Manjunath Matam
@ucf.edu
Assistant Professor and Solar and Energy Integration Division
University of Central Florida
EDUCATION
B.Tech, M.Tech, Ph.D.
RESEARCH, TEACHING, or OTHER INTERESTS
Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ryan M. Smith, Manjunath Matam, and Hubert Seigneur
MDPI AG
The deliberate removal of photovoltaic modules from a string can occur for various reasons encompassing maintenance, measurements, theft, or failure, reducing that string length relative to others when replacement modules are not available and there are not any viable alternative makes and models that could be inserted. This phenomenon, delineated in our prior experimentally validated research, manifests two significant effects: (1) a shift in the ideal maximum power point and (2) the induction of potentially substantial reverse currents in the shortened strings at open-circuit voltage, VOC. However, the scalability and asymptotic limits of these observed behaviors concerning array size remained undetermined. In this study, we elucidate the operational dynamics of such arrays by manipulating two mismatch-contributing variables in simulated arrays of up to 900 strings: the number of removed modules per string (indicative of the level of mismatch, ranging up to 5) and the quantity of shortened strings (1 to 60). Simulation outcomes underscore that mismatch severity impacts array operation more than the proportion of shortened strings. This research delves into the practical ramifications of operating with shortened strings, including implications for low-irradiance operation and the manifestation of deleterious reverse currents (>35 A in specific cases), emphasizing the need for careful array configuration for optimal performance and safety in these implementations.
Cécile Molto, Jaewon Oh, Farrukh Ibne Mahmood, Mengjie Li, Peter Hacke, Fang Li, Ryan Smith, Dylan Colvin, Manjunath Matam, Christopher DiRubio,et al.
Wiley
Bifacial modules are increasingly deployed in the field and are expected to represent half of the market share within 10 years. Their rear structure differs from monofacial modules to allow additional light absorption. However, it brings new reliability challenges to address. In particular, the risk of potential‐induced degradation (PID) is increased as both module sides are impacted. Different PID processes have been identified in the literature: shunting type (PID‐s), polarization type (PID‐p), Na penetration type, and corrosion type (PID‐c). Their occurrence depends on the photovoltaic system configuration as well as the module's materials. Apart from PID‐s, PID processes are not well understood and extensive research is needed to elucidate the PID scenario and underlying mechanisms. Herein, current knowledge about PID processes and their impact on the main bifacial modules in the market are gathered with the aim to guide future research. Bifacial module technologies and leakage current paths leading to PID are described. Indoor and outdoor PID testing methods are detailed. For each bifacial module technology, the PID processes are investigated with their indicators, mechanism and recovery process. PID‐impacting factors and limitation solutions are finally reported and a state of the art on PID modeling is presented.
Max Liggett, Dylan J. Colvin, Balaashwin Babu, William C. Oltjen, Xuanji Yu, Manjunath Matam, Hubert P. Seigneur, Mengjie Li, Andrew M. Gabor, Philip J. Knodle,et al.
IEEE
As the solar energy industry expands, the reliability and lifespan of photovoltaic (PV) modules have become increasingly important to ensure commercial viability for large-scale applications. To improve reliability and performance, it is necessary to better understand modes of failure through accelerated aging tests, which can identify degradation mechanisms that take a long time to manifest. This work investigates contact corrosion of fielded PV modules using a multi-scale analytical approach. Current-voltage (IV) and Suns-VOC measurements, electroluminescence (EL) imaging, Infrared (IR) imaging, and Ultraviolet Fluorescence (UVF) photography imaging were performed on multicrystalline silicon (multi-Si) and monocrystalline silicon (mono-Si) modules installed in a hot and humid climate. Subsequently, locations of interest were cored from the modules and analyzed using cross-sectional scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS).
