This thesis details the implementation and evaluation of seven machine learning classifiers for the detection of Autism Spectrum Disorder (ASD) using resting-state functional MRI (rs-fMRI) data from the ABIDE I dataset. Two feature representations were compared: traditional Pearson correlation features and graph-based features. Logistic Regression (LR), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP) achieved the highest performance on Pearson correlation features, satisfying all predefined non-functional requirements, with average balanced accuracies up to 64.4% (SVM) and standard deviations below 2.5%. Linear Discriminant Analysis (LDA) narrowly missed the standard deviation constraint with 0.5%.
In contrast to the Pearson correlation features, graph-based features yielded consistently lower balanced accuracies, typically ranging from 54% to 59% across classifiers, underscoring their limited informativeness in the current implementation. Feature importance analysis on Pearson correlation data revealed connections between brain regions involving the inferior occipital gyrus, middle temporal pole, precuneus, and cerebellum as
consistently influential for classification. To facilitate neuroscientific exploration, an interactive tool, NASDA (Neuroimaging Autism Spectrum Disorder Analyser), was developed and demonstrated to fulfil all functional and non-functional requirements for Pearson correlation based analysis using LR as the recommended classification model.
These results highlight the dependency of classifiers performance on the quality of input features and contribute to ongoing efforts to localise robust neurological biomarkers for ASD.

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.

Hybrid PV-wind systems improve land use efficiency but introduce shading interactions, with wind turbines potentially reducing PV output. The PVMD Toolbox is an energy yield simulation tool that accounts for a PV module’s position, mounting, and surroundings, enabling detailed shading analysis. However, high accuracy in modeling how the module perceives its environment comes at significant computational cost. A selective skydome refinement method was developed and implemented in the PVMD Toolbox to perform accurate and efficient shading analysis for PV modules in complex environments. The method begins with a coarse-resolution skydome simulation to identify shaded regions, which are then selectively refined, along with a surrounding buffer. Sensitivity values are recalculated only for the refined areas using targeted ray tracing, while the rest retain values from the initial simulation. This approach reduces ray tracing operations by over 70% and total simulation time by approximately 90%, with a relative DC energy yield error of less than 1%. The method was validated across different initial resolutions, demonstrating a consistent trade-off between computational efficiency and accuracy. In large-scale PV-wind layouts, it captured spatial shading effects reliably and highlighted the importance of fine-resolution input data.

In the Netherlands, 3% of people above 4 years old are diagnosed with autism. Diagnosing is currently done with a psychological assessment, but classifying people with autism using resting state functional magnetic imaging, or rs-fMRI, has become promising. The goal of this project was to see if new features could be found, based on the graph of rs-fMRI data stored in the Autism Brain Imaging Data Exchange (ABIDE) dataset, that had a significant positive influence on the accuracy of a predictive model. To do this, several feature selection modules were researched and coded in Python. Subsequently, these were tested with the features and classification methods created by our partner subgroups. The best performing model, using all data, had an accuracy of 74.26% and a sensitivity of 65.35%. The best performing model using graph features, on all data, had an accuracy of 60.4% and a sensitivity of 46.6%. This indicates that there were no graph features developed that had a significant positive influence on classifying whether someone has autism.

As global temperatures rise and energy demands increase, the need for clean, renewable
energy sources is more critical than ever. Solar energy is one of the key solutions, with the
majority of solar panels currently on the market being made from crystalline silicon. However, emerging photovoltaic (PV) technologies such as perovskite solar cells have already demonstrated efficiencies comparable to those of silicon solar cells, making them a promising contender to achieve even higher efficiencies.

Most of the layers in perovskite solar cells are deposited via spincoating, which is a fast and easy process but can only be done on laboratory-scale. However, deposition through thermal evaporation offers significant advantages, enabling fabrication of nanometer-thin films and facilitating large-scale fabrication needed for future industrialization of perovskite solar cell. Therefore, this research aims to develop perovskite solar cells entirely through thermal evaporation.

