Photovoltaic-Thermal (PVT) modules, alongside Solar Thermal (ST) and Photovoltaic (PV) technologies, offer solutions to energy demands such as electrical consumption, space heating, and domestic hot water of residential buildings. This research employs a model-based approach to analyze how building insulation, solar collector configurations, and seasonal heating modes impact system design. Enhanced insulation scenarios demonstrate potential space heating demand reductions up to 70\%, highlighting the relevance of proper insulation selection.
The findings identify that using a PVT/PV configuration with one module per string is optimal, reducing roof area usage while achieving balanced thermal and electrical energy exchange. The analysis further reveals that higher indoor temperature settings substantially increase heating demands, suggesting significant energy savings potential through temperature set point adjustments. Operational heat supply strategies are adapted to seasonal variations, optimizing the use of solar energy and effectively incorporating aquifer thermal energy storage (ATES) systems as seasonal storage for winter months. But notably, the integration of PVT modules with heat pumps emerged as the primary driver of heat supply, contributing approximately 67\% of the total heat demand.

This thesis aims to enhance the performance of solar cells, specifically those used by Solarge, through comprehensive research on optical characterization and texture fabrication.
In the first part, the focus is on understanding and optimizing the optical properties of Solarge's polymer front sheet and encapsulant. Through meticulous measurements, both computationally and experimentally, the thickness and optical constants of each layer are determined. This information is used to develop an accurate optical model, validated against real-world measurements, to simulate the performance of Solarge's solar cell stack. Additionally, electrical performance is thoroughly evaluated using a combination of computational and experimental techniques.
The second part of the research delves into the fabrication of textures on Solarge's front sheet to minimize optical losses. Two fabrication methods, release papers and Teflon sheets, are examined, and a diverse range of texture morphologies undergo rigorous experimental testing. These textures are carefully evaluated based on their optical and electrical characteristics. By analyzing the findings from the initial texture analysis, a set of requirements is established to guide further investigations and determine the most effective texture for Solarge's solar cell stack. A computational study is conducted to accurately simulate and analyze different texture geometries, including scaled-up bio-inspired textures, random pyramids, and corner cubes, using the advanced capabilities of GenPro4 software. Based on the results obtained, two texture geometries are recommended to Solarge for further optimization. The implementation of the first recommended texture demonstrates a significant increase of 2.65% in power output compared to the current Solarge cell stack.
A holistic perspective is provided through a simple financial analysis, evaluating the potential profitability and economic feasibility of implementing the recommended improvements outlined in this thesis. The research findings offer practical insights for Solarge, enabling them to enhance module performance, reduce optical losses, and potentially generate substantial revenue.
In conclusion, this thesis presents a comprehensive investigation into the optical characterization and texture fabrication for Solarge's solar modules. The research outcomes contribute to an improved understanding of the optical properties of the cell stack components and the impact of surface texturing on performance. By combining scientific analysis, experimental testing, and computational simulations, this research offers valuable recommendations to enhance the overall efficiency and profitability of Solarge's solar cell stack.

Considering the rapidly growing energy demand in worldwide and climate deterioration caused by fossil fuel, the remarkable potential of solar energy has captured the attention of individuals and industries alike. Among different techniques, poly-Si based passivating contacts have shown great performance on solar cell application, which enabling a high efficiency of over 26%. Plasma-enhanced chemical vapor deposition (PECVD) as one of the promising technologies in a-Si contacting layer fabrication has gradually replaced the conventional LPCVD method in industry. However, the accompanied severe ion bombardment is not negligible, especially on its underlying fragile tunnelling oxide. In this work, the impact of PECVD a-Si:H contacting layer deposition on poly-Si/SiO_x passivating contact is investigated. 
PECVD radio-frequency (RF) power for the contacting a-Si layer on the underlying SiO_x is the only variable in this project, varying from 5 W to 55 W, and pinhole density acts as a bridge to help analyse the intrinsic principles. Firstly, the results of a-Si:H thin film characterization suggest that with an increasing RF power, the a-Si:H thin film is grown at a higher deposition rate and becomes porous. In addition, the pinholes in tunnel oxide are inspected by applying the concepts of “selective etching” and “pinhole magnification”. With a two-step five-point sampling method, it is shown that the effect of RF power on the pinhole density is not monotonically increasing. The highest value is found at 25 W. To explain this, a concept of “protective layer” is proposed, which is defined as a buffer layer (contacting layer) formed at the very beginning during a-Si:H deposition. It appears to be more effective when higher RF power (> 35 W) is applied. Another influence on tunnel oxide property is discussed according to the result from XPS measurement. The percentage of Si⁴⁺ species is found in the case of 25 W, corresponding to the highest pinhole density. This proves to some extent that the severe particle bombardment brought by strong power would weaken or directly break the Si-O bonds in the PECVD substrate, that is the tunnel oxide in our case.
As a result of thin film characterization, five factors contribute to pinhole formation: (i) Defects in tunnel oxide from imperfect oxidation leave potential for pinhole formation. (ii) Severe ion bombardments in PECVD deposition are allowed to weaken or break Si-O in SiO_x. (iii) Island growth of a-Si:H contacting layer makes the exposed region in tunnel oxide continue to be damaged. (iv) “Buffer layer” formation protects the substrate from ion bombardments. (v) The tensile stress applied by a-Si:H films during annealing intensifies the formation of pinholes. 
Subsequently, an unexpected result from passivation quality assessment is that higher passivation level is presented with higher pinhole density. The best passivation quality is found in the case of 25 W, with J₀ of 3.3 fA/cm² and iV_oc of 714 mV. Further, a large optimal process window for RF power adjustment is found from 25 W to 35 W, which leads to an iV_oc over 710 mV, with single side J₀ below 3.5 fA/cm². The results from specific contact resistivity indicate that it is positively correlated to the pinhole density. Eventually, the champion passivating contact with a selectivity of 14.37 in this project is expected to yield a maximum efficiency of 28.9% in an ideal c-Si solar cell.

