With the enormous rise in installed photovoltaic (PV) modules over the past decade, it is to be expected that soon, a massive increase in decommissioned PV modules will arise. Current PV modules are difficult and energy-intensive to recycle, leading to some of the most valuable materials going to waste. To prevent this, new PV module structures have been proposed, with the most promising structure containing a layer of air between the module’s front glass and the solar cell. Due to this replacement of the ethylene vinyl acetate (EVA) layer, the air-filled modules are easier to disassemble and recycle. However, it lowers the module efficiency due to a mismatch in the refractive index of the front glass and air. To overcome the refractive index mismatch of air-filled modules, this study evaluates the performance and degradation behaviour of self-manufactured, liquid-filled PV modules, which are subjected to humidity freeze accelerated ageing and their results are compared to air-filled and EVA-laminated mod-
ules. To achieve this, suitable liquids are selected. Subsequently, several one-cell mini-modules are hand-manufactured, which are filled with air, the selected liquids, and laminated with EVA. The results are obtained by subjecting the modules to 30 cycles of humidity freeze testing and by measuring their electrical characteristics under standard testing conditions. Initial performance measurements show that all four tested liquids, including water (3.7%), polydimethylsiloxane (PDMS) (6.2%), mono propylene glycol (MPG) (5.1%), and glycerol (5.1%), offer substantial efficiency improvements over air-filled modules, with PDMS even slightly outperforming EVA (5.5%). A major point of failure is the PIB edge seal, especially at the liquid injection points, indicating a need for improved manufacturing techniques. The module failures also allowed for disassembly trials, which show that liquid-filled modules can be completely disassembled with ease, allowing for full material recovery. This highlights the reusability potential of liquid-filled designs due to the absence of more permanent encapsulant layers like EVA. The humidity freeze accelerated ageing, subjects the modules to extremely low and high temperatures of -40 °C and 85 °C, whilst also subjecting them to 85% relative humidity. Intermediate visual and electroluminescence inspections revealed mechanical failure in air-filled modules due to edge seal flattening and cell breakage. Whilst after the full 30 humidity freeze cycles the relative degradation in module efficiency in both PDMS and glycerol encapsulated modules (both 5.2%) are comparable to that of an air-filled module (5.5%) but worse than that of EVA (3.9%), whilst the module encapsulated with MPG shows the lowest degradation (2.8%). These results highlight the potential of MPG as a stable encapsulant and underscore the importance of redesigning the liquid injection method for reliability of the polyisobutene edge seal


The humidity freeze accelerated ageing subjects the modules to extremely low and high temperatures of -40 °C and 85 °C, whilst also subjecting them to 85% relative humidity. Intermediate visual and electroluminescence inspections revealed mechanical failure in air-filled modules due to edge seal flattening and cell breakage. Whilst the full 30 humidity freeze cycles show that relative degradation in module efficiency in PDMS and glycerol encapsulated modules (both 5.2%) are comparable to those of an air-filled module (5.5%) but worse than that of EVA (3.9%), whilst the module encapsulated with MPG shows the lowest degradation (2.8%). These results highlight the potential of MPG as a stable encapsulant and underscore the importance of redesigning the liquid injection method for reliability of the polyisobutene edge seal.

As the global energy sector shifts towards electrification to achieve a net-zero future, the demand for photovoltaic (PV) systems is expected to surge. By 2050, an estimated 63.4 TW of installed PV capacity will be required, with annual additions reaching up to 4.5 TW, to help limit global temperature rise to below 2°C. This significant expansion will substantially increase the demand for aluminum, a key material in PV systems. This study presents a material flow model to analyze aluminum demand and its environmental impacts in global PV systems from 2020 to 2050. The model captures the flow of aluminum through module frames, mounting systems, and inverters, while also considering the influence of various parameters such as PV efficiency, aluminum intensity of components, component lifetimes, and recycling rates. In the baseline scenario, cumulative aluminum demand is projected to reach 830.98 mega tonnes (Mt) by 2050. However, through advancements in PV efficiency, reduction in material intensity, extension of component lifetimes, and improvement in aluminum recycling rates, the demand could potentially be reduced to 568.65 Mt.