The reported number of hole transport materials deposited through thermal evaporation is limited. Recently, fully thermally evaporated perovskite solar cells have been created using the hole transport materials MoOx and TaTm, and these hole transport materials will be studies in this thesis.

The MoOx and TaTm were used as single and double hole transport layer to replace the
reference layer of spincoated PTAA. It was found that the MoOx in direct contact with the pervovskite resulted in a chemical reaction, which negatively affected the energy alignment. The MoOx also showed poor charge carrier selectivity, resulting in high interfacial recombination. Great hole extraction from the perovskite was observed for TaTm, however, a misalignment of the band energy with the electrode hindered the hole collection. Improved hole transfer was found with MoOx and TaTm being used a double hole transport layer. Here, the TaTm functions as a passivation layer between the MoOx and perovskite, while effectively blocking the electrons. In turn, the MoOx improved the energy alignment from the TaTm to the electrode to improve the hole collection.

A thickness optimization of the hole transport layers was also performed. For MoOx as
single hole transport layer, it was found that number of oxygen vacancies decreased with
thickness, leading to less recombination. No change was observed for TaTm as single hole
transport layer when varying the thickness. However, as a double hole transport layer with MoOx, increasing the thickness of TaTm led to an increase in Voc . Ultimately, a thin layer of 2 nm MoOx with a 5-nm thick TaTm showed the most promising results, demonstrating a final efficiency of 4.73%.

As the energy demand keeps rising and the need for clean, affordable energy increases, the switch to completely sustainable energy production comes closer and closer. Solar cells are expected to play a big role in this energy transition. However, the technology of the most used type of solar cell, crystalline silicon, is nearing its limit. This calls for other novel technologies that could surpass it. One of these promising technologies is the perovskite / c-Si tandem cell. This type of cell has shown promising results in recent years, but for it to be commercialized and challenge the current technologies that dominate the market, some steps need to be taken. This thesis focuses on hysteresis, a behaviour commonly shown in perovskite cells, resulting in an uncertainty when measuring the characteristics of these cells. The most common explanation for this behaviour has been due to ion migration under certain conditions. This report, however, looks at hysteresis from a different perspective. It investigates the effect of defects on the hysteresis behaviour, continuing on previous research on this mechanism. It is argued that the defects trap charge near the interfaces, affecting the charge extraction and with that the amount of recombination in the cell. This hypothesis is researched by modelling a state-of-the-art perovskite / c-Si tandem cell in TCAD Sentaurus. This research investigates multiple important parameters to these defects, such as defect density, distribution, energy level, and capture cross-section. With these variables, the hysteresis behaviour as a result of the defects is explored. These results are then used to compare the hysteresis behaviour of the tandem cell with a similar single-junction cell, after which the difference between the two is analysed. It is found the two types of cells have similar hysteresis behaviours, but not equal. With the main deviation finding its origin in the current-limiting that can be displayed by tandem cells.

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 main goal of this project is to utilize a commercially available OpenBCI Ultracortex IV for the measurement of Electroencephalogram(EEG) signals. A pipeline consisting of preprocessing, classification and extraction is employed to transform the motor execution EEG signal into a singular Left or Right output. This output is then further displayed on an Interface that offers the option to either calibrate or play a simple game.

The Ultracortex and relevant software were used to determine the sensor layout, with the placement of the sensors focused on areas which exhibited high cortical activity during motor execution. Experiments were strategically designed to optimize our chance of successful readings and OpenVIBE was used in conjecture with preprocessing filters to save the raw and filtered data which was further sent to the Machine Learning group.

The collected data was analyzed through Spectrograms, Power Spectral Density(PSD) and Event-Related Desynchronization/Synchronization(ERDS) plots. The analysis aimed to confirm whether the desired activity occurred and whether the observed patterns resemble those documented in other research papers.

The data from the headset is live-streamed to the interface via Lab Streaming Layer(LSL) where it undergoes further filtering before being sent to the Machine learning group. This process was done through python libraries which then allowed for efficient and effective communication between the other groups.