Bifacial modules are expected to have a 60% share in the PV market, which require spectral irradiance data incident on both sides to optimize the design. Sensors that provide spectrally resolved data are expensive and thus a cost-effective spectrally resolved albedometer was designed in two previous PVMD Master Theses. This albedometer measures irradiance in three wavelength bands. The focus of this research is on developing a model that reconstructs the spectral irradiance incident on the top part of the albedometer.

The spectral simulation program SMARTS was converted to MATLAB, after which a Particle Swarm Opimization Algorithm was added to determine values for unknown parameters. The model was first tested against spectra generated by SMARTS. After which both the original model and an model with additional modification coefficients was tested with clear-sky measurements from the albedometer and validated against an EKO spectroradiometer.

The original model proved to fail in the first wavelength band, which caused the other wavelength bands to be reconstructed poorly as well. The adjusted model performed close to the performance of the EKO for clear-sky irradiances above 400 J/Z2 in the total albedometer region, 320-1100 nm.

In 2022, the Power conversion efficiency of perovskite solar cells has achieved an efficiency of >25\%. The cost-effective and flexible perovskite-based photovoltaic has been identified as an ideal solution to increase the integration of photovoltaics in buildings. However, for a large scale implementation, the perovskite photovoltaic must perform at its best and be highly stable. The upscaling of perovskite-based solar cells to the module must be done at minimal losses.

The following research is performed on an opaque double cation p-i-n perovskite module of aperture area 4 $cm^2$. The focus is on the laser scribing patterning technique to develop a quality interconnection in a module. The various laser parameters to be optimized and the approach to achieve a quality P1-P2-P3 scribe for the module are reported. With an ultrashort pulsed laser, the ablation of photoactive perovskite material varies remarkably. There are many possible scenarios regarding the level of ablation of $NiO_{x}$ and ITO using a picosecond pulsed laser with a wavelength of 355nm. In this study, the characterization concerning the emergence of contact resistance at ohmic contact is essential to identify the optimal ablation for interconnection in the module. The optimization is performed using a Scanning electron microscope in EDS mode, optical microscope, and Transmission line measurement. It helps to study the impact of different parameters on interconnection in a device.

This research shows that it is optimal to ablate beyond the HTL to completely remove the $NiO_{x}$ and minimize the contact resistance. The optimized laser parameters for each scribe helped achieve an optical gain, by reducing the dead area in a module. It helped in improving the geometrical fill factor by 3\%. Furthermore, the set of laser parameters also helped improve the electrical performance of a module by minimizing the drop in FF\% when up-scaled from cell to module. The obtained results show an encouraging outlook for further optimization of the module by studying other laser parameters and could fast-track the up-scaling of the perovskite module with negligible interconnection and inactive area losses.

