Smart AI-Monitoring solutions by GradeSens

Smart AI-Monitoring solutions by GradeSens

Smart Monitoring Of Power Transformers

Power transformers are critical assets of the energy supply. Their failure can be at the origin of black-outs which affects large geographical areas and numerous services. Today, the maintenance of power transformers is largely based on preventive actions. With the evolution of the load pattern induced by the renewable energy and the electrification of the mobility,

INTRODUCTION

Power transformers are critical assets of the energy supply. Their failure can be at the origin of black-outs which affects large geographical areas and numerous services. Today, the maintenance of power transformers is largely based on preventive actions. With the evolution of the load pattern induced by the renewable energy and the electrification of the mobility, the maintenance of this critical infrastructure is becoming increasingly important as the classic life expectation rules are not as applicable as it used to be. Therefore, the needs for monitoring solutions are rising. The question is how to implement a solution, that is at same time cost effective, non-intrusive and reliable to detect incipient failures on the windings and OLTC?

In partnership with Efacec, GradeSens has proposed a cost-effective Smart Monitoring solution based on its high-end wireless technology LYRA.

LYRA allows capturing critical data with the minimum commissioning effort and time. This solution has been implemented on the 170MVA 220/63kV power transformer owned and operated by REN (Redes Energéticas Nacionais), Portugal national TSO located in Custoiás sub-station. The transformer is in service since 2007.

PROJECT DESCRIPTION

The project is a pilot intending to monitor the transformer operation over a duration of one year. The monitoring technology relies on Gradesens vibration and temperature sensors as well as transformer load information combined with wireless data collection, advanced signal processing and artificial intelligence. More specifically, sensing data is captured by 8 LYRASens (vibration) and 1 LYRALink (load)

and collected by 1 LYRAGate. The synchronised acquisition ensured by the LYRA radio technology allows getting a global picture of the power transformation vibration pattern along with its operation conditions. The data capturing system is fully independent from the existing network so that this approach is non invasive and safe. Data is then transferred to the GradeSens cloud platform MoonStone for storage and Smart Monitoring.

The monitoring objective is to draw a baseline of the healthy condition of the transformer and eventually assess the preliminary signs of failing behaviours on the power transformer’s windings and OLTC. A detailed article will be available with the monitoring outcome and all the project details.

Many thanks to Efacec and REN for their partnership in this highly promising project.
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