This thesis addresses a critical challenge in the field of renewable energy, focusing on the efficient utilization of Photovoltaic-thermal (PVT) systems. Much research has already been done on PVT and there exist many thermal simulation models. However, many of the researches done and existing thermal models are restricted to a specific collector archetype which gives less flexibility in experimentation between multiple archetypes. In addition, many experimental researches require a physical setup for measurements and thermal simulation models would need to be altered for different research approaches and collector archetypes. The primary objective of this thesis project is therefore to create a performance simulation framework model that is suitable for the calculation of the thermal and electrical performance for any PVT archetype. It aims to develop and implement a toolbox application encompassing heat transfer models that can establish a foundation for future research on PVT collector optimization, PVT system integration and PVT performance analysis. This toolbox application will be implemented into the PVMD Toolbox Vogt et al. (2022), housed within the Photovoltaic Materials and Devices research group at TU Delft.

Selected PVT collector: This research has visualized that there is a wide variety of PVT archetypes that can be used for current and future generations of PVT collectors. PVT collectors can be combined with heat pumps, refrigeration pumps, phase change materials and multiple forms of heat collection via fluids or air. These combinations can all contribute to high electrical and thermal efficiencies

Numerical heat transfer model and assumptions: It is possible to calculate heat transfer rates of complex designs when using a Finite Element Method (FEM) approach to calculate the heat transfer within the collector. With the proper convective and radiative equations to the environment, the heat transfer inside the collector and to the environment could be calculated without needing an experimental setup.

Performance calculations: The performance calculations gave insight into the simulated behavior of the PVT collector when operating in real-world conditions. Ranging the inclination angle from 0 to 60 degrees showed that the thermal efficiency became around 55% at an irradiance of 800 W/m2 at 45 degrees. It also showed that differences in dimensions like pipe thicknesses and number of pipes did not affect the thermal performance that much. The daily performance calculations illustrated that the thermal energy lost to the environment can be three times as high as the incoming solar energy due to the low ambient temperatures compared to the inflow temperature. In the summer, PVT can achieve high total efficiencies of around 75% making PVT suitable during those times. The economic analysis showed that a PVT collector can have an LCOE of $0.08/kWh which is lower than the $0.13/kWh of conventional PV.

With the rapid increase in renewable energy demand, various kinds of renewable technologies have been realized. Of particular interest is that they require a certain amount of space, and they may conflict with other land utilization purposes such as food production, protected nature areas, and life-sustaining services, thus the land use pressure is multiplying. For this reason, spatial management is required to analyze the optimal locations for such implementation.

A site suitability analysis is one of the applications that could be used to address this issue. Typically, it was done by mainly examining two constraints: technical and economical criteria, and excluding natural locations from the analysis. The challenge is that without the consideration of an environmental aspect, rich nature areas that are not included in the protection zones, cannot be identified. Therefore, this research aims to conduct the site suitability analysis for ground-based solar energy technology in the Netherlands and advance a suitability model by incorporating the environmental criterion in the assessment.

The study was designed into four phases. Beginning with Phase 1, a compatibility index was developed based on the concept of area degradation. This technique evaluates the compatibility level of an area in terms of an environmental constraint by quantifying the existing land degradation. Subsequently, it was combined with other factors from technical and economical criteria, constructing the suitability index in Phase 2. The Analytic Hierarchy Process (AHP) is a method that was adopted in this combination process. At the end of this phase, five suitability maps were generated from the shift in focus among technical, economical, and environmental criteria. Later in Phase 3, an additional suitability map was developed by analyzing the locations of existing solar projects in the Netherlands. Finally, an example of applying the suitability results was demonstrated in Phase 4 through a case study that set an energy target of 35 TWh as a minimum requirement for solar energy development.

As a result, the preferable locations were specified by the suitability model for this energy realization. They are mostly distributed in the western part of the country (Zeeland, Zuid-Holland, and Noord-Holland provinces) around the major urban and industrial sectors. The proportion of land features in these areas is comprised of 0.4% for border of infrastructure, 17.9% for natural areas, 19.3% for urban areas, and 62.4% for agricultural areas.

