Advancements in spectral corrections for enhanced photovoltaic performance monitoring and modelling.
| dc.contributor.advisor | Rix, Arnold J. | en_ZA |
| dc.contributor.author | Daniel-Durandt, Francisca Muriel | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. | en_ZA |
| dc.date.accessioned | 2024-02-28T07:46:47Z | en_ZA |
| dc.date.accessioned | 2024-04-26T16:42:21Z | en_ZA |
| dc.date.available | 2024-02-28T07:46:47Z | en_ZA |
| dc.date.available | 2024-04-26T16:42:21Z | en_ZA |
| dc.date.issued | 2024-03 | en_ZA |
| dc.description | Thesis (PhD)--Stellenbosch University, 2024. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT:Innovative advancements in spectral corrections for improved photovoltaic (PV) performance monitoring and modelling are presented, contributing to the sustainability of PV technology in the fight against climate change and reduced reliance on fossil fuels. Traditional performance metrics like the performance ratio (PR) have been improved for irradiance and temperature but not for the spectrum, a known PV performance influence. This study also emphasises the importance of accurate data quality standards for reliable PR calculations. The irradiance used to estimate PR requires decomposition and transposition models. Errors in these measurements translate to over or underestimations of PR. The quantification of the spectrum also remains an obstacle, as spectral variables in developing countries are rare. An assessment of the spectral effects on large PV plants indicated that Normal and weather-corrected PR decrease when air mass and precipitable water are higher. The wavelengths where the most significant changes in these spectral variables occur are when the PV module’s spectral response is higher; thus, a more pronounced spectral effect on performance and power output. Quality control checks are imperative for large irradiance datasets, and as the dataset size grows, these checks become more time-consuming. The study addressed this challenge by proposing an automated quality control procedure, initially evaluated in two case studies. After the automated procedure showed promising results, it underwent further validation across 24 stations within the SAURAN database. A review of the SAURAN database recommended each site’s data quality and identified irradiance patterns to group the stations in clusters. The study developed, tested, and validated a novel decomposition model for hourly direct normal irradiance (DNI) estimations in Southern Africa. The model development methodology utilised he SAURAN database and its quality-controlled stations. The models underwent validation for clearness index levels ranging from 0.175 to 0.875. The substantial reduction in errors in the estimation of DNI for the localised models demonstrated the validity of the model development. Further, using the SAURAN review’s clustering method, clustered models for different areas in Southern Africa were developed. The clustered decomposition models are especially useful when a potential PV plant is within the area. However, if no data is available, the data can be substituted using the SAURAN database. A Southern African model encompassing multiple climates, altitudes and geographical profiles showed enhanced DNI estimations, which has a universal application for the project assessed the sensitivity of spectral variables on the spectral mismatch to address the data scarcity problem in developing countries. The analysis showed how to substitute spectral data when none is available. Aerosol optical depth at 500nm showed a more significant effect on spectral irradiance than ozone, translating to spectral mismatch calculations. The project validated estimating ozone and a constant aerosol optical depth value for spectral mismatch calculation. Before developing the spectral correction methodology, the dataset must exclude potential biases not associated with the spectrum. A study of inverter-level performance analysis of the long-term degradation caused by wind and temperature effects on a utility-scale plant in a semi-arid region indicated that different plant areas degrade at different rates. Observations of higher degradation rates were associated with the areas with less wind and higher temperatures. The wind has a cooling effect, which