Network asset management
The management of electricity network assets is one of the cornerstones of a network company’s finances. The tools of this management are timely maintenance and replacement of assets. Risk-based life-cycle management of network assets is based on condition indices, criticality classifications, sensor technology and monitoring, and an efficient analysis of collected information. We study the latest trends of these different sectors and the way these trends can be utilised.
In cable diagnostics (smart cable guard), the increasing development trend is towards in-use online diagnostics. Helen Electricity Network is testing the possibility of measuring partial discharges taking place in medium-voltage cables.
The measurement data thus obtained is analysed with respect to the load, time and the apparent charges of partial discharges produced. With this study, Helen Electricity Network seeks innovative new ideas and procedures that promote and support the commissioning of new technologies.
Deployment of methods that diagnose in-use condition monitoring together with the use of good network planning and high-standard network components provide a basis for even higher security of supply. It also gives information for utilisation in the life-cycle management of network components.
Studies related to cable diagnostics
Feasibility Experiences of On-line Partial Discharge Monitoring of Medium Voltage Cables in Helen Electricity Network Ltd.
Keränen, Hämäläinen, Vepsäläinen: The 11th International Conference on Power Quality and System Reliability, 2019.
Condition assessment of medium voltage underground cables based on tangent delta and partial discharge measurements
Pakonen (Tampere University), Keränen (Helen Electricity Network Ltd.), Heinonen (Dekra International Ltd.), Verho (Tampere University). CIRED 2019. Paper 1866.
Studies related to main transformers
Recognizing the best way to utlilize power transformers' loss heat
Korhonen Emilia. Master Thesis. Lappeenranta University of Technology.
Tiedon hyödyntäminen sähköasemien elinkaarisuunnittelussa
Ruotsalainen, Jari. YAMK. Metropolia.
Automatic Meter Reading
Machine learning for determining the condition of electricity meters