Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

S Theocharides, G Makrides, A Livera, M Theristis… - Applied Energy, 2020 - Elsevier
A main challenge towards ensuring large-scale and seamless integration of photovoltaic
systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high …

Experimental and numerical performance analysis of a converging channel heat exchanger for PV cooling

AAB Baloch, HMS Bahaidarah, P Gandhidasan… - Energy conversion and …, 2015 - Elsevier
An experimental and numerical investigation of a cooling technique called as converging
channel cooling intended to achieve low and uniform temperature on the surface of PV …

Comparison of different simplistic prediction models for forecasting PV power output: assessment with experimental measurements

M Wang, J Peng, Y Luo, Z Shen, H Yang - Energy, 2021 - Elsevier
This paper tested the energy outputs of different types of PV modules and evaluated the
accuracies of different simplistic PV module power prediction models. A test rig was …

Impact of duration and missing data on the long-term photovoltaic degradation rate estimation

I Romero-Fiances, A Livera, M Theristis, G Makrides… - Renewable Energy, 2022 - Elsevier
Accurate quantification of photovoltaic (PV) system degradation rate (RD) is essential for
lifetime yield predictions. Although RD is a critical parameter, its estimation lacks a …

Performance loss rate of twelve photovoltaic technologies under field conditions using statistical techniques

G Makrides, B Zinsser, M Schubert, GE Georghiou - Solar Energy, 2014 - Elsevier
This paper presents a comparison of the annual performance loss rate (PLR) of twelve
different grid-connected photovoltaic (PV) technologies based on outdoor field …

Review of photovoltaic module energy yield (k W h/k W): comparison of crystalline S i and thin film technologies

S Hegedus - Wiley interdisciplinary reviews: energy and …, 2013 - Wiley Online Library
The energy yield (k W h/k W STC) reported from photovoltaic (PV) installations were
reviewed to look for consistent trends in performance between module technologies. The …

Machine learning algorithms for photovoltaic system power output prediction

S Theocharides, G Makrides… - 2018 IEEE …, 2018 - ieeexplore.ieee.org
Accurate photovoltaic (PV) production forecasting is necessary for the optimal integration of
this technology into existing power systems and is important for both grid and plant …

Experimental investigation of the bifacial photovoltaic module under real conditions

W Gu, S Li, X Liu, Z Chen, X Zhang, T Ma - Renewable Energy, 2021 - Elsevier
In this study, the bifacial photovoltaic (bPV) and mono-facial photovoltaic (mPV) modules,
with similar structure, are employed to validate the previously developed coupled model …

[HTML][HTML] Estimation of soiling losses in photovoltaic modules of different technologies through analytical methods

Á Fernández-Solas, J Montes-Romero, L Micheli… - Energy, 2022 - Elsevier
Photovoltaics (PV) has reached high level of maturity in terms of material efficiency and low
production costs. For this reason, nowadays, lot of emphasis is put on the reduction of the …

Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module

O Hachana, KE Hemsas, GM Tina… - Journal of renewable and …, 2013 - pubs.aip.org
The estimation of the photovoltaic (PV) cell/module model parameters could lead to
accomplish a diagnostic tool and to estimate several factors which affect the health state of a …