Indonesia has recently made a target to shift to more sustainable and renewable energy sources through its energy transition commitment to achieve net zero emissions by 2060. It is widely reported in various literature that the country has significant solar energy potential. At the moment of writing, the current solar PV in construction, potentially the largest in Indonesia, is the Cirata floating solar PV project with an installed capacity of 145 MWp. This study shows that the technical potential of floating solar PV in Indonesia is 33 GWp at 5% water occupancy. Meanwhile, this study finds that the economic potential of floating solar is significantly lower than its technical potential, with only 6.4 GWp at 5% water occupancy. There are various support schemes to increase the economic potential of floating solar in Indonesia. The FSPV can become an alternative solution to renewable energy sources for Indonesia’s energy transition plan. In addition, a potential scenario is provided in this study to achieve the energy transition in Indonesia.

Grid congestion, which results from a larger demand for electricity transport than the available transport capacity, is a challenge in the Dutch energy transition. The growing pace of decentralized renewable energy development in less densely populated areas and the electrification of demand leads to congestion, which potentially hinders the connection of new renewable projects to the grid and slows down the energy transition.

Due to the intermittent behaviour of renewable resources, the grid connection capacity is not used to its full capacity at all times. Cable pooling is introduced as a possible solution to congestion, allowing an existing and a new renewable resource to share a grid connection and improving the utlilisation of the current grid infrastructure.

This thesis’ main objective is to develop a calculation framework to assist developers to evaluate the economic potential of a cable pooling location by optimizing the Net Present Value (”NPV”) of a shared grid connection, considering technical, regulatory, legal, and financial aspects. It aims to provide developers with a tool for making a preliminary decision on whether to continue development for a potential cable pooling location.

The Dutch context is used to identify different grid connecting possibilities, different combinations of wind and solar to form a hybrid farm and different revenue streams. These are used in a methodology to find the optimal installed capacity of the added resource and the impact of on-site storage to one of the hybrid farms. The approach considers the influence of market prices on the technology specific cable pooling business case at an hourly level and accounts for long-term market developments. Other factors accounted for in the tool are the hourly export capacity, defined as the residual space after the export of the existing farm, land size and costs of installation.

A case study of a solar farm oriented to the east-west is used to test the tool and draw conclusions on the potential of cable pooling for this case study. The additions of a wind and solar resource with either south or east-west generation all yield positive NPV values with the highest values seen for the wind addition.

Sensitivity tests for technical and economic inputs show that the results are sensitive to weather data and various economic inputs, but the results of this case study are robust. The case study however considers a relatively large grid connection. Generalizing the results by considering a smaller grid connection shows the value of complementary production patterns.

The impact on the cost-benefit framework by adding a battery is considered. The addition of a battery adds value by peak-shifting the produced energy, but not enough to cover the costs of the battery without any subsidy or alternative revenue streams.

In conclusion, cable pooling shows potential for this case study, for different revenue streams and additions. The tool used to obtain the results can be tailored to different case studies and input scenarios and shows the economical attractiveness of a cable pooling location, based on the Dutch context. The Dutch context shows a promising potential for cable pooling as a method to deal with congestion, but not many projects are present yet. Considering different parties sharing one grid connection, coming to an agreement on the terms can form a hurdle. Therefore, the introduction of more transparent cable capacity calculations by DSOs and a separate subsidy for cable pooling projects could help incentivize the development of more cable pooling projects. The impact of developments such as the ”Use-itor-lose-it” on the cable pooling potential should be monitored closely. Other solutions to dealing with congestion, such as using the fault reserves, should not be disregarded.

Increasing the energy yield per unit area of Photovoltaic (PV) modules is one of the main challenges the PV technology is currently facing. In search of ways to address this issue, solar tracking systems are a favorable solution, which according to literature can enhance the energy yield by up to 45%. Another way is to opt for high-efficiency solar cells. Tandem cells have emerged as a promising technology, achieving efficiencies of over 30%. The integration of these tandem cells with sun-tracking techniques suggests high-performing solar modules. The present work develops a solar tracking model to simulate the performance of tracking PV systems equipped with tandem modules. The model will be incorporated into the PVMD toolbox, a PV modeling software developed within the PVMD group. This software can predict the energy yield of PV systems using self-consistent models for each aspect of the energy conversion.