Despite these mitigation strategies, the rapid growth in PV deployment poses significant challenges for aluminum supply, as global aluminum production is projected to be only 176 Mt by 2050, suggesting substantial supply pressures. Moreover, aluminum production is both energy- and carbon-intensive, contributing significantly to global greenhouse gas emissions. The cumulative emissions associated with aluminum use in PV systems are projected to reach 3534 Mt CO₂eq from 2020 to 2050, highlighting the urgent need for decarbonization in aluminum production. The study emphasizes the critical importance of developing a closed-loop aluminum recycling system for PV components to form a circular economy, which could reduce primary aluminum demand and associated emissions. By adopting a multi-faceted approach, including improvements in technology, materials, and recycling processes, the PV industry can mitigate its environmental impact and support the global transition towards sustainable energy.

Degradation of PV modules reduces their operational lifetime, resulting in an increased levelised cost of electricity (LCOE) and shortening the useful lifetime of valuable materials. One of the leading cause of degradation is moisture. Understanding how this moisture diffuses through PV materials and in different conditions can help prolong modules’ lifetime. This thesis investigates moisture ingress in PV modules, specifically looking at non-Fickian diffusion and material degradation as alternative, and potentially more accurate, ways of modelling it. To simulate
non-Fickian diffusion, a dual-transport method is used; the study finds the approach to deliver more accurate results for EVA, but not for PET. To simulate material degradation, an adapted version of the diffusion coefficient equation is proposed, incorporating a degradation constant based on the materials’ properties. The findings are then used to analyse the behaviour of other PV materials and behaviour in different climates. The simulations find very slow moisture ingress for ionomer under non-Fickian diffusion and a strong deviation from Fickian diffusion. In EVA/PET simulations, non-Fickian behaviour is found to deviate more from Fickian behaviour in warmer climates. Degradation constants are found for the other PV materials. The approach shows promising results for the TPO/PET and ionomer/PET simulations, showing degradation in proportion with their material properties. However, simulations that include EVA appear to strongly limit moisture diffusion, indicating a revision of the EVA degradation constant should be made. TPO/PET degradation simulations in show minimal degradation over 20 years in different climates, but more material degradation in colder climates is found.

As policies and technological advancements accelerate the energy transition, more resources are required to develop sustainable pathways for end-of-life solar modules. Chemical delamination is an attractive option for solar recycling as it has the potential to separate the layers of a module and recover the cell intact. In this work, four primary testing factors were considered to optimize the process: solvent, temperature and residence time with the goal to reduce the reliance on fossil fuel based solvents, improve the reliability of cell material recovery and to attempt to recover cell materials intact. A preliminary solvent screening found three sustainable solvents that could replace current fossil fuel based recommendations. A subsequent optimization under atmospheric conditions found that 60% of the encapsulating EVA could be removed in 3 hours at 160°C. Additionally, this process was observed to be scalable. This research offers a baseline result for chemical delamination that can be built upon to advance the technical and economic viability of this solar recycling method.

The full potential of the Dutch residential solar sector is still untapped, as renters face barriers to the adoption of solar PV systems. These barriers are caused by the mismatch between the PV panel lifespan and the rental contract period of rental properties. This thesis studies the implementation of a product-as-a-service business model for the case of balcony PV systems. By virtue of its flexibility, the business model allows tenants to consider solar energy solutions, hence expanding the residential solar PV market. In addition, the business model applies strategies designed to enhance its circularity, which in turn contributes to enhancing the circularity of the Dutch PV sector. Numerous concepts were developed and evaluated to decide on the winning concept, which consists of a compact, modular PV system that can be easily installed on a wide range of balconies while preserving their aesthetics and offering an optional privacy feature. The business model proved to be profitable for both the company and the end-users, with an Internal Rate of Return (IRR) in the range of 6.1 and 7.6% and cost savings ranging between 12 and 17 €/year. From an environmental perspective, electricity generated under this business model was found to have an 80% lower carbon footprint than the electricity drawn from the grid. Ultimately, this research offers interested stakeholders a blueprint for a novel application of the product-as-a-service business model, that if put into practice can accelerate the adoption of solar PV solutions.

