Automation of risk priority number calculation of photovoltaic modules

Moorthy, Mathan Kumar; TamizhMani, GovindaSamy

doi:10.1109/pvsc.2016.7749920

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…RPN calculated on the basis of severity and occurrence rank only. Higher values of RPN mean that particular defects mainly affect the system performance [2] , [3] , [4] .…”

Section: Literature Reviewmentioning

confidence: 99%

A method for failures grouping and priority ranking case study: Operating gas compression plant

2021

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The gas compression plant is a core and major unit in oil and gas industries that have high gas oil ratio or considerable gas production. Compressed gas is needed as fuel, support processing handling, increase reservoir builds up pressure by gas injection as well as a useful product. Gas plants are critical and dangerous working location and it is classified as a critical zone due to circumstance parameters like high pressure, high temperature, gas specifications and the potential to impact to human health, safety, environment and possibility to impact invested revenues in case of incidents. Therefore, all recorded compression plant operational failures shall be assessed and reviewed in order to decrease the unit down time and increase plant safety and efficiency. In general, limited studies were conducted in gas plant maintenance management. This paper studied a working gas compression unit in an operating oil and gas field in order to present the followings: • A model of failures raking and sorting in gas compression plants based on total down time importance (TDTI) grouping. • A model of failures ranking by using the risk priority number (RPN). RPN is giving priorities based on associated risk and TDTI as a new method is providing rankings based on maximum contribution to the total occurred down time. Therefore, the study is elaborating to demonstrate these two methods and highlighted the areas of difference which need attention of the owner and the site working team.

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“…RPN calculated on the basis of severity and occurrence rank only. Higher values of RPN mean that particular defects mainly affect the system performance [2] , [3] , [4] .…”

Section: Literature Reviewmentioning

confidence: 99%

A method for failures grouping and priority ranking case study: Operating gas compression plant

2021

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“…The rate of degradation for performance parameters (P max , I SC , V OC , FF and PPF) were computed using the formula reported in the literature [24]: P max drop = (Manufacturer rated P max − measured power)…”

Section: Calculation Of Rates Of Degradation Of Pv Modulesmentioning

confidence: 99%

“…Table 5 shows the rate of degradation computed using +10% and −10% of the manufacturer's rated power of 50 watts. This is important because we were unable to obtain actual data forof the modules at the time of installation 20 years ago (zero age) and therefore have to use the manufacturer's rated data, which has been used in the literature [24]. The assumption here is that the actual data is ±10% of the manufacturer's rated data.…”

Section: Module Degradation Rate and Power Dropmentioning

confidence: 99%

Correlation of Infrared Thermal Imaging Results with Visual Inspection and Current-Voltage Data of PV Modules Installed in Kumasi, a Hot, Humid Region of Sub-Saharan Africa

Takyi

2017

Technologies

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Abstract:In this study, a photovoltaic (PV) modules site installed from 1997 to 2017 (20 years of outdoor exposure) in the hot, humid region of Kumasi, Ghana in Sub-Saharan Africa was selected in order to study the aging phenomenon and rate of degradation due to long-term exposure. The main purpose of this work was to correlate the performance of 14 PV modules using data from infra-red thermal imaging (hot spot tests), current-voltage (I-V) tests and visual inspection. The modules were first visually inspected followed by electrical performance tests using an I-V curve tracer. Hot spot testing of each module was performed to enable further characterization. The results of the visual inspection using the United States National Renewable Energy Laboratory (NREL) checklist did not show any major observable defects. The results also show that the higher the temperature difference in the hot spot tests, the higher the rate of power degradation. Eleven modules failed the hot spot tests according to the criteria indicated in the literature. The average power degradation rate was 1.36%/year, which is above the industry-accepted range of 0.7-1.0%/year. The results provide evidence of a positive correlation between temperature difference and performance parameters such as power degradation (Pdeg), power performance factor (PPF) and power drop (Pdrop). The power performance factor for all 14 modules fell below the average 80% standard set by most manufacturers for modules operating within the 25-year warranty.

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