The current version of the toolbox makes it impractical to include solar tracking due to the time-consuming nature of ray tracing used to compute the irradiance. Ray tracing generates sensitivity values that illustrate how sensitive is the module to incoming irradiance from any direction in the skydome. Initially, this work focuses on substituting ray tracing with an alternative faster approach to express sensitivity based on view factors. The view factor and ray tracing method are compared with respect to computational time and extent of agreement. It was found that the view factor can significantly reduce the computational time from over 12 minutes, as required in ray tracing, to a few milliseconds for a single module orientation. Additionally, the view factor method generates sensitivity values closely matching those from ray tracing. For instance, a mean RMSE of 1.2% between the two methods is achieved, for an albedo of 0.2 and module tilt of 30 degrees. Sun tracking aims to locate the module orientation that maximizes the in-plane irradiance. Directly calculating the irradiance for every orientation to identify the optimal, is not a viable option, as it requires substantial
time. Thus, sun tracking was expressed as an optimization problem and algorithms were employed to address it. Based on the prevailing sky conditions three optimization case studies were defined on an hourly basis: sunny, cloudy, and intermediate hours. Multiple algorithms were compared across the three cases with selected criteria the convergence to the optimum and runtime. Matlab’s surrogate solver and an author-developed algorithm were selected, as a satisfying solution, compromising those two criteria.

Finally, energy yield simulations were performed on perovskite-silicon tandem modules mounted on a dual-axis tracking system. Four locations were selected, representing different real-world conditions: Stockholm, Athens, Bombay and Bogota. Results show the module’s tilt dynamic adaptability to sky conditions: increas- ing nearly to the sun’s zenith when direct light dominates, and lowering when diffuse light is prevalent. Furthermore, the seasonal fluctuations of the energy gain of tracking systems are explored, with locations further from the equator such as Stockholm exhibiting the highest variability of 19% in winter to 36.9% in summer. In addition, the annual energy gained among the locations was found to span between 24.8% (Bogota) and 34.1% (Bombay). An important finding is the direct proportionality in gains from absorbed irradiance to DC and AC yields, illustrating a 1:1:1 ratio. Then, the effect of tracking technology on mismatch losses of tandem modules was examined. Results indicated that tracking has little impact on both the current and power mismatch. For example, the power mismatch losses slightly increased from 1.10-1.46% in static PV systems to 1.29-1.77% for tracking topologies in the locations examined. Moreover, the tandem’s annual energy gain is compared to silicon heterojunction modules. The analysis showed similar gains across locations for both cell technologies.

The Indonesian aims to greatly increase the share of renewable energy sources in the electricity generation mix. Rooftop solar photovoltaics (RTSPV) are a potential generation method that can be used in support of this, with Bali chosen as a case study. No estimates of the total technical and economic potential of RTSPV on Bali exist in academic literature. Low spatial resolution statistical methodologies exist to estimate the technical potential of RTSPV, but these are not accurate on the sub-national scale of Bali. Methodologies with a medium spatial resolution are most suitable for an area of the scale of Bali, however existing methodologies cannot be used due to incomplete cadastral data. In this thesis a novel methodology is introduced that allows the use of incomplete cadastral data, in combination with land use data, to estimate the total rooftop area in a region at a medium spatial resolution. The total rooftop area is then used to estimate the total technical potential and the total economic potential. Using this method, the rooftop area of Bali is estimated to be 130 km2, and the technical potential 22.9 TWh/year. The economic potential for RTSPV is estimated to be zero, as RTSPV cannot compete with conventional generation methods at current capital costs (CAPEX) of RTSPV components of 1200 USD/kWp. It is estimated that at a CAPEX of less than 870 USD/kWp sufficient electricity can be generated annually to fulfill the estimated annual demand of Bali of 5.7 TWh. 96% of the entire technical potential can be achieved at or below the cost per kWh of conventional generation methods if the price of RTSPV installations decreases to below 650 USD/kWp. If the compensation paid by the Indonesian state electricity company PLN for RTSPV electricity that is supplied
to the grid is increased from 65% to 100% of the consumer electricity price, residential RTSPV installations can become economically viable at the current CAPEX of 1200 USD/kWp. This thesis will enrich existing literature on RTSPV potentials by introducing a novel methodology that can be applied in other regions with incomplete cadastral data. In addition, it provides a blueprint to estimate RTSPV potentials for other parts of Indonesia, and it supports policy makers by giving insight in factors that influence the economic potential of RTSPV on Bali and in Indonesia as a whole.