The rapid expansion of the solar industry necessitates understanding the material requirements for photovoltaic (PV) inverters and cabling by 2050 to meet the sub-2-degree target of the Paris Climate Agreement. This thesis formulates a material stock-to-flow model, utilising data from the ecoinvent database 3.10, to evaluate material needs under broad electrification (63 TW) and conservative (15.5 TW) scenarios. The study includes copper, aluminium, steel, silver, nickel, zinc, lead, gold, magnesium, manganese, titanium, and tantalum. Five scenarios were analysed: baseline, learning rate increase, lifetime improvement, recycling, and combined strategies. Key findings indicate that the combined scenario can reduce material demand by up to 68% and waste by up to 98%, with copper identified as a critical material due to its potential supply issues.

This graduation project presented the development of a new Photovoltaic-Thermal panel (PVT) module design, aimed at addressing sustainability challenges in conventional solar panels. The research focused on improving repairability and recyclability by replacing the standard ethylene-vinyl acetate (EVA) laminate with a liquid encapsulant. This transformation enhanced the module's thermal stability and light transmittance and innovatively converted the panel into a pioneering photovoltaic-thermal (PVT) system. Experimental prototypes, conducted at the Photovoltaic Materials and Devices - TU Delft, demonstrated the feasibility of this concept. The outcome of this graduation project, conducted for Biosphere Solar, laid a robust foundation for future developments in sustainable solar energy solutions.

The worldwide energy need is increasing and the share of renewable energy sources is too. To generate electricity from renewable sources, no harm to the environment is done. But producing a PV panel is not without emissions. The amount of emissions during production is researched with a life cycle analysis. In the current PV market 75% of the installed capacity is Passivated Emitter and Rear Cell (PERC), so this is the cell type that will be analysed. The majority of PV panels are produced in China, but for this study Europe is chosen as the location of production. When panels are produced in Europe the electricity mix of Europe is used, which consists of less fossil fuels and more renewable sources. Production in Europe also Previous LCA studies on solar panels are performed on PERC panels but in Asia, or on Al-BSF panels in Europe. One study is found on a PERC panel produced in Europe, and its inventory is used for this study. The goal of this study is to calculate the impact of producing a PERC PV panel and compare it to other studies on PV panels and to other energy sources. The functional unit is 1 kWh, and the system boundary includes the phases cradle-to-gate. Two inventories are used, one for Al-BSF produced in 2018 and one for PERC produced in 2021. The PERC inventory is then altered to represent a panel produced in 2022, 2023, and 2030. The assessment of the panels is done using IDEMAT and Ecoinvent 3.8.

The results for the PERC panel produced in 2022 are: climate change 1.09E-02kcCO2/kWh, ozone depletion1.09E-08 kg CFC11/kWh, ionising radiation 2.50E-05 kBq U-235/kWh, photochemical ozone formation 4.12E-05 kg NMVOC/kWh, particulate matter 2.69 disease/kWh, non-cancer human health 7.37E-11 CTUh/kWh, cancer human health 2.35E-11 CTUh/kWh, acidification 4.40E-05molH+/kWh, freshwater eutrophication 5.39E-07 kg P/kWh, marine eutrophication 5.12E-06 kg N/kWh, terrestrial eutrophication 5.50E-05 mol N/kWh, ecotoxicity 1.06E-02 CTUe/kWh, land use 1.24E-03 pt/kWh, water use 5.25E-05 m3/kWh, resource use fossil 1.59E-01 MJ/kWh, resource euse mineral & metals 1.29E-06. In terms of climate change a PV panel has lower emissions than wind power and the Europe electricity mix, but higher emissions than nuclear power and hydro power. PV has lower particulate matter emissions than nuclear, wind power, and the Europe electricity mix, and higher than hydro power. For noncancer human health, PV is lower than nuclear and wind power, but higher than hydro power and Europe electricity mix. PV power has a lower amount of acidification than wind power, nuclear power and the Europe electricity mix, but higher than hydro power. For ecotoxicity PV has a lower value than wind power and nuclear power, but higher than hydro power and the Europe electricity mix.

