As sustainable energy technologies continue to attract growing interest worldwide, comprehending their environmental implications becomes essential. Along with cost optimisation and enhancing efficiencies, it is equally important to reduce a wide range of environmental impacts, which is crucial for attaining global sustainability goals. Silicon Heterojunction (SHJ) solar panels are one such example of a growing sustainable energy technology that are anticipated to take up a considerable share of the global PV market in the coming years, owing to its high achievable efficiency. The goal of this study was to conduct a Life Cycle Assessment on a PV system consisting of Silicon Heterojunction solar cells and modules in order to gain insights for the environmental impacts of such a PV system based on manufacturing in the Netherlands. The study included the production steps of SHJ cells and modules, from raw material to final product and use phase until end of life time. Recyling processes were not included. Inverters and mounting structures were also used to complete the PV system. 4 impact categories were analysed in this study for a rooftop PV system with SHJ cells in 2024. The results for these impact categories were: 22 g CO2-Eq/kWh for Climate Change; 14 g 1.4-DCB-eq/kWh for Ecotoxicity Freshwater; 17.5 g 1.4-DCB-eq/kWh for Ecotoxicity Marine and 0.0016 m2 crop − eq/kWh for Land Use. Similarly, the results for the future scenarios were also reported: Climate change impacts will reduce by more than 10 g CO2-Eq/kWh ; Ecotoxicity impacts will reduce by around 0.6 g 1.4-DCB eq/kWh and land use by 0.0006 m2 crop−eq/kWh over the course of a decade. Then, the contribution analyses were presented for these categories, representing the components and process steps that were major contributors to each of these categories. Finally, two sensitivity analyses were conducted, to see how the environmental impacts change by changing certain parameters. The results gathered in this study, and upon comparing them with the LCA results from earlier published studies showed that the SHJ cell and module manufacturing was more environment friendly than some of the other technologies, along with certain room for improvement. Improving the manufacturing processes and with a change in Dutch electricity mix, in the future scenarios, showed that the environmental impacts will further reduce, making this PV technology highly acceptable and implementable.

The agricultural sector holds the potential to integrate a resilient and renewable energy system due to high penetration of renewable energy sources. This study addresses the obstacles towards this transition. The first obstacle is the Dutch electricity grid. As of 2024, the greatest bottleneck in the Dutch energy transition is the lagging grid capacity. Instead of relying on grid power, matching local generation and demand of energy provides an elegant alternative. The second obstacle is that on-farm activity is powered mainly by diesel, since the majority of the demand is from tractor activities. To these two ends, this report investigates two primary aims: first, to provide an overview of the hourly and seasonal energy demand for dairy and open-field farms; second, to evaluate the feasibility of decarbonizing on-farm energy systems given the current grid capacity. The first aim was achieved by identifying the main energy-consuming activities in both dairy and open-field farming, revealing that dairy farming has consistent day profiles throughout the year, whereas open-field farming shows significant variability depending on crop needs and practices. The activities constituting most of the electricity demand on dairy farms have been found to be 1) milking, 2) milk cooling, 3) water pumping and 4) lighting. Feeding and grassland management (fertilizing and mowing) have been identified as the main diesel-consuming activities. For open-field farming, electricity is consumed largely for crop storage in the form of cooling or ventilation, or a combination. This contribution is small compared to the diesel consumption for field operations (mainly for tillage).
The second aim involved accurate modeling of various photovoltaic (PV) system architectures with TNO’s BIGEYE software and linear programming (LP) optimisation using Open Energy Modeling Framework (OEMOF) to assess their impact on the feasibility of decarbonization. The findings suggest that while the choice of PV systems can dampen the mismatch peaks by several percentages, the type of farm and its specific practices play the most significant role. For open-field farms, minimal crop storage requirements and sowing/harvesting periods, such as broad beans and wheat, that align with PV yield profiles are more suitable for achieving self-sufficiency. Short-term forms of energy storage, shifting loads and clipping maximum PV power are measures that directly enhance self-sufficiency and decarbonization without additional grid reinforcement. The highest self-sufficiency rates reach to 82%. In the discussion, the potential contribution of long-term storage needed to decarbonize the farm types with high mismatch levels is discussed. The report concludes with an outlook for further studies to enhance the reliability of energy demand data and suggests actionable and effective alternatives to grid reinforcement for the successful electrification and decarbonization of the agricultural sector. The most straightforward and pressing step in further research is broadening the scope to matching mismatch profiles with other prosuming systems, such as other farmers, towns and businesses, forming resilient energy communities