One of the main problems with Instance-level Image Retrieval in video data is that for longer query videos or large amount of image queries, comparing all of the query images to every extracted frame is time-inefficient. This thesis aims to solve this problem by implementing Nearest Neighbour Search (NNS) algorithms and data compression methods, significantly reducing total comparison time. In most NNS use cases, the reference data is provided before reaching the user, allowing methods such as ANNOY or HNSW to partition the data beforehand. However, little research has been done into partitioning the data during run-time. In this thesis, the use of Nearest Neighbor Search and Data Compression methods are discussed for the purposes of matching a query image to a query video, both of which are provided at run-time. The result is an implementation of several state-of-the-art NNS and data compression methods in a system which, based on the amount of query images and the amount of extracted keyframes, selects the optimal comparison method to be used, as well as its optimal parameters if applicable.

Perovskite/Silicon tandem cells are gradually becoming more promising in the field of photovoltaic technology since they have already surpassed the theoretical power conversion efficiency (PCE) limit of single junction (SJ) silicon cells (~30%), while they can be commercially compatible. Several architectures of Perovskite/silicon devices were proposed. The most known of them are four terminals tandem (4TT) and two terminals tandem (2TT). Which are well researched and have already surpassed the highest efficiency achieved by SJ silicon cells. On the other hand, 3TT is less known architecture which have received less attention in research than 2TT and 4TT but seems to combine the advantages of both and eliminate their disadvantages. Although of the few research done on 3TT, they revealed great potential of achieving high efficiency. Yet it is still practically challenging to design and fabricate stable 3TT devices that bring 30% PCE’s goal to reality. To continue unveiling the potential of 3TT perovskite/Si device, more research needs to be done in areas that haven’t been investigated before. And that was the target of this project.
The 3TT device structure proposed in this work is a perovskite top cell on a c-Si IBC bottom cell. And the focus of the project was to investigate and optimize the design parameters of the perovskite top cell as well as the IBC bottom cell to improve the overall efficiency of the tandem device using 2D modelling. To achieve these Objectives, a 2-D simulation model template was built for the mentioned tandem device with the help of Sentaurus TCAD. Further, the model template has been validated. Subsequently, the validated model was used to conduct a comparison between the proposed 3TT device and an identical 4TT device to examine the compactivity of the model with other tandem configurations. This has shown that the 3TT model has performed as good as the 4TT model. Both models showed capability of achieving efficiency beyond 30%.
Then, the performance of the 3TT model was examined under different thicknesses of Perovskite layer. This revealed that the 3TT device has the highest efficiency when the perovskite layer has a thickness between 0.5 - 1.2 µm where efficiency higher than 30% can be achieved.
The next step was to investigate and redesign the IBC bottom cell to improve the 3TT performance. First, the device performance under different pitch values in the IBC bottom cell was examined. It was found that the lower the pitch is, the higher the performance becomes. It was also found that the pitch value doesn’t influence only the bottom cell but also the top cell. Which makes the performance of 3TT device more sensitive to pitch values than the SJ IBC cell. Second, the rear emitter to base ratio in the IBC bottom cell was investigated. Which showed that the emitter/base ratio has less influence on the 3TT behavior when the pitch value is within or less than the range of the diffusion length of the bulk material. But the influence of the ratio grows up when the pitch is higher. The 3TT device has its peak performance when the ratio is between 2:1 to 4:1.
After that, the tandem model was redesigned to corporate all the outcomes that was found in previous steps. This resulted in several scenarios based on best parameters to design 3TT models with the best outcome. Four scenarios have been suggested where each of them can achieve PCE higher than 31.5 %.
Finally, we have studied the effect of surface recombination on the performance of the 3TT device. Which revealed that most of surface recombination losses are coming from the interfaces between perovskite layer and ETL or HTL layers. Therefore, if these surface recombination losses are suppressed, that will lead to a PCE higher than 33 %.