enhances the PV performance. Another potential bias was the decomposition and transposition models’ inherent temporal bias on different metrics. Hourly-based decomposition models do not translate well to sub-hourly models. These can lead to over or underestimations for the irradiance, affecting the PR estimations. As real-time monitoring trends increase with data-driven techniques, eliminating the temporal bias becomes increasingly important. Using the newly developed decomposition models with anisotropic transposition models showed lower instances of over and underestimating the PR. Wrong estimations offer a distorted view of the plant’s current and predicted performance. A novel spectral correction method, when using short-term measurements, for correcting the PR to align better with the annual PR is presented in this work. The results indicated that, by correcting the spectrum, short-term measurements can predict the annual PR with superior performance over the Normal and weather-corrected PR. The model includes a geographical location-based variable, air mass, and a technology-based variable, a newly defined spectral correction factor with universal application. The novel approach is the first documented effort to address the spectrum’s influence on PR for utility-scale PV plants. The model demonstrated satisfactory temporal transferability from 5- minute to hourly to monthly aggregated data. The project produced significant advancements in PV performance monitoring and modelling by addressing various aspects of spectral corrections. The universal application has widespread applications in the PV industry, performance modelling and monitoring, and forecasting. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Hierdie navorsingsprojek lewer innoverende vooruitgang in spektrale korreksies vir verbeterde fotovolta ¨ıese (PV) prestasiemonitoring en modellering, wat tot die volhoubaarheid van PV-tegnologie in die stryd teen klimaatsverandering en verminderde afhanklikheid van fossielbrandstowwe bydra. Tradisionele prestasiemetrieke soos die prestasieverhouding (performance ratio (PR)) is aangepas vir bestraling en temperatuur, maar nie vir die spektrum nie, al het die spektrum ’n beduidende impak op prestasie. Hierdie studie beklemtoon ook die belangrikheid van akkurate data-kwaliteitsstandaarde vir betroubare PR-berekeninge. Die bestraling wat gebruik word om PR te bereken, vereis ontledings- en transposisiemodelle (decomposition and transposition models). Foute in hierdie metings het oor- of onderskatting van PR tot gevolg. Die kwantifisering van die spektrum bly ook ’n struikelblok wat aangespreek moet word, aangesien spektrale data in ontwikkelende lande skaars is. ’n Evaluering van die spektrale effekte op groot PV-aanlegte het aangetoon dat Normaal- en weer-gekorrigeerde PR afneem wanneer ligmassa (air mass AM) en waterdamp (preciptiable water) ho¨er is. Die golflengtes waar die mees beduidende invloed met hierdie spektrale veranderlikes het, is wanneer die spektrumrespons van die PV-module ho¨er is; dus ’n meer oorheersende spektrale invloed op prestasievermo¨e. Kwaliteitsbeheerkontroles is noodsaaklik vir groot estralingdatastelle, en met ’n toenemende databasisgroottes word hierdie kontroles ’n meer tydsame proses. Die studie het hierdie uitdaging aangespreek deur ’n geoutomatiseerde kwaliteitsbeheerprosedure voor te stel en aanvanklik twee gevallestudies ge¨evalueer. Na die geoutomatiseerde prosedure belowende resultate getoon het, het die metode verdere bevestiging vir 24 stasies van die SAURAN-databasis ondergaan. ’n Evaluering van die SAURAN-databasis het aanbevelings van die datakwaliteit van elke stasie gegee en bestralingpatrone ge¨ıdentifiseer word om die stasies in groepe/klusters in te deel. Die studie het ’n nuwe ontledingsmodel vir uurlikse direknormaalbestralingsskattinge (direct normal irradiance) in Suidelike Afrika ontwikkel, getoets en geldig verklaar. Die modelontwikkelingsmetodologie het van die SAURAN-databasis en sy kwaliteitsbeheerde stasies gebruik gemaak. Die modelle het geldigverklaring vir helderheidsindekse (clearness index) van 0.175 tot 0.875 ondergaan. Die aansienlike foutvermindering in direknormaalbestralingsskattinge vir die gelokaliseerde modelle het die nuttigheid van die modelontwikkeling