Thesis (PhD) - Cyprus International University. Institute of Graduate Studies and Research Energy Systems Engineering Department

Includes bibliography (sheets 99-117)

ABSTRACT
The evolution from fossil fuel sources to environmentally friendly and sustainable
energy sources is one of the critical aspects of the energy transition goal. Solar
Photovoltaic power plants have been leading these sources globally since 2020 as
recent developments in photovoltaic (PV) module manufacturing increased the
efficiency and reduced the PV module prices. Thus, significantly lowering the
levelized cost of electricity (LCOE). The optimal operation of PV plants and
performance loss rate (PLR) of PV plants are decisive in levelized cost of electricity.
Accurate estimation of these factors will provide precise performance guarantees and
reduce investment risks.
The general data pipeline consists of aggregation period, filtering, normalized metric
and statistical approaches used for PLR determination. In-plane irradiation and module
temperature are required for the normalization of measured power output; however,
these measurements are often not available for PV systems. Therefore, this work
proposes a general methodology to analyze PLRs by modelling in-plane irradiation
and module temperature applicable for systems with various orientations and tilt
angles using data from the closest meteorological station.
Furthermore, modelled and measured in-plane irradiation shows variations, especially
under cloudy winter conditions, due to the distance between the analyzed site and the
meteorological station. Owing to this, a diligent filtering approach is also presented in
this study to eliminate miss represented data in modelled parameters due to
meteorological conditions.
In addition, a case study was carried out with the proposed methodology to determine
the PLR of PV installation with a total installed capacity of 1045.32 kWp. Statistical
approaches, seasonal and trend decomposition using locally weighted scatterplot
smoothing (STL), classical seasonal decomposition (CSD) and year-on-year (YOY)
methods coupled with various performance metrics, namely performance ratio (PR),
temperature corrected performance ratio (TCPR), and weather corrected performance
ratio suggested by National Renewable Energy Laboratory (NRELPR) for performing
PLR analysis. As a result, it is found that PLRs of analysed venues, Arazi, Arena and
Stonite, with the YOY approach are -1.2%/year, -0.73%/year and -2.65%/year,
respectively. Furthermore, the STL method demonstrated PLRs of -0.69%/year, -
0.65%/year and -2.91%/year, respectively. On the other hand, the CSD method
generated positive PLRs for some inverters. At the same time, the aforementioned
statistical approaches proposed PLRs close to -2%/year due to 12 months centred
moving average, making the CSD method inappropriate to be used under heavy soiling
environments.
Keywords: Filtering, PLR, STL, YOY