A moisture ingress model is developed using the FEM software COMSOL. The model uses Fick’s second law of diffusion to model the diffusion of moisture in the module. The model also reflects the temperature dependent nature of parameters affecting moisture ingress by using an Arrhenius equation. The model is validated with experimental and simulated data from literature showing a good agreement. A brief comparison with alternative models such as analytical models and a simplified numerical model is also made. The model allows to simulate the moisture ingress into different PV modules in different conditions. The moisture ingress in 11 different locations with different climatic conditions is simulated. The moisture ingress is also simulated using 4 different encapsulants and 4 different backsheets. Finally, the model is adapted to simulate the moisture ingress into impermeable backsheet modules.\\

These results are used to find a relation between ambient conditions and the results delivered by the COMSOL model. A simplified relationship is found that holds for the different climates and encapsulants. It is found that the effective relative humidity in the environment is the key parameter in determining the amount of water that will be in the module once it reaches equilibrium. The time that it takes for a module to reach its moisture equilibrium content is determined by the temperature. The presence of these simplified relations can help in estimating the moisture ingress behaviour of a model without the need of carrying out a full FEM simulation. However, the dynamics of the system when using different backsheets does not follow the same simplified relations.\\

The degradation caused by water in the module is also studied. An analytical model is used to predict the degradation observed during damp heat tests. Due to the properties of the analytical model a different approach has to be followed for real life conditions. The degradation model is used to compare the expected degradation under different conditions. This shows that the expected degradation is larger in hot and humid climates while it is minimized in colder climates. The general degradation trend observed for the different climates is: Tropical > Arid > Temperate > Continental > Polar.

The municipality of Amsterdam is swiftly advancing its climate neutrality aspirations within the EU’s Climate Neutral Cities Mission. To accelerate this transition, the municipality has set the target to fully utilize suitable rooftop surfaces for solar panels by 2050. Yet, economic incentives prompt households to replace PV panels prematurely, leading to functional panels being discarded for low-value recycling. This study focuses on evaluating the environmental consequences of lifetime extension strategies at city scale, using Amsterdam as a case study. Employing an innovative prospective Life Cycle Assessment (LCA) approach, this research examines net environmental impact across multiple scenarios, derived from a General Morphological Analysis (GMA). The findings indicate that, despite rapid technological advancements, retaining older panels on buildings proves environmentally preferable to early disposal. Moreover, re-installing functionally disposed panels holds the potential to drive a significant reduction of 790 to 1910 million kilograms of CO2-equivalent emissions, or 126 to 327 million euros in shadow costs. To seize the opportunity for reuse, the municipality is advised to initiate pilot projects urgently and collaborate with European end-of-life management stakeholders. Future research is needed to incorporate the influence of novel recycling practices, emerging circular technologies, regional market shifts toward Europe, and the implications of resource independence. This study underscores the need for sustainable PV panel management strategies to accelerate Amsterdam’s climate-neutral journey.

Two words that could epitomize the focal point of today’s society are ”Energy Transition” and ”Sustainability”. The PV systems are at the forefront of this energy transition. In PV systems, first-generation Si-based PV modules are the market leaders with a market share of 92.5% in 2020. However, sustainability concerns have emerged in recent years regarding the module technology’s post-initial lifespan. In order to make solar panels truly sustainable, it is also important to focus on what happens to these solar panels at the end of their initial intended use. The aim of this thesis is to focus on enhancing the sustainability of the existing PV system by investigating strategies to prolong the lifespan of PV modules through the concept of second life. To accomplish this, the thesis investigates the boundary conditions (the price of the refurbished module) for an economically feasible second use of PV. This research is crucial, particularly given the projected increase in cumulative installed capacity from 1 TWp in 2022 to 5.2 TWp by 2030, in order to meet the Paris Climate Agreement target of limiting global warming to below 1.5°C. To propose a new market structure, it becomes important to understand the existing policies and practices. Overarching policies in the EU, such as the Waste from Electrical and Electronic Equipment (WEEE) directive sets out the targets for collection, preparation for reuse and recycling, and recovery targets for waste generated from EEE including PV modules. Glass and aluminum are the components of the PV module that are recycled. They make up close to 85% of the weight of a PV module and represent only 35% of the total value of the components in a module. Most of the recycling today is
downcycling, meaning that not even 35% is completely recovered. The remaining materials and sometimes the entire module is dumped in a landfill at e1 per module. Recycling these panels can cost between €15 to €30 per panel and post recycling a minimum value of €6.6 and a maximum of €21 can be derived from the recovered materials. However, these materials cannot be directly utilized to manufacture PV panels without further processing. The thesis estimates the quantity of materials in PV systems, such as silver, copper, silicon, glass, and aluminum. This estimation includes the weight of each material within PV modules, as well as the monetary value associated with these materials. In the year 2030, about €86 billion and €58 billion worth of silicon and silver, respectively, are contained in the installed PV panels. If the prevalent EoL processes are followed, these materials will be unaccounted for at the end of their lifetime. All processes must be economically viable and operate within well-established financial boundaries. In this study, the concept of the Levelized Cost of Electricity (LCOE) is utilized as a standardized metric for comparing a new PV module versus a refurbished module and setting up boundary conditions. To emulate the market, two scenarios are considered. On the one hand, the first scenario considers the entire system cost, including the second-hand PV module, Balance of Plant (BoP), and soft costs. In this scenario, a minimum second lifetime of 23 years ensures a positive cash flow for the manufacturers/suppliers. On the other hand, the second scenario considers the placement of a second-hand module into an existing system (eliminating the need for additional BoP and soft costs) and shows that no minimum second life of the panel is needed to ensure a cash inflow for the manufacturers/suppliers. The effect of subsidies and policies on LCOE are also analyzed utilizing discount rates. In general, the higher the discount rate, the higher the resultant LCOE. Finally, a market structure that utilizes the concept of a Product Service System (PSS) and aims to facilitate the utilization of second-life PV modules along with a proposal for the positioning of a Product Service System Provider (PSSP) is presented. Integration of the PSSP into the existing market structure is proposed in a stage-wise manner, utilizing the distribution system operator (DSO) for effective implementation. To achieve this integration, two strategies are recommended, one based on the size and capacity of the installed systems and the other based on geographical boundaries. Additionally, a brief overview of PV subscribe, which is a business model that stimulates the second-life market, is provided.

