On the Construction of Energy Efficiency-based Degradation
Indicator for Photovoltaic Solar Inverters
Jorge Ruiz Amantegui
12
, Phuc Do
1
, Hai-Canh Vu
3
, Marko Pavlov
2
and Nicolas Favrot
2
1
Universit
´
e de Lorraine, CNRS, CRAN, F-54000 Nancy, France
jorge.ruiz-amantegui@univ-lorraine.fr, phuc.do@univ-lorraine.fr
2
Quantom, Feedgy, 75009 Paris, France
mpavlov@feedgy.solar, nfavrot@feedgy.solar
3
Universit
´
e de Technologie de Compi
`
egne, CS 60319, CEDEX, 60203 Compi
`
egne, France
hai-canh.vu@utc.fr
ABSTRACT
Photovoltaic systems are essential in the renewable energy
sector, addressing global energy needs. Photovoltaic (PV) in-
verters, which convert direct current (DC) from solar panels
to alternate current (AC) for grid use, are the most failure-
prone components in these systems. This study aims to de-
velop a degradation indicator based on energy efficiency for
PV inverters to enhance their reliability and lifetime manage-
ment. Through analysis of data from 35 PV plants in central
Europe, involving eight inverter brands and fourteen models,
this research identifies trends in inverter efficiency degrada-
tion. Despite literature suggesting minimal efficiency impact
over time, our findings demonstrate measurable efficiency
degradation, providing a new key performance indicator for
proactive maintenance and replacement strategies.
1. INTRODUCTION
Photovoltaic (PV) systems have become a cornerstone in the
renewable energy landscape, providing a sustainable solution
to the increasing global energy demands. Central to the op-
eration of these systems are PV inverters, which convert the
direct current (DC) produced by solar panels into alternating
current (AC) for grid use. Despite their critical role, PV in-
verters are the most failure-prone components in solar energy
systems, significantly affecting overall system performance
and reliability (Gunda et al., 2020; Lindig et al., 2022). Fur-
thermore, their failure can lead to the shutdown of the entire
system.
Unscheduled interruptions of the system operation will de-
crease production, increase operational costs and reduce the
Jorge Ruiz Amantegui et al. This is an open-access article distributed un-
der the terms of the Creative Commons Attribution 3.0 United States Li-
cense, which permits unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are credited.
quality of service, and profitability. Predicting the lifetime of
the devices allows better scheduling of maintenance interven-
tions to avoid unexpected downtime. Reliability is a concept
that is difficult to measure and quantify, current techniques to
predict wear-out failures include model-based lifetime pre-
diction methods or data-driven methods (Rahimpour et al.,
2022). This is quite a challenging task; it requires an initial
lifetime analysis, which consists of investigating the failure
mechanisms of different components of the system along with
identifying the failure data for the assessment (Abuelnaga,
Narimani, & Bahman, 2021). It is followed with a lifetime
prediction, evaluating failure rates at the component level.
Then the provided failure rates are summed to generate the
system-level lifetime estimation. This process requires the
estimation of both the random failure behavior and the pre-
diction of wear-out failures. The latter includes several steps,
such as collecting data from the mission profile (any possible
stressors to the components), test data, and field data. The
next step is to translate the data to a thermal profile using
an electro-thermal model. After a cycle counting process, a
proper lifetime model should be chosen to provide the num-
ber of cycles to failure (Rahimpour et al., 2022).
Given the complexity and amount of required data of current
methods to develop a lifetime prediction model, this article
proposes to simplify the process of lifetime management via
the measurement of the trend of efficiency of the inverters as
a Key Performance Indicator (KPI). This work will present in
which manners the different failures and performance of the
inverter are related, and how using appropriate methods, the
trend of efficiency of the inverter can be measured.
Inverter efficiency degradation is a topic that has not been
much explored yet in the literature. Current literature sug-
gests that the inverters do not degrade enough over time to
impact the performance of the system significantly. How-
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