A public utility in Sub Saharan Africa needed to model its power grid and enable advanced analysis such as economic loss detection. Existing models were incomplete, lacked real world use, and internal expertise in grid modelling and standards was limited. Sotex implemented IEC CIM 17, building a structured data model across multiple distribution companies, resulting in a functional digital twin that supports accurate modelling, power flow analysis, and advanced algorithms.
Challenges
- Limited domain knowledge of power grid modelling and IEC CIM standards
- Unstructured and rapidly expanding grid network
- Lack of a reliable base model to support real-world use cases
- Need to standardise data for utility data exchange
- Requirement to support multiple grid configurations across utilities
- Legacy constraints and limited internal technical capacity
Our Solution & Key Features
Sotex Solutions implemented a CIM-based data modelling platform that serves as the foundation for representing and analysing power grid networks.
The solution introduces a standardised data model aligned with IEC 61970, enabling consistent representation of assets, topology, and relationships across different utility systems. This structure allows the client to build a digital twin of the grid and run analytical models on top of it.
Key capabilities include:
- IEC CIM compliant data model for power grid representation
- Support for multiple grid configurations and utility environments
- Digital twin of the power grid network
- Foundation for power flow analysis and advanced algorithms
- Structured data layer enabling interoperability and data exchange
- Scalable architecture for expanding grid networks
This approach transformed fragmented and incomplete models into a standardised, extensible system that reflects real-world grid behaviour.
Key Achievements
Successful implementation of the IEC CIM standard for grid modelling
Creation of a functional digital twin of the power grid
Improved accuracy and structure of grid data
Enabled execution of advanced analytics such as loss detection
Foundation for scaling across multiple utilities and regions
Technology Stack
Frontend: Angular
Backend: .NET Core (C#)
Database: Azure SQL Server, Azure Blob Storage
Cloud Hosting: Azure Cloud, Azure Container Apps, Docker Swarm
Integrations & Frameworks: IEC 61970 (CIM), Lakehouse architecture
Business Impact
By implementing a standardized CIM based model, the client gained the ability to understand, simulate, and optimise their power grid operations. The digital twin enables better planning, improved loss detection, and supports collaboration with third-party utilities through standardised data exchange.
Conclusion
Sotex Solutions enabled the transition from incomplete and inconsistent grid models to a structured, scalable digital twin platform. The system now supports advanced analytics, operational improvements, and future expansion across additional utilities and regions.
Looking to build advanced data models or digital twins for complex systems?
Contact Sotex Solutions to design scalable, standards-driven platforms for your industry.
📧 bd@sotexsolutions.com
📞 +381-64-165-7193