People worldwide have begun to feel the effects of climate change in recent years with unpredictable weather patterns, heatwaves, changes in precipitation, and sea level rise. To help mitigate climate change, photovoltaics (PV) is seen as a technology with the tremendous capability to satisfy the world’s electricity demands by tapping into renewable energy from the sun. There are various PV technologies available, each with its challenges; the newest upcoming material is perovskites. They have showcased an immense potential of further lowering the production costs of solar modules, lower material consumption, and promising high conversion efficiencies. The single cell efficiency has seen incredible improvement in the last decade to 25.7%. The next stage is the scaling up to module level and outdoor deployment. However, some significant challenges remain towards achieving this; one is its response to shading, which has been studied little thus far and will be investigated in this study. The increasing integration of PV into the close surroundings also means that integrated PV will be exposed to much more shading than a typical panel in a solar farm. It is imperative to understand the behavior of perovskite solar cells (PSCs) to shade, primarily due to the poor reverse bias behavior reported in recent years. Since the cells are typically connected in series, shaded cells dissipate energy by going into negative voltages. The response to shading of any material also depends on the interconnection method adopted for the solar cells. So, several interconnections were identified in the project, a few including bypass diodes to improve shade tolerance. Due to the poor reverse bias characteristics of the PSCs, the interconnections and shading were modeled using Matlab and Simulink to better understand the interconnection configuration with the least power mismatch losses. Total Cross Tied (TCT) with bypass diodes was identified as the optimal configuration. Furthermore, the TCT interconnection with bypass diodes was tested experimentally on a shading setup to validate the model. The experiments confirmed the modeled results. None of the modules degraded under shading for the interconnection as the cells did not experience large enough reverse bias voltages. Additionally, tests were conducted to gain deeper insights into the degradation mechanism of perovskites. Shading was tested on a single module, parallel and perpendicular to laser scribes, to confirm that the degradation was due to reverse bias voltage. When the module was exposed to an Electroluminescence (EL) test after shading, it revealed the degradation through the formation of dark spots. The degradation is speculated to form due to the formation of shunt paths caused by the migration of copper into the absorber layer. A similar test was conducted on semi-transparent modules that did not lead to degradation. Also, the modules were tested to find their reverse breakdown voltage. It was observed to breakdown at -6.5V, translating to a cell breakdown at -1.6V. Interestingly, the module’s performance was slightly regained under light soaking for one hour in forward bias due to the reversal of the ion movement, which occurred in the reverse bias condition. The research into the shading of PSCs is still in the early days; many further topics for the future are proposed that could be interesting for later research.

The development in solar cells began with wafer based cells, also called the first generation photovoltaic technology. Most of these wafer based cells were made of crystalline silicon. As a crystalline silicon cell must be relatively thick to absorb most of the incoming energy, the second generation (thin film solar cells) was introduced. In the third generation the focus is more on achieving high efficiencies at low production costs. A way to achieve higher efficiencies is by the use of multi-junction devices. In such devices, different sub cells are stacked onto each other and in this way a larger part of the solar spectrum can be utilized. Moreover, the fabrication costs of multi-junction devices can significantly be reduced by using a cheap processing technique, like plasma enhanced chemical vapor deposition (PECVD).

When germanium and germanium-tin are passivated by hydrogen atoms, Ge:H has its theoretical bandgap in the 0.9-1.1eV range and GeSn:H its bandgap in the 0.6-1.0eV range. The use of such low bandgap materials facilitates absorption of photons in the infrared spectrum, what reduces the non-absorption losses. Their low bandgaps make them perfect candidates to act as the absorber material in a bottom cell in a multi-junction device. Both materials can also be processed by PECVD.

In this thesis about 100 Ge(Sn):H films were PECVD processed in the CASCADE reactor located in the Else Kooi Lab. The objective was optimizing the plasma conditions to obtain device quality thin films. A device quality bottom cell material must fulfil some requirements, like having a low bandgap, being intrinsic and having a high photo response. The influence of various deposition parameters was investigated to characterize their effect on the material properties.

It was found that a densification of Ge(Sn):H generally lead to lower bandgap energies. Densification of these materials can be caused by increasing the substrate temperature (in the 250-300°C range). Next to this, a decrease in hydrogen dilution (in the 100-400 range) also leads to lower bandgap energies for the amorphous Ge(Sn):H films. By combining a substrate temperature of 290°C with a hydrogen dilution of 100, promising a-Ge:H films were processed containing refractive indexes above 5.3, optical bandgap energies below 1.1eV, activation energies above 330meV and dark conductivities below 5∙10-4 Ω-1cm-1. The material properties of the processed a-GeSn:H films were even closer to a device quality bottom cell material. Nevertheless, processing device quality GeSn:H layers remains challenging. Adding relatively large amounts of tetramethyltin (TMT) into the plasma chamber led to clusters of tin and significant oxygen and carbon concentrations throughout the layer. Managing the atomic carbon, oxygen, germanium and tin fractions could be crucial in obtaining device quality bottom cell absorber layers based on GeSn:H in the future.