Technological advances, cost reduction, depletion of fossil fuels, environmental concerns, and growing energy demand are expanding photovoltaic solar energy (PV) in more latitudes and locations. A simple and effective procedure to assess the PV potential of a particular region is to analyse its climatic conditions. In general, climatic studies use the K¨oppen-Geiger (KG) climate classification as a reference. However, KG is solely based on temperature and precipitation, resulting in an unsatisfactory scheme for analyses in the PV field, since the most important variable, solar irradiation, is not considered. Thus, in 2019 Ascencio-V´asquez et al. developed a new worldwide classification based on temperature, precipitation, and solar irradiation: the K¨oppen-Geiger-Photovoltaic (KGPV) climate classification. Even though KGPV is a good improvement, it just consists of a simplified version of the KG groups subdivided into four levels of irradiation: low, medium, high, and very high. Hence, the climate parameters are not considered in a combined manner in the sorting process.

In this project, a new worldwide climate classification directly applicable to PV has been developed. Machine Learning proved to be a convenient tool to achieve this objective. First, supervised learning served to identify and assess the climate variables more correlated to the specific energy yield. More specifically, a Linear Regression model was implemented. Subsequently, these variables were used to create the classification by applying k-means, a clustering algorithm. The classification was optimised following a comprehensive qualitative analysis, resulting in a scheme based on seven climate variables and 20 clusters. By contrast, KGPV considers five variables. Even though it contemplates 24 groups at first, half of them are neglected based on a land-surface ratio and population density criterion, resulting in a classification based on 12 clusters. Hence, the methodology proposed in this work enables identifying new relevant regions. Moreover, “Machine Learning driven PV-climate classification” presents a satisfactory correlation with the specific energy yield, except for very low values, where the correlation is minor.

Lastly, the relationship between climate and degradation rate was explored. The complexity and non-linear behaviour of degradation demand an alternative approach. Random Forests was proposed, but it showed poor performance. It is necessary to be able to predict non-linearities and, at the same time, keep a logical mathematical relation between the supervised and clustering algorithms. In this regard, Multivariate Adaptive Regression Spline (MARS) might be a promising option.

Many functional photovoltaic (PV) modules are decommissioned prematurely, often due to the financially motivated repowering of PV systems. This study assesses under which circumstances there is an environmental incentive to reuse these modules as opposed to recycling and replacing them with new, more efficient modules. A life cycle assessment was conducted, covering the end-of-life treatment, manufacturing, transport and use phase of decommissioned and new modules. The decommissioned modules had an efficiency of 14.7% in 2011, the new modules have an efficiency of 19.79%. The analysis covers two different reuse scenarios (local and export) and two different replacement scenarios, based on the quality of the recycling and the manufacturing country of the new modules.

