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A structured approach to increase situational awareness in low voltage distribution grids

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Author: Helmholt, K.A. · Groote Schaarsberg, M. · Broersma, T. · Morren, J. · Kruizinga, B. · Wouters, P.A.A.F. · Steennis, E.F. · Baldinger, F.
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source:2015 IEEE Eindhoven PowerTech, PowerTech 2015
Identifier: 530887
doi: doi:10.1109/PTC.2015.7232779
ISBN: 9781479976935
Article number: 7232779
Keywords: asset management · business data processing · condition monitoring · cost benefit analysis · Power cables · Administrative data processing · Asset management · Cables · Condition monitoring · Cost effectiveness · Data handling · Degradation · Distribution functions · Electric power transmission networks · Maintenance · Voltage distribution measurement · Degradation mechanism · Distribution density function · Distribution systems · Low-voltage distributions · Power cables · Situational awareness · Submerged environments · Value determination · Cost benefit analysis · ICT Urban Mobility & Environment · MCS - Monitoring & Control Services SBA - Strategic Business Analysis · TS - Technical Sciences ELSS - Earth, Life and Social Sciences


Wear and tear, electrification and aging of (low voltage) distribution grids require maintenance in order to assure continuous provision of electricity. Situational awareness is required to find out when parts of the grid need maintenance and which parts should be prioritized. The paper proposes a conceptual value model which relates sensor data from the condition of the asset to the potential value of information (i.e. interpreted data) for the distribution system operators. Distribution density functions account for uncertainties in model parameter values. They can be narrowed down by monitoring relevant degradation mechanisms. To this end, degradation processes are simulated in laboratory scale setups, emulating low voltage cables in moist and submerged environments. Understanding fundamental aspects of degradation, failure and value determination of sensor data allows prioritization of maintenance actions that lead to best results in terms of customers-minutes-lost, remaining useful lifetime of assets and cost-effectiveness. © 2015 IEEE.