Crystalline silicon (c-Si) interdigitated back contacted (IBC) solar cell with poly-Si passivating contacts is one of the most promising approaches to achieve high conversion efficiency solar cells. The fabrication of IBC silicon-based solar cells provided by poly-Si passivating contacts is investigated in this thesis. The passivating poly-Si contacts structure used in this work is based on an ultra-thin layer of t-SiOX with optimized poly-Si thicknesses of 250 nm and the implantation parameters of Phosphorous and Boron doping with 6e15 and 5e15 ions/cm2 respectively, at a fixed implantation energy of 20 keV. The influence of the post-implantation annealing conditions is discussed with experimental results, obtained on symmetrical test structures with thermal SiOx/doped poly-Si on each side. The bestobtained passivation result for n+ -poly-Si contact was 728 mV at annealing conditions of 1050°C for 1 minute, while for the p+ poly-Si contact at the same annealing conditions 699 mV is obtained. To enhance the passivation, PECVD deposited SiNX capping layer and annealing in forming gas as hydrogenation processes are carried out. Then, FBC solar cells are fabricated to evaluate the electrical performances, in terms of passivation and carrier transport, of the poly-Si contacts structures, which are prepared with different annealing conditions, in terms of temperature and time. The results obtained from the FBC cells show that increasing the annealing temperature leads to an increase in the passivation thus the VOC. The best-obtained VOC was 706mV for the wafer annealed at 1050°C for 1 minute. To enhance the optical properties of the IBC cells, the surface is textured and the influence of doping dose on passivation of the front surface field (FSF) is evaluated. Four different passivation stack layers SiNX, AlOX/SiNX, a-Si/SiNX, and double SiNy /SiNX are evaluated for FSF implanted with dose of 1e14 ions/cm2. The best-obtained passivation result is from FSF sample passivated with a-Si/SiNX. It shows excellent passivation property with iVOC of 714 mV and a J0 of 7.5 fA/cm2. while the other stacks show lower passivation of iVOC 708 mV for the AlOX/SiNX sample and iVoc=686 mV for the SiNy /SiNX sample. The influence of FGA on the FSF passivation quality is also evaluated. The results show that the sample passivated with a-Si/SiNX experienced a sharp decrease of 35 mV in the iVOC after FGA due to the low thermal stability of the a-Si:H. On the other hand, other FSF samples with passivation stacks of SiNX, AlOX/SiNX, and SiNX /SiNX show a positive influence upon the FGA on their passivation quality as a result of the extra hydrogen diffusion during the FGA which saturates more defects on the c-Si surface. The implantation of the optimized thermal SiOx/ doped poly-Si structure and FSF with a-Si/SiNX passivating layer into the IBC solar cells leads to high-efficiency IBC solar cells. The record cell has a conversion efficiency of 21.04% and 22.15% after the post metallization annealing, VOC of 681 mV, and FF of 78,9 with Jsc of 37.5 mA/cm2

Solar energy is an abundant, scalable, and clean source of energy. With an exponential drop in prices of PV modules, more and more rooftop photovoltaic (PV) systems are being installed worldwide. Since these small-scale PV systems do not use expensive sensors, it is difficult to detect malfunctions for these systems. This could lead to lower energy generation along with financial losses for the owners. Thus, a method for PV yield monitoring is developed for early and remote fault detection. This method does not use the conventional analytical approach as it depends on inaccurately extrapolated weather data. Instead, the proposed method uses data from similar or neighbouring or peer PV systems for estimating the expected energy generation. By comparing the expected energy generation with actual energy generation, a faulty system can be flagged. In this project, information from about 12000 PV systems is used, which includes system design information such as location, number of panels, panel orientation, etc. along with the historical daily energy generation for periods ranging from two months to up to seven years per system.

In this thesis, a machine learning model was developed for predicting energy yields, which uses a Genetic Algorithm (GA) for optimization. This model splits the available data into system design, system location and system yield data. Thus, the model uses these as criteria for finding PV systems similar to the monitored system. Once good peer systems are located, system yield data of those systems are used for estimating the expected energy yields of the monitored system. The three criteria used by the model do not have equal influence on finding good peers, thus, the model had to be trained or optimization was done using the training data. Post optimization, the relative influence of system design: system yield: system location was found to be 0.125:0.875:0 with on average 16 good peers needed for accurate predictions. The proposed model has a mean normalized RMSE of 0.057 and about 95% of the systems tested had an R2 score higher than 0.85. The existing commercial software at Solar Monkey has a mean normalized RMSE of 0.082 and about 83% of the systems tested had an R2 score higher than 0.85.

The predicted energy generation calculated by the proposed model is compared with the actual energy generation to detect any malfunctions that may have occurred in the monitored system. Thus, 120 randomly chosen PV systems were analysed for faults. Based on this, a semi-automatic categorization framework was created with the proposed model as one of the criteria to detect common faults in the system such as missing data, under-performance, over-performance and false positives. Using the categorization framework, certain PV systems were found as interesting examples for under-performance with broken panels or string, over-performance with system size change and false positives. The model is especially useful for separating system design mismatch from actual system malfunctions. With the framework, it was shown how the proposed peer-to-peer model can be used for fault detection along with certain other models.

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.