic form for operational use, then system integration capability is improved, but transformation complexity and error potential increase
Solution Approach 1:
The model management gateway provides universal transformation capabilities that handle multiple data formats and transformation types through a single system. By implementing a standardized validation framework and common transformation logic, the system reduces complexity while maintaining the ability to integrate diverse GIS and operational systems.
Solution Approach 2:
The system manages transformation complexity by controlling parameter changes during the geographic-to-schematic conversion process. Validation rules define acceptable parameter transformations, and version control tracks parameter changes over time, allowing the system to maintain adaptability while reducing uncontrolled complexity.
3Reliability
If full network models are stored and validated, then data consistency and reliability are improved, but storage requirements and processing time increase
Solution Approach 1:
Instead of validating and storing complete full models every time an update occurs, the system validates only the incremental change data against the existing full model. This partial action approach maintains data consistency by verifying changes while significantly reducing processing time and storage requirements compared to validating entire models repeatedly.
4Productivity
If multiple systems (GIS, DMS, OMS) are integrated and synchronized, then operational efficiency is improved, but synchronization complexity and data conflicts increase
Solution Approach 1:
The system segments the synchronization process into distinct functional components: data import, validation, version control, and export. Each component handles a specific aspect of the integration process, reducing overall synchronization complexity. The database is also segmented into working model and permanent model areas, allowing independent management of different data states.
Solution Approach 2:
Version control mechanisms provide feedback about data changes across systems, allowing the model management gateway to detect and resolve conflicts. Timestamp-based versioning creates a feedback loop that tracks data evolution, enabling the system to maintain synchronization while managing complexity through automated conflict detection and resolution.
Data Source
AI summary
Disclosed are methods and apparatus for providing version control for a model. A database (102) is divided into three logical areas corresponding to working model area (120), full model area (122), and permanent model area (124). Data, which may be CIM formatted data, imported into the model is validated against data previously stored in the full model area (122) and version controlled based in part on timestamp data. The version controlled data may then be exported for use by network applications. Imported data may come from a power system utility while the exported data may be used for control of such a utility.