Manjunath Matam, Ryan M. Smith, and Hubert Seigneur
IEEE
Photovoltaic (PV) plant owners usually install PV arrays that are larger than the inverter's rated capacity. With a DC to AC ratio greater than unity, the PV array occasionally operates at a sub-optimal point imposed by the inverter. This is common practice in the USA, and is known as ‘clipping.’ Clipping may be implemented by operating the array at voltages below the maximum power point (MPP), or more commonly, above the MPP. Advantages of clipping operation are the utilization of an inverter's full capacity and improved financial break-even time. Regulatory requirements may also mandate reduced power output from an array in a forced clipping situation known as curtailment. However, the long-term impact on the PV array's life, array degradation, aging, hot spots, and module warranty has not been adequately investigated for prolonged off-MPP operation. This paper presents preliminary studies of the potential long-term impact of clipping on the PV array beyond energy production. For this study, the module and string level data, primarily through I-V curves and IR imaging, is investigated along with analysis of inverter electrical data. This preliminary work shows that the PV array exhibits significantly different temperature signatures if operated below the maximum power point as opposed to above, conditions which could be experienced when clipping. In addition, the initial data revealed unique IR imaging patterns: checkerboard patterns at voltages below the MPP and uniform elevated temperature patterns at voltages above the MPP.
Ryan M. Smith, Manjunath Matam, and Hubert Seigneur
Elsevier BV
Manjunath Matam and Hubert Seigneur
IEEE
This paper presents a Machine learning-based algorithm to filter the time-series I-V curves collected from a PV plant. The filter’s objective is detecting and segregating the normal looking I-V curves from the abnormal ones. A non-linear Machine learning regression model was used for this purpose. Initially the model is trained on the labeled data and then tested on a unknown data. The proposed model is trained and tested on the time-series I-V curves of experimental PV strings installed in the field. The obtained model coefficients, results are discussed in the paper.
Manjunath Matam, Hubert Seigneur, and Joseph Walters
IEEE
This paper presents the shortcomings in existing methodologies used for calculating the shunt resistance from the current vs. voltage (IV) curves collected at the indoor lab under controlled conditions or the outdoor under natural conditions. This paper mainly presents the inverse slope methodology and shortcomings surrounding it. Shunt resistance is one of the critical parameters for detecting the low power faults like cracks in the modules caused by extreme conditions. The findings were validated on the IV curves of a PV module from indoor tests and a string from outdoor tests collected at stable conditions. The findings of this paper open a new window of opportunity to search for new calculation methodologies.
Manjunath Matam
IEEE
This paper presents the principles behind the formation of current vs. voltage (IV) curves of a solar photovoltaic (PV) array. More than that, the inherent relationship existing between the strings of the PV array and rows of its IV curve is revealed. Explaining why IV curves always subscribe to a ‘staircase’ shape forms the dominant part of this paper. The findings going to help the PV instructors and teachers explain the IV curves in a better way, and PV analysts now can visualize them better than before. More importantly, findings are presented using graphical illustrations and plots. Hence, laborers, beginners and people with no mathematical background would understand the same way the people already working in the PV.
Manjunath Matam and Joseph Walters
IEEE
This paper proposes a new concept to detect the abnormal profiles of a grid-tied PV plant. Continuous measurement of many parameters and storage in the database is a routine task performed by any commercial Grid-tied PV plant. Detecting the abnormalities in the operation of PV plant is an import part of the reliable operation of the PV plant. Operational factors like electrical and non-electrical faults result in ‘abnormal’ profiles. However, non-operational factors like interruptions in the data transfer protocols found filling the database with ‘corrupt’ data leading to the ‘abnormal’ profiles. Detecting ‘abnormal’ profiles is crucial to the operation of PV plant. A new concept of comparing the daily profiles of a set of parameters and labeling a day normal or abnormal is proposed in this paper. The methods are programmed to detect the data on a given day is ‘normal’ or ‘abnormal.’ Recorded data from a 6.2 kW grid-tied PV plant is used for validating the proposed methods. A sample dataset and proposed methods can be downloaded at https://ieee-dataport.org/authors/manjunathmatam.