The impacts are quantified in three categories: global warming potential, eco-cost of resource scarcity and total eco-cost. The findings indicate that, because of rapid technological advancements, the recycling and replacement of 10-year old decommissioned modules generally yield greater environmental benefits than local reuse: the net benefit in terms of global warming is greater after only 5 years. In addition, the calculations show that reusing decommissioned modules in a new PV system is only the preferred strategy from a global warming perspective if the modules are less than 5 years old, if that system is intended to have a (financial) lifetime of 10 years or longer.
However, reuse in a selected European Union member state can provide greater benefits in the global warming potential and total eco-cost impact categories than recycling and replacement. The advantage of export is driven by higher annual irradiation as well as a higher emissions intensity of the electricity mix.

These results contrast the conventional belief that reuse is always environmentally preferable to recycling. Based on this research it can be argued that in most cases of premature decommissioning, there is no strong environmental incentive to reuse the modules, provided that new PV modules are widely available or that the materials go directly to the production of new modules. The annual efficiency increase of PV technology was identified as a key parameter for this outcome.

The photovoltaic (PV) technology plays a significant role in the global energy transition and perovskite solar cells (PSC) have been experiencing rapid development in the past few years. The life cycle analysis (LCA) method evaluates the possible environmental impacts during each life stage of one product, and applying this method to the production processes of perovskite solar cells can assess the environmental implications in each phase of the PSC life cycle, from the initial raw material extraction to manufacturing, operation, and end-of-life stages.

This thesis mainly focuses on the cradle-to-gate stages of LCA, more specifically in raw material extraction and manufacturing of one perovskite PV module. This work selects a perovskite solar module with a mesoporous TiO2 scaffold as the studied module, then defines the goal and scope, including the definition of the research goal, functional unit and system boundaries of this LCA study. Followed by the selection of Ecoinvent V3.8 and Idemat 2023 databases, a new life cycle inventory (LCI) is created both in material and energy aspects. Based on the existing literature inventory, some changes and improvements are made to specialise the life cycle inventory data. Due to the limitation of existing databases, the missing materials and data are collected, self-calculated or replaced to complete the LCI. After calculating and integrating the LCI data by mass allocation, three impact categories are chosen to conduct the life cycle impact assessment (LCIA), which are separately climate change, human health and resource use (fossil). Next, the thesis compares the LCIA results in three different perovskite PV modules, one is the studied perovskite PV module with a silver cathode, one is the same studied module but with a gold cathode, and the other is the literature’s perovskite PV module (with a gold cathode). This thesis compares the environmental impact results in material, energy consumption and total three perspectives, simultaneously analysing the different LCIA performances between the metal gold and silver. Finally this work exerts the
contribution analysis on three life cycle impact categories, explains the LCIA results of three different perovskite solar modules and proposes further research advice.

The LCIA results illustrate that compared to the literature’s module, the studied perovskite PV module with silver cathode has the lowest life cycle environmental impacts in all three impact categories. More specifically, 50% in climate change, 12% in human health and 33% in resource use (fossil) compared to the literature. Furthermore, the metal gold has the highest contribution in all three categories, FTO and energy contribute the second and third both in climate change and resource use (fossil), and silver takes the second occupation in human toxicity.

A next step in the energy transition is to produce green fuels from sunlight. One way to achieve this is via high voltage photovoltaic (PV) devices which can directly drive electrolysis reactions to produce hydrogen or other chemical fuels. Group IV based multijunction (MJ) PV devices are a candidate to function as these high voltage devices.
This work is focused on improving the efficiency of crystalline silicon/nanocrystalline silicon/amorphous silicon (c-Si/nc-Si/a-Si) triple junction (3J) solar cells through better current matching. On top of that, the low bandgap material germanium tin (GeSn:H) is characterized as it shows potential for use as bottom junction in multijunction photovoltaic devices.

