Summary

This paper explores the evolution of data historians as critical infrastructure for modern power systems, with emphasis on Eskom’s Remote Monitoring and Diagnostics Centre (RMDC). The rise of smart grids has introduced massive, high‑velocity datasets from sensors such as PMUs,

IEDs, smart meters, etc, overwhelming traditional SCADA/DCS systems and relational databases. Utilities are therefore adopting specialised Time‑Series Databases (TSDBs) and historians, optimised for timestamp indexing, high‑frequency ingestion, and compression techniques such as exception reporting and swinging door algorithms. These approaches preserve signal fidelity while reducing storage costs, enabling long‑term retention of granular operational data.

The paper emphasizes the importance of semantic standards such as the Common Information

Model (CIM), IEC 61850, and OPC Unified Architecture (OPC UA) to overcome silos and ensure interoperability. A case study of Eskom’s RMDC shows how centralised historian architecture enables proactive fleet‑wide monitoring, predictive fault detection, and reliability‑centred operations. By integrating diverse data sources including turbine vibration monitors, generator health systems, transformer gas analysers, and enterprise systems, RMDC provides a unified “single version of the truth.” Future directions include consolidating legacy platforms into unified TSDB architectures, hybrid cloud adoption, and advanced capabilities such as digital twins and AI‑driven analytics.

Additional informations

Publication type Session Materials
Reference D2_12098_2026
Publication year
Publisher CIGRE
Country South Africa
Study committees
File size 516 KB
Price for non member 30 €
Price for member 30 €

Authors

MANYAPETSA Kgomotso - National Transmission Company South Africa (NTCSA); BUTHELEZI Lindani - Eskom; NGEMA Phiwayinkosi - Eskom

Keywords

Analytics, Data Historians, Decision-Making, Power Grid, Time-series Data

Unlocking the full potential of data historians across the modern power grid: from generation