Development of free-cooling detection procedures to support energy intelligence actions within telecommunication environments. (5th November 2018)

• Record Type: Journal Article
• Authors: Sorrentino, Marco; Cirillo, Valentina; Panagrosso, Davide; Trifirò, Alena; Bedogni, Filippo
• Is Part Of: Applied thermal engineering. Volume 144(2018)
• Page Start: 1037
• Page End: 1048
• Publication Date: 2018-11-05
• Subjects: Free-cooler detection -- Diagnostics -- Energy intelligence -- Monitoring -- Telecommunication -- Thermal management; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2018.08.048
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Signal-based detection and assessment of correct use of free-coolers in TLC rooms. Procedure proven effective within Energy Intelligence (EI) protocols in TLC sites. Detection outcomes enable advanced supervisory energy management of cooling systems. Method reliability assessed through extensive experimental validation. Big-data EI fosters lean predictive maintenance in the telecommunication (TLC) sector. Abstract: A signal-based diagnostic technique is proposed to enable remote monitoring of free-cooling (FC) systems operation in telecommunication (TLC) environments. The presented activity falls within a comprehensive energy intelligence action, which TIM-Telecom Italia has been carrying-on since more than a decade in its most strategic central offices and data centers. Main aim is to suitably exploit the available information, about temperature and electrical consumptions, so as to reduce its carbon footprint through strategic energy saving actions. The signal based procedure allows identifying in real-time what is the current status (i.e. properly working, not working or inefficient operation) of FCs in telecommunication rooms. Two alternative methodologies are proposed: one based on the analysis of temperature signal, through Discrete Fourier Transform (DFT), and the other on the evaluation of negative temperature time slope. This paper mostly focuses on the second methodology, which turned out to be the most effective one from a real-world deployability point of view. The results and experimental validation confirm the reliability and suitability of the proposed technique as an effective energy monitoring and diagnostic tool for TLC applications, to be deployed for leaner predictive maintenance tasks aimed at reducing FC failure dependent extra-costs. Further benefits include the synergies with control and/or supervisory energy management levels, which are expected to enable immediate counter-actions and upgrade current control logic, as well as the opportunity of supporting the execution of big-data energy intelligence actions within TLC central offices.