Photovoltaics will play a pivotal role in achieving a low-carbon-emission society. Remarkable advancements in the efficiency of crystalline Si (c-Si) solar cells, combined with standardized processes along the whole value chain, have enabled cost-competitive solar electricity production. In order to further decrease the cost of photovoltaic, significant efforts must be dedicated to further enhancing the efficiency of solar cells. The implementation passivating and carrier-selective contacts in recent years has led to a remarkable increase in the conversion efficiency of c-Si solar cells. Solar cells, such as silicon heterojunction (SHJ) and poly-Si/SiOx-based technologies are prime examples of the efficacy of these contacts, as cell efficiencies above 26% have been demonstrated. These achievements can be attributed to the excellent surface passivation properties of the intrinsic amorphous hydrogenated silicon (a-Si:H(i )) and the ultra-thin SiOx interlayers, coupled with the high carrier-selectivity exhibited by the doped Si-based layers. However, a significant limitation associated with these passivating and carrier-selective contacts is related to their optical parasitic absorption losses within the layers. These losses stem from the free-carrier absorption in a-Si:H layers of SHJ solar cells and poly-Si layers, which possess relatively narrow bandgaps, making them prone to absorbing the ultraviolet (UV) portion of sunlight. Consequently, these parasitic absorption losses diminish the amount of light reaching the c-Si absorber, ultimately restricting the short-circuit current (J sc) output of the solar cell. To mitigate these losses, wide-bandgap metal oxide layers, such as MoOx and TiOx, have been proposed as promising alternatives to replace these highly doped Si-based contacts. These metal oxides possess distinct carrier-selective characteristics, primarily due to their differences in work function (WF) with respect to the c-Si, leading to induced band bending within the absorber. Despite significant progress in recent years, several challenges still exist, as metal oxide contacts often suffer from carrier-selectivity issues due to material instability and interface reactions with adjacent layers. This thesis explores several possible strategies to minimize the parasitic absorption losses in passivating and carrier-selective contacts. A considerable portion of the research is devoted to understanding and enhancing the contact properties of the MoOx layer. The focus on MoOx is driven by the challenges it faces with carrier-selectivity, stemming from its low thermal stability and its susceptibility to band alignment issues when combined with various passivating interlayers. An innovative MoOx contact is introduced, incorporating ultra-thin surface passivating interlayers based on Al2O3 films. These ultra-thin interlayers offer substantial advantages, including enhanced surface passivation, minimal parasitic absorption, and improved transport of majority carriers. Additionally, MoOx and TiOx contacts, deposited by pulsed laser deposition (PLD) are also explored for c-Si solar cells...@en

With advancements in the photovoltaics (PV) market, involving increased PV module efficiency and reduced costs, the logical progression is the integration of PV into various surfaces, including vehicles (VIPV). For a driving VIPV, the constant change in irradiance presents a significant challenge. The location, weather, and time are key factors that affect the irradiance prediction. An accurate prediction of solar energy generation is crucial for realizing the full potential of VIPV. In this study, the incident irradiance loss is referred to as shading loss.

This thesis is conducted in collaboration with Delft University of Technology (TU Delft) and the Netherlands Organisation for Applied Scientific Research (TNO). TNO has an existing shading loss model that accounts for the surrounding obstructions and weather effects using a fixed value, where the only variable input is the day of the year. On average, it assumes 27% shading losses yearly. This study has improved TNO’s VIPV shading assessment by incorporating more variables into a new model, thereby contributing to a better estimation of the VIPV energy yield. The inputs of the new model are based on key factors causing irradiance loss, where location data is obtained using a Digital Surface Model (DSM). The new contribution to the DSM-based approach is the Web Coverage Service (WCS), which retrieves height data directly through a URL, eliminating the need for the previous manual operations and building upon the model’s scalability. The improved model determines shading losses along a route using two varying shading indicators: Sky View Factor (SVF) and Shading Factor (SF). It can input various irradiance datasets, including or excluding weather effects, and precisely determines the Sun’s position based on the time and day of the year. The DSM-based approach is validated using a dynamic and static validation dataset, with a SVF≤1. The accurate representation of surrounding obstructions during validation contributes to a good-quality model. Both validation studies differ in inputs based on location, time, and weather conditions. The differences in measured and simulated irradiance values are larger in the dynamic dataset than in the static dataset. Deviations are caused by uncertainties and errors, such as local weather effects, sensor inaccuracies, traffic shading, and LiDAR discrepancies, which is the inability to simulate open or changing structures. Weather variability is the primary factor affecting model quality in this validation study, resulting in no fixed inaccuracy factor for model validity. The validated model can accurately represent the environment, but weather variability should be minimized when comparing measured and simulated irradiance. Therefore, averaging is chosen to compare results in this work as it removes unknown or untraceable data points.