With the increased market share of bifacial modules, it is becoming increasingly important to have sensors that provide information about the irradiance falling into both sides of the modules. Such instruments give more information about the performance of PV modules. They can optimize the material, tilt, and orientation of PV modules according to the surface on which they are installed. However, most sensors in the market do not provide spectrally resolved data, and the ones they do can be expensive.

Because of the preceding, this thesis aimed to design and fabricate a cost-effective spectrally resolved albedometer that will measure the global and reflected irradiance in three different parts of the solar spectrum using photodiodes as sensing elements. This thesis demonstrates how the device's optical, electrical, and mechanical characteristics can be optimized to obtain a more accurate estimation of the spectral albedo.

Additionally, a bio-inspired casing design with self-shading properties was created to reduce the temperature inside the device. Two prototypes were fabricated with two different colour-diffuser configurations (Grey-N-BTK diffuser and White-Hybrid diffuser). Data measured by the final prototypes was calibrated and validated with measurements from an EKO MS700 spectroradiometer. The final sensors have an average error of 20.4% and 7.3% and operate at 17ºC and 8.6ºC above ambient temperature. The albedometers have a volume of 810 cm2 and cost around €978.

Shading on photovoltaic modules is practically inevitable, especially in urban environments. The shadows cast by neighbouring objects on the solar panel force shaded solar cells to operate under reverse bias. In this case, instead of generating power, the shaded solar cell dissipates power, which is converted into heat and may induce the formation of hot-spots. Many attempts have been made to improve the shade tolerance photovoltaic modules. In this work, we focus on solar cells with low breakdown characteristics to build shade tolerant photovoltaic modules. These types of solar cells allow the current flow at low reverse bias voltages (around −4 V). The main design challenge is to maintain high conversion efficiencies while achieving low breakdown voltages.
In order to design shade tolerant photovoltaic modules, the carrier transport mechanisms in the solar cell under reverse bias conditions are firstly investigated. A robust simulation template is created in Sentaurus TCAD to perform a parametric evaluation, including both the structural and operating parameters, of the device I-V characteristics. The silicon heterojunction interdigitated back contact solar cell with a silicon oxide passivation layer is among the most promising cell structures to achieve both the low breakdown voltage and the high efficiency. Band-to-band tunneling happens between the heavily doped p+ and n+ regions at the rear side, which allow charge carriers to recombine without entering the bulk of the solar cell. We analyze the effect of the tunneling mass, the gap distance and the dopants penetration length on the forward and reverse I-V curves. Simulations suggest that it is possible to design high efficiency solar cells with breakdown voltages as low as −1.2 V. In addition, device performances under different temperature and irradiance conditions are analysed for the purpose of further investigations on the system level.
While this research study is mainly focused on the performance of solar cells, the results presented in this thesis facilitate comprehensive system level energy yield analyses of shade tolerant photovoltaic modules with low breakdown voltage solar cells.

Transparent conductive oxides (TCOs) play important roles in information and energy technologies. In the photovoltaic (PV) community, they are normally required to provide sufficient lateral carrier transport towards metal electrodes at the illumination side. Thus, a trade­off between optical and electrical
properties is of critical importance in relevant device fabrications. So far, within the PVMD group, the investigation on TCOs has been mainly focused from an experimental perspective. In this thesis, a firstprinciples approach based on DFT software is investigated to obtain the self­consistent opto­-electrical properties of TCOs.

