Introducing innovative energy performance metrics for high-level monitoring and diagnosis of telecommunication sites

•Definition ofnovel performance indexesto detect anomalous energy absorptions in TLC sites.•High level monitoring and diagnosis procedures proven effective within Energy Intelligence (EI) protocols in TLC sites.•Clustering analysis-oriented conceivement of innovative energy metrics.•Enhancement of big data-based diagnosis of TLC sensors and apparatus.•Analysis and optimization of existing hardware/thermal management strategies. This paper aims at deepening the theme of monitoring and energetic diagnosis of telecommunication (TLC) central offices, via the development and application of innovative performance parameters, whose objective is to detect the presence of anomalous energy absorption of the electronic equipment and cooling systems. Firstly, extensive energy analysis is conducted by using the heating degree days (HDD) parameter, which is already consolidated in the field of efficient thermal management of data-centers. Secondly, properly designed indicators are added to this metric: the parameter of central utilization (PUC), which allows distinguishing the multi-use (e.g. combined TLC rooms and offices) from pure central offices; the index of cluster reliability (ICR), which evaluates the stability in time of the acquired data, and the reliability index (RI). The last parameter was specifically introduced to assess if a data center exhibits an unusual energy behavior with respect to a reference energy consumption benchmark, here defined for the group the site belongs to. The innovative contribution of the paper lies in the introduction and joint use of ICR and RI parameters, which can be set up as an effective diagnostic tool for telecommunications sites. The combined verification of current ICR and RI values allows outlining four possible scenarios, differentiated on the basis of the data reliability. Particularly, immediate determination of reliable and unreliable TLC sites is enabled, while the diagnostic potential is exploited to determine whether deeper investigation of energetic consumption trajectories is required. Specifically, the joint assessment of the ICR-RI pair was successfully applied to detecting the presence of anomalous TLC and cooling energy consumption data, as well as whether these abnormalities were due to inefficient thermal management or sensor malfunctioning.