Several methods were tried to improve current matching in the 3J PV devices. Varying the nc-Si middle absorber thickness was successful at improving the shortcircuit current density (J 𝑠𝑐 ) in the middle junction, which was the current limiting junction. A range between 35μm ncSi absorber thickness is effective at keeping the middle junction J𝑠𝑐 high while keeping opencircuit voltage (V𝑜𝑐 ) and fill factor (FF) losses at an acceptable level. Varying the n-type nanocrystalline silicon oxide (n-nc-SiO𝑥) intermediate reflective layer (IRL) thickness was also effective at improving the J𝑠𝑐 of the middle junction. Introducing a silver IRL between the n-layer of the middle junction and the player of the bottom junction was ineffective, as was introducing various transparent conductive oxides (TCOs). The J𝑠𝑐 of the middle junction did not increase with the introduction of these layers. In the case of the TCOs, the shunt resistance decreased drastically resulting in decreased V𝑜𝑐 s and FFs. The best performing device in this thesis was manufactured using a 400nm a-Si:H absorber, a 4.5μm i-nc-Si:H absorber and a 60nm n-nc-SiO𝑥 intermediate reflective layer. This device had a V𝑜𝑐 of 1.947V, FF of 0.789, a J𝑠𝑐 of 9.51mA/cm2 and an efficiency of 14.6%, which, to the best of our knowledge, is the highest conversion efficiency achieved to date with this device architecture.

Introducing tetramethyltin (TMT) to process GeSn:H films resulted in carbonization of the films. Carbon passivates Ge dangling bonds better than hydrogen. This reduces the defect density, leading to higher activation energy (E𝑎𝑐𝑡) with high TMT injection rates. A high germane flow rate resulted in dense, relatively defectfree films with a high photoconductivity, low bandgap and near intrinsic semiconductor properties. A high germane flow of around 2 sccm is therefore recommended. Varying the pressure in the deposition chamber offers some control over postprocessing oxidation, where higher pressure results in less oxidation. Changing the radiofrequency power offers a tradeoff between film growth rate and film quality.

The global share of photovoltaic electricity has been expanding at a breakneck pace with CAGR of 27% over the last decade. This resulted in remarkable advancements in photovoltaic technology and design. The performance of the majority of PV modules is determined in laboratories under controlled conditions. Perhaps the climatic conditions on-site are not always stable when the PV module is installed. As a result, modules are subjected to changing environmental stressors such as temperature, relative humidity, UV radiation, and cyclic temperatures. Each of these environmental factors results in a distinct mode and mechanism of degradation, resulting in a loss of performance over time. As a result, determining the rate of degradation of a photovoltaic module is crucial for performance prediction and financial analysis. Primarily, this research identifies a degradation model that is adaptable to various of photovoltaic technologies and designs while maintaining long-term accuracy such model is implemented into PVMD toolbox. We use this model to explore the degradation of photovoltaic modules in a variety of locations around the world, as each site has its own distinct environment. We explore a few well-known climates, namely tropical, steppe, temperate, desert, and cold. According to the study's findings, the lifetime of Cold > Steppe > Desert > Temperate > Tropical and inverse for degradation rates. Financial analysis is critical for determining the value and social impact of a project. Thus, the levelized cost of electricity metric is utilized to determine the economic value of photovoltaic modules under the various climatic conditions indicated previously. To perform this study an LCOE model is incorporated in PVMD toolbox consisting of economic and system variables along with growth rate per year parameter to determine future costs of PV modules. Tropical, steppe, and cold regions are evaluated financially using a variety of economic scenarios and discount rates in order to compare the effect of degradation on LCOE. Tropical zones have the highest LCOE values and the greatest influence on LCOE when the scenario is changed. Cold zones exhibit the greatest range of LCOE values in sensitivity analysis. Finally, as crystalline silicon modules approach their theoretical limit, we discovered the tandem module in quest of more efficient technologies. Due to its broad compatibility with silicon modules, this study focuses on perovskite/silicon tandem modules. Despite this, new research indicates that perovskite/silicon tandem modules are susceptible to degradation. As a result, a model is designed with the objective of assessing the total degradation of tandem modules. We focused on the ability of the perovskite layer degradation to affect the overall degradation of the tandem module by employing normalized power in tandem degradation research. To investigate correlations, the energy production loss owing to degradation in tandem modules is compared to that of an independent crystalline silicon module. Following that, the LCOE of tandem modules is assessed and compared to that of crystalline silicon modules in order to determine the economic impact. According to the study, the perovskite layer in 4T tandem modules degrades at a greater rate than the perovskite layer in 2T tandem modules in order to maintain the same lifetime as independent crystalline silicon modules at the location. When perovskite layers in 2T and 4T degrade at optimal rate, they reach economic equilibrium at 5% and 10% additional module cost over crystalline silicon module.