A comprehensive study is carried out to understand the fundamentals of DFT software, as this is crucial to get reliable results from it. Within the PVMD group, the DFT method is applied on the indium­oxide (IO) host material. It was found that referable results for the (partial) density of states and band
structure could be obtained for this structure using the PBE exchange­correlation (XC) functional. The dielectric function could be obtained by combining the PBE and HSE06 XC functional through the PHSmethod.

Based on a preliminary validation of IO, two case studies are carried out. In these case studies, it is investigated if DFT can be used to compare the opto­-electrical properties of different doping types and ratios. This is done for post­transition metals (Sn), transition metals (W and Mo) and anionic doping
(F). By observing the partial density of states of each element, it was found that significant hybridization of dopant states with the CBM of the IO host states occurs for the cases of Sn­ and F­doping.
Such disturbance in the host conduction band may lead to detrimental influences to the opto­-electrical properties of corresponding TCOs. However, in the cases of W­ and Mo­doped TCOs at commonly used doping concentrations, no hybridization between dopant states and the host conduction band was observed. Furthermore, physical parameters of different TCOs at different doping levels are extracted and compared, such as band gap, effective electron mass, work function and dielectric functions. These results may provide supportive and indicative information for the experimental work.

This thesis work has successfully introduced DFT calculation into TCO investigations within our research group. Although the preliminary results were not sufficiently accurate to predict the opto­-electrical properties of the TCOs in a quantitative way, the qualitative trend can still be used as guidance and support for explaining experimental results. However, many challenges still remain, especially for determining some optical properties like the band gap and dielectric function. Further research is still needed to improve the proposed method.

Solar photovoltaic (PV) technologies offer a renewable alternative to power generation that is based on fossil fuels; however, to meet the rising demand in electricity a substantial amount of surface area is required. This will inevitably lead to the installment of these systems on agricultural land, subsequently intensifying the land-use conflict and threatening food security. To alleviate this, the use of agrophotovoltaic (APV) systems is investigated, which enable the simultaneous production of food and renewable energy. More specifically, the aim of this thesis is to determine the optimal topology for a medium-scale and stationary bifacial APV array, which is simulated under the climate of Boston, USA (42.37˚N, 71.01˚W). Irradiance modelling is performed with Radiance’s raytracing algorithm in combination with the daylight coefficient approach of Daysim and the Perez All Weather sky model, which is then coupled to the crop and electrical yield models to determine the overall land productivity. The modelling approach used is robust, while offering flexible manipulation of the array’s deployment configuration, which is crucial for multivariable optimization. The integration of bifacial PV offers various synergistic effects mainly due to the amplified ground irradiance necessary for crop growth. Owing to the decreased PV density and high elevation from ground, rear irradiance homogeneity and bifacial gain are enhanced. Widening of the row spacing resulted in a logarithmic increase of the incident ground irradiation, while the overall energy yield portrayed a negative exponential trend, which is attributed to the use of bifacial modules. East-west (E-W) facing and vertically installed topologies are better suited for shade intolerant species, or permanent crops since they permit additional light penetration, especially during the winter months. In contrast, south-north (S-N) facing and latitude inclined arrays lead to intense and non-homogeneous shading that is unfavorable for growth during winter or for crops that cannot acclimate to shade; nonetheless, energy yield and land equivalent ratio (LER) are significantly enhanced. Unlike previous studies where only conventional modules were examined, here the potential of a customized one is inspected to assess whether blueberries can grow effectively under shade. By integrating such a module in an E-W hinged PV topology, which is associated with the most optimal shading patterns and schedule, the agrivoltaic performance is optimized. In comparison to the reference case, the land’s productivity is increased by 59% with a reduction in electrical yield by a third. Through this holistic approach that incorporates a multi-scale sensitivity analysis, it is possible to achieve a spherical understanding of the limitations and potential synergies associated with the dual use of land, ultimately encouraging the sustainability of the agricultural sector.