bevestig. Verder, deur die klustermodelle te ebruik wat in die SAURAN-evaluering ontwikkel is, is geklusterde ontledingsmodelle vir verskeie areas in Suidelike Afrika ontwikkel. Die geklusterde ontledingsmodelle is besonders nuttig wanneer ’n potensi¨ele PV-aanleg in die area is. Indien daar egter geen data beskikbaar is nie, kan die data met die SAURAN-databasis se data vervang word. ’n Suid-Afrikaanse model wat verskeie klimate en geografiese karakteristieke insluit, het verbeterde direknormaalbestralingsskattinge getoon, wat ’n universele toepassing vir die skatting van uurlikse direknormaalbestraling het. Om die probleem van dataskaarheid in ontwikkelende lande verder aan te spreek, het die projek die sensitiwiteit van spektrale veranderlikes vir spektrale wanpassing (spectral mismatch) ge¨evalueer. Die analise het getoon hoe spektrale data vervang kan word. A¨erosol optiese diepte by 500 nm het ’n groter effek op spektrale bestraling getoon as osoon, wat na spektrale wanpassingsberekeninge oorgedra word. Die projek het die skatting van osoon en die gebruik van ’n konstante a¨erosol optiese diepte waarde vir spektrale wanpassingsdoeleindes geldig verklaar. Voor die ontwikkeling van die spektrale korreksiemetodologie, moet die dataset potensi¨ele vooringenomehede wat nie met die spektrum verband hou nie, uitskakel. ’n Studie van omskakelaar-vlak (inverter-level) prestasie-analise van die langtermyndegradasie wat deur wind- en temperatuureffekte op ’n grootskaal aanleg in ’n semi-dro¨e klimaat veroorsaak word, het aangetoon dat verskillende areas van die aanleg teen verskillende versnellings agteruitgaan. Waarnemings van ho¨er agteruitgang is gekorreleer met areas met minder wind en ho¨er temperature. Die wind het ’n verkoelende effek wat die PV-prestasie verbeter. ’n Ander potensi¨ele vooroordeel was die inherente tydresolusie-bevooroordeeldheid wat ontledingsen transposisiemodelle op verskeie metrieke het. Uurlikse ontledingsmodelle word nie oodwendig akkuraat na subuurlikse modelle oorgedra nie en kan lei tot oor- of onderskatting van die bestraling, wat gevolglik die PR-skattings be¨ınvloed. Met die toenemende tendens van huidige-tyd (realtime) monitering met behulp van data-aangedrewe tegnieke, word die eliminering van tydresolusiebevooroordeeldheid uiters belangrik. Die gebruik van die nuut ontwikkelde ontledingsmodelle saam met anisotropiese transposisiemodelle het minder gevalle van oor- en onderskatting van die PR getoon. Onakkurate benaderings van PR het ’n wanpersepsie van die aanleg se huidige en voorspelde prestasie tot gevolg. Die navorsingsprojek het ’n nuwe spektrale korreksiemetode ontwikkel vir die korrigering van PR. Die resultate toon aan dat korttermynmetings kan die jaarlikse PR met uitstekende akkuraatheid bo die Normaal- en WC-PR kan voorspel wanneer die spektrum in ag geneem word. Die nuwe model behels ’n ligging-gebaseerde veranderlike, AM, en ’n tegnologie-gebaseerde veranderlike, die nuutgedefinieerde spektraalkorreksiefaktor, wat tot ’n universele toepassing gevolg het. Die nuwe benadering is die eerste gedokumenteerde poging om die invloed van die spektrum vir die PR van grootskaalse PV-aanlegte aan te spreek. Die model het bevredigende tyd-oordragb aarheid van 5-minute tot uurlikse tot maandelikse data getoon. Hierdie projek het beduidende vooruitgang in PV-prestasiemonitoring en -modellering opgelewer deur verskeie dele van spektrale korreksies aan te spreek. Die universele toepassing het wydverspreide toepassings in prestasiemodelering en -monitering, en voorspelling van die PV-bedryf. | af_ZA |
| dc.description.version | Doctorate | en_ZA |
| dc.format.extent | xxi, 171 pages : illustrations | en_ZA |
| dc.identifier.uri | https://scholar.sun.ac.za/handle/10019.1/130413 | en_ZA |
| dc.language.iso | en_ZA | en_ZA |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject.lcsh | Photovoltaic power systems | en_ZA |
| dc.subject.lcsh | Spectral corrections | en_ZA |
| dc.subject.lcsh | Spectral Correction | en_ZA |
| dc.subject.lcsh | Spectral irradiance | en_ZA |
| dc.subject.lcsh | UCTD | en_ZA |
| dc.title | Advancements in spectral corrections for enhanced photovoltaic performance monitoring and modelling. | en_ZA |
| dc.type | Thesis | en_ZA |
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