PV systems in urban environments frequently get shaded by nearby objects, which greatly reduces their yield. A potential solution for such situations is the use of reconfigurable PV modules. They are a type of modules which can reconfigure themselves under varying illumination conditions to ensure optimum yield at all times. The individual PV cells of the module are grouped into reconfigurable units/ cell blocks which can be interconnected in various ways to form a variety of unique configurations. The modules have an inbuilt algorithm which is responsible for controlling the reconfiguration process. There are various kinds of reconfiguration algorithms found in literature, each working with varying input parameters and operating principles. One such algorithm is the short circuit current sensing (SCCS) algorithm developed by the PVMD research group at TU Delft. The algorithm is meant for series-parallel
connected reconfigurable modules and uses each cell block’s short circuit current as input. It is a synchronous reconfiguration algorithm, which means it runs at regular time intervals and not when there is actually a change in the module’s irradiance conditions. Therefore, the aim of this thesis was to develop a robust reconfiguration algorithm with a shade detection mechanism. Consequently, numerous versions of a reconfiguration algorithm with shade detection mechanism were defined and tested using a simulation framework for modelling reconfigurable PV modules. It was observed that the reconfiguration algorithm that performed the best in terms of yield, reconfiguration count and accuracy was the one referred to as the ”CC4AP+IR algorithm”. The algorithm uses the module’s and a single cell block’s operating current and voltage as inputs for shade detection. It was observed that the algorithm reconfigured a fraction of the time that the SCCS algorithm reconfigured and had a DC yield comparable to the SCCS algorithm. The new algorithm was also tested using real-life data to validate its performance. This experiment indicated that if the module were to be run using the new reconfiguration algorithm instead of the SCCS algorithm, it would have run only 6% of the time that the SCCS algorithm ran, but have a comparable DC yield. The significantly lower reconfiguration count is relevant because in practice, the PV modules are connected to power converters which will not be able to tolerate the high fluctuations in output owing to frequent reconfigurations.

In the field of photovoltaics, tandem cells have emerged as a promising technology with high power conversion efficiencies. The academic society grew interest toward this technology due to its high generation capabilities at low production costs. For the time being, most of the research efforts are limited to the lab performance of these cells. However, real life performance studies allow for better understanding of the design effects and yield potentials of this technology. The commercially available yield prediction tools do not involve energy yield prediction models for tandem modules. In addition, they fall short at modelling all the aspects influencing the PV energy yield. The PVMD Toolbox, developed by the Photovoltaic Materials and Devices group at Delft University of Technology, is proposed to serve this need. This thesis presents the work done to develop version 4 of the toolbox. A calibrated lumped element model (CLEM) was developed to simulate the electric performance at the cell level. The CLEM combines the accuracy of physical models with the speed of lumped-element models to generate hundreds of thousands of simulations within a single minute. Additional models were implemented in the toolbox to account for the effects of cell interconnections and metallization on the energy output. Besides, a cell mapping algorithm was developed to reduce the AEY simulation time. This algorithm proved beneficial by reducing the number of required electric simulations by 86% at the small cost of 0.226% bias. Afterwards, the accuracy of the thermal and electric models was validated against two datasets. The simulated results showed a great agreement to the measurements with total energy yield deviations from the measurement of 2.65% and 4.15%, compared to 7.43% in version 3. Therefore, version 4 of the toolbox offers more accurate simulations with a reduced computation speed by a factor of 45.
The CLEM and cell interconnection models were utilized to perform energy yield simulations on tandem modules. Case studies were performed on c-Si/tandem modules to investigate the implications of design choices. After optimizing the STC output of four design options, the toolbox was used to simulate the energy yield for each of them. Then, the optical and electric performance of the modules were studied. The tandem modules proved advantageous, with energy yield increase ranging between 12.91% and 27.13% compared to SHJ modules. In addition, specific yield computations confirmed the sensitivity of tandem modules to meteorological conditions. The final result of this thesis is a first-time combination of modelling spectral irradiance, thermal, and cell and module electric aspects for energy yield simulations of tandem modules.