Beyond previous research studies, this work focuses on two public transport case studies, given the systematic routing with a fixed timetable. The first case study includes a car and a bus, and the second, more extensive case study focuses solely on buses. The choice of inputs in both case studies centers on key factors influencing VIPV irradiance loss. In the Bus 40 study, simulations under clear sky conditions and a fixed time around solar noon resulted in shading losses of 22.7% for the bus and 27.7% for the car. Moreover, the simulated shading loss shows a 2.6% relative difference compared to the yearly average TNO value. For the case study considering 27 bus routes in Amsterdam, simulations are performed using averaged KNMI irradiance and all hours a day, where the annual average shading loss resulted in 24.8%. The SF and clear sky irradiance correlate in the first case study and the SVF and average KNMI irradiance correlate in the second case study. However, using clear sky conditions and uniform overcast conditions does not represent realistic weather conditions and leads to a bias in the correlation. Moreover, classified terrain types do not correlate with SVF, in contrast to the reversed approach by Araki et al.

Finally, the model can effectively characterize the shading losses on the route level. However, this methodology falls short when reaching finer resolution, such as when examining smaller route segments or partial shading. The determination of shading losses at the route level can be of further benefit to various stakeholders, such as bus operators who want to determine the optimal bus routes for maximum solar energy generation. In addition, this model can be helpful for policymakers, to predict the required charging infrastructure in a scenario when vehicles are equipped with solar panels. Moreover, this model improves shading loss estimation by accepting a range of datasets instead of TNO’s current approach. By inputting irradiance data for clear skies to complete overcast skies, the shading losses can be predicted in a safer range instead of over- or underestimation based on one shading value.

Large-scale deployment of photovoltaic (PV) technology is imperative for realizing a future sustainable and electrified energy system. Over the past decades, technological advancements that enhance the efficiency of PV technologies have been one of the crucial aspects for significantly reducing the cost of PV-generated electricity. Among various crystalline silicon (c-Si) PV technologies, silicon heterojunction (SHJ) solar cells, which have achieved the highest efficiency of single-junction c-Si solar cells, hold great promise for advancing the energy transition facilitated by PV technologies even further. Moreover, notable efficiency enhancements, which are well beyond the theoretical efficiency limit of single-junction c-Si solar cells, have been experimentally demonstrated by combining SHJ solar cells with semi-transparent perovskite solar cells in tandem configurations. This thesis focuses on addressing the challenges of efficient deployments of doped hydrogenated nanocrystalline silicon-based (nc-Si:H-based) layers for high-efficiency front/back-contacted (FBC) SHJ solar cells and applications of FBC-SHJ bottom-cells in two-terminal (2T) and four-terminal (4T) tandem devices with perovskite top-cells, supported by advanced opto-electrical simulations.@en

Perovskite solar cells (PSCs) have a high potential in PV systems, with total power conversion efficiencies (PCEs) of single junction PSC reaching up to 25.52%. Because of the fast growth of PCE, PSCs has become the emerging star of the PV industry which piqued the attention of the research community. The fact that they can be used as a top cell in a tandem perovskiteSi design further adds to their potential. However, for perovskites to be effective in the solar industry, scalability and stability must also be considered. For a long time, the stability of PSCs has been a major source of concern. Thus, it is important to observe the performance of perovskite carefully in laboratory to understand the behavior under realworld, and thus operational, conditions. Therefore, this work is focused on characterizing several properties and behavior of perovskite devices important for these operational conditions: series resistance losses, behavior under different temperature and illumination levels and a protocol for maximum power point tracking (MMPT).

