Abstract

A proposal is sought to use this information for quicker and more effective fault localization.

Please find attached - at the bottom of this page - regulations and challenge descriptions in Portuguese and Romanian.

Description

BACKGROUND

Traditional maintenance of MV network is composed of periodical verifications of the status of the network (preventive maintenance) and fault localization and repairs (corrective maintenance).

As modern networks are remotely monitored, and a wide range of measurements and data is available (number protection interventions, fault currents, electrical parameters, power quality measurements, faults registers, etc.), Enel wants to use this information together with network topology to move towards predictive maintenance.

Among the many advantages of predictive maintenance are:

• periodicity of preventive maintenance does not need to be fixed but according to need, so the number of visits to sites can be reduced and only made when required
• degradation of specific portions of the network can be identified before the presence of a fault that affects service, this way impact on service can be greatly reduced
• the information available can be used for an improved diagnosis of faults during corrective maintenance activities

THE CHALLENGE

Solvers are asked to propose a system that uses the available set of data - plus any additional data considered to be relevant – to help with the introduction of predictive maintenance and to introduce a non-conventional way to locate faults in MV network.

A solution is sought to both reduce the time required for fault localization and introduce predictive maintenance.

The solution

• should be suitable for all different types of network, underground or overhead (bare conductors, aerial cables and covered conductors).
• should identify
  • the affected section of the network, reducing the time currently spent in identifying the affected section
  • the specific localization of the fault, reducing the effort spent in following the line to find the problem
  • the specific faulted component (switchgear, disconnector, insulator, joint, cable, conductor, transformer etc.).
• must be data-driven
• must keep in consideration the current set of available data
• additional data collection can be proposed, both permanent measures and temporary measurements (e.g. for fault localization)
• the solution must reduce the current number of visits to site for preventive maintenance
• the solution must provide guidance during corrective maintenance to identify the problem

Solvers must present the technical description of the proposal and the procedures to follow.

ESTIMATED BENEFITS

• Reduce cost and time dedicated to preventive maintenance
• Reduce number of faults
• Improve the knowledge on the status of the network
• Improve resolution time during corrective maintenance

In 2017 Enel I&N companies spent roughly 300 M€ on in preventive maintenance and approximately 500 M€ in corrective maintenance.

EVALUATION CRITERIA

• Cost of solution
• Effectiveness of preventive maintenance implementation
• Effectiveness of fault localization
• Effectiveness of fault classification
• Easy to implement
• Implementation time
• Universal use (can be used in all types of network)
• Lack of constraints

The proposed challenge will support Enel towards achieving its commitments with the Agenda 2030 and will contribute particularly to the following SDGs:

SDG 9: Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

The use of the requested system in the O&M procedures will contribute to safer and more resilient infrastructures.

Any questions about this challenge can be e-mailed to your local focal point (list of focal points in Regulations)