Condition Monitoring System (CMS) for Fingrid

Power Grid1

The Company

Fingrid is Finland’s electricity transmission system operator (TSO), responsible for planning and monitoring the operation of the Finnish transmission system in addition to maintaining and developing the system. The transmission system encompasses over 14,000 kilometers of 400, 220 and 110 kilovolt transmission lines plus more than 100 substations. Major power plants, industrial plants and regional electricity distribution networks are connected to the grid. The Finnish power system is part of the inter-Nordic power system.

The challenge

The target for the Condition-Monitoring System (CMS) project was to give easy access to on-line historical data for maintenance purposes and to process the off-line maintenance data. The objective was a common tool for maintenance specialists and control room personnel to monitor assets. The function of the system required was to provide a smart overview of the status of equipment, generate alarms, display relevant trends and analyze data on user demand.

PI Asset Framework structure process data

To fulfill the target and objective, a tool was developed to process the large volume of data in a way that improved visualization and added automatic early-stage notifications.

Based on the PI System

The Condition Monitoring System (CMS), which has been developed together with Amitec, is based on technologies from the PI System from OSIsoft, and SQL Server business intelligence software from Microsoft.


Grid power flows, voltages, currents, SF6 pressures and transformer gas development come from supervisory control and data acquisition (SCADA) and on-line condition-monitoring devices. Nominal values, manufacturing date, device defects, defect-severity categorizing and measurements from device service actions come from the off-line asset-management system.


The PI Server processes both on-line and off-line measurements, which are combined in the PI Asset Framework so that measurement tags are linked with a corresponding asset element.

Scalable Visualization

The CMS system provides displays for each element, but only one display is needed for each type of asset. When users change from transformer 1 to transformer 2, the display stays same but the values are updated.

In May 2012 an increasing oil-gas ratio was detected on a transformer. The CMS detected the adverse correlation between two SCADA system on-line measurements, the low-voltage current and the oil-gas ratio and confirmed with diagnostics measurements that gave time to take remedial action.

SF6 On-Line Monitoring

European Union regulations have become more stringent concerning the use of fluorinated gases and monitoring of their emissions. The implementation of SF6 on-line monitoring supports the gas management and improves the monitoring of the gas levels in the switchgear.

Alarm Levels

Fingrid monitors SF6 gas leakages in the CMS system using two notification rules. The first rule is designed to monitor fast leaks using warning and alarm levels, while the second rule detects slow and small leaks using linear regression.

Health Index Analysis

This health index identifies the priority in terms of additional maintenance or need of renewal. An index of this kind is essential when the population of components is large. The idea of a switchgear health index is to determine a value for every device and then combine these values to evaluate the complete switchyard.

Artificial defect index

Where the defect frequency of an asset population is high, the sum value index will be noted, although the actual asset location would not have experienced as many defects as the rest of the population. If the actual asset location has been subject to a high defect rate and the asset population is in good condition in general, this will be noted. Having high value in both approaches will highlight these devices clearly.

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