Performance of photovoltaic modules are widely expressed using their efficiency at Standard Test Conditions (STC). Although, real world conditions largely differ from this standard. Energy yield of photovoltaic modules at a certain location gives a clear indication of the performance of the module exposed to varying weather conditions. Photovoltaic Materials and Devices (PVMD) Toolbox developed at Delft University of Technology and implemented in MATLAB®, aims to simulate energy yield of photovoltaic modules while providing the flexibility of modifying cell-level to module-level parameters of the device. Accurately determining the irradiance falling on the module at a certain location and simulating the electrical properties of a solar cell at realistic conditions is crucial in determining the yield generated by a module. Due to the promising results displayed by the technology, in this study, energy yield of perovskite/c-Si tandem modules are simulated using newly developed daylight and parameter extraction models in PVMD toolbox. Due to high computational efficiency and functionality offered, Preetham daylight model is implemented as an improvement to Perez model currently used in PVMD toolbox. The model considers the effect of Rayleigh and Mie scattering, and turbidity of atmosphere in determining the distribution of diffuse irradiance across the skydome. By implementing the model, three factors can now be determined: luminance distribution, RGB co-ordinates and relative spectral power distribution over the skydome for any location. Luminance is calculated for every point in sky using Perez parametric function that use coefficients derived from simulated data for different sun directions and turbidity values. For all locations considered, Preetham model calculates higher luminance over the year by ~2%. Calculated luminance values normalized against zenith luminance is used to derive CIE xyY values and consecutively, the RGB co-ordinates that are rendered real-time to create images of the skydome for every hour in chosen timeframe. By calculating the relative spectral power distribution, analysis of incident light falling on the module from all points of the skydome is possible which especially deems useful for modelling tandem modules. To accurately simulate electrical properties of solar cell under varying operating conditions, parameter extraction model for simulated ASA J-V curves is implemented using an analytical method. For the c-Si and perovskite cells considered in the study, the reconstructed curves using extracted parameters fits ASA curve with RMSE or 1.98% and 3.02% respectively at STC. Using these models introduced in this study, energy yield of mono-facial and bi-facial 2T/4T tandem modules are calculated and analyzed for Rome, Reykjavik and Alice Springs. Depending on air mass of a location, perovskite thickness of mono-facial 2T tandem devices are optimized to produce maximum specific yield. All considered modules generate highest yield at Alice Springs due to high insolation at the location. The yield difference between modules while using the two daylight models is insignificant at <1%. With an increase in perovskite thickness, energy yield of 2T bi-facial modules increase significantly for high albedo while it drops beyond the optimum thickness due to current mismatch for low albedo. Bi-facial 4T module on high albedo (albedo= 0.85) surfaces show best performance out of all the modules producing 36% higher yield than mono-facial 4T module for Rome.

The Levelized Cost of Electricity (LCoE) produced by PV systems is determined by yield (kWh) and cost of the system. Reducing the LCoE of the solar power can be achieved either by increasing the yield or by reducing the cost. The yield of bi-facial PV systems is promoted by high efficiency and a high bi-faciality factor.

Yield due to the front efficiency depends on the parameters ($V_{oc}$ ,$I_{sc}$ and $FF$) that contribute to that efficiency. It was found that the different parameter helped maximize the yield in each climatic condition. For low irradiation and low operating temperature zones, yield improved when the product $I_{sc} \times V_{oc} $ was increased at the cost of the $FF$. While at equatorial tropical climates with fairly high temperatures, yiele improved when $V_{oc}$ was increased at cost of $I_{sc}$ and $FF$. For high irradiance and high temperature desert climates, yield improved when the product $ V_{oc} \times FF $ increased at the cost of $I_{sc}$. Designing cells to suit the operating conditions of the region improved yield per $W_{p}$ thereby reducing the LCoE.

A large part of the cell processing cost is in the metal (silver) used on the cell. The amount of silver is usually optimized for the cell efficiency (i.e. power in W) delivered under standard test conditions, i.e. a solar irradiance of 1000 W/m2. When the metal patterns were optimized for the yield at a climatic zone, results showed that up to 50\% of silver per cell could be saved (From a reference cell considered). Up to 5\% LCoE improvement was theorized.

The irradiance on the bi-facial modules varies with different system orientations (Equator facing, East west tilted, East West Vertical ). The metal patterns were also optimized for the different system orientation at a climatic condition. The results showed metal patterns can be made more thin when designed for vertical systems.

Advanced c-Si cell concepts try to reach the theoretical efficiency by employing different passivation technologies, grid patterns, etc. Each cell technology will have advantage over the other. This makes it interesting to study if we can attribute a cell concept to a climatic condition where it will outperform other cell concepts.

With the fast expanding photovoltaic (PV) industry, we are currently witnessing an unprecedented evolution of high-efficiency PV technologies in laboratories. The topic of this thesis is certainly among the novel technologies that could eventually break through on the market. Ultra-thin molybdenum oxide (MoOx) layer, as a hole-selective contact in a silicon heterojunction (SHJ) solar cell, was found to be suitable due to its transparency and high work function. This work presents the implementation of a MoOx layer in a 6 inch SHJ solar cell piloting towards an industrial level. Moreover, with MoOx commonly thermally deposited, this report shows the applicability of the electron beam evaporator for large scale deposition.

Despite the fact of the outstanding efficiency of the perovskite-based devices, their current size is
around a few square millimeters. The application of this thin-film technology in module scale requires
an interconnection with optimal laser processing to create a channel for the photo current. In
this project, the relation between each film material and the laser beam is analyzed. Furthermore,
this scribing process is applied to a workingmodule manufacturing.
A semi transparent triple cation-based perovskite module scribing processing has been studied.
An n-i-p structure was used for the device. 200 nm indium tin oxide films were used as the front
and back electrode, to guarantee the transparency. Spin deposited layers of tin oxide and spiro-
OMeTAD were used as the n-type and p-type layers, respectively. A buffer layer between the hole
transmitting film and the anode was applied to enhance the performance; for this purpose, a 20 nm
molybdenum oxide layer is vapor-deposited. This architecture had a performance of 10.95 % for a
single cell, and 4.06 % for a six cells module in front illumination. The laser system is set to work in
the UV range with 1 ps pulse length, 10 kHz frequency and apparent power from 1300 to 1800 for
scribing speed between 30 to 60 mm/s. To further improve the performance of the module, it was
illuminated from the rear side, achieving a 5.9 % efficiency. The results shows a promising outlook
for this technology for novel applications, such was in tandem cell applications.

The goal of this master thesis was to optimize the tunnel oxide passivating contact (TOPCon) concept for p-type substrates and implementation in silicon (Si) solar cells. TOPCon and other passivating contacts are believed to be a crucial link for increasing solar cell efficiency and further reducing the costs of photovoltaic (PV) systems. The concept that comes closest to the theoretical Auger limit is the Si heterojunction cell with a record efficiency of 26.6%[1]. A problem with this type of cells is that the process temperature that is allowed is limited, increasing the processing temperature results in decreasing passivation and thus loss of efficiency. The TOPCon concept can withstand higher processing temperatures, which is beneficial when it comes to applying a transparent conductive oxide (TCO) layer of certain metallization schemes. For n-TOPCon good results have been obtained in the past leading to a record efficiency of 25.7%[2]. For p-TOPCon, the efficiency is significantly lower and the cause of this discrepancy is not fully understood yet. In this work, the boron doped TOPCon configuration was optimized by optimizing all of the individual components of this passivating contact concept. During this work the tunnel oxide, which can be grown using variousmethods, proved essential to obtain a good passivation. A comparison was made between four different growth methods for the tunnel oxide, from which it was concluded that the thermally grown tunnel oxide performed best in terms of passivation quality and thermal stability. The optimal p-TOPCon stack was found to consist of three layers: a thin intrinsic hydrogenated amorphous silicon (a-Si:H) layer, followed by a boron doped a-Si:H layer. The p-TOPCon stack is finalized by depositing a thin silicon carbide (SiC) capping layer, which was also boron doped. Besides passivation, the specific contact resistivity was also investigated. A metallization stack consisting of titanium, palladium, and silver proved to result in the lowest contact resistivity values. The lowest value which was measured was 10 m­cm2, this is below the threshold value for which fill factor (FF) losses are to be expected. Implementing a thin tungsten oxide (WOx) layer underneath this metallization stack resulted in a stark increase in the specific contact resistivity values. Furthermore, the tunnel oxide influenced the contact resistivity values, where a lower oxidation time and temperature resulted in lower contact resistivity values. In order to better understand the correlation between contact resistivity and passivation, the contact resistivity values and corresponding recombination current values were fitted to two different models: the oxide tunneling model [3] and the pinholes model [4]. The measured resistivity values all laid in the saturated regime, whichmade it difficult to exclude one of the two models. The passivation quality of the p-TOPCon stack was improved by altering the tunnel oxide to a thermally grown oxide and optimizing the TOPCon stack. This resulted in an implied open-circuit voltage (iVoc) value of 710 mV and an implied fill factor (iFF) value of 84.5 %. A good contact was obtained with a titanium, palladium, silver metallization. This resulted in a specific contact resistivity value of 10m­cm2.

Monofacial modules capture light that falls on the front side of the module, and convert the solar energy to electricity. Bifacial modules can also capture the light that falls on the rear side of the module. For free standing bifacial modules, this results in a power output increase of 5 to 30% compared to monofacial modules. However, due to the heat generation by rear irradiance, this gain is partly lost. In this work, the effect of cell architecture (bifacial/monofacial) and module layout (bifacial/monofacial) on how much modules heat up under outdoor conditions is examined and the heat input mechanism from indoor measurements investigated. This is important because high temperature decreases the open circuit voltage (Voc) of the cell/module which means less power output...

In order to make the bifacial yield prediction models commercially available, a lot of work their development, improvement and validation is being done by many research institutes. At Energy research center of the Netherlands (ECN), one such model is under development. In this project, couple of aspects were investigated to give better insight into improving the model. The two main aspects of the model that were investigated were the rear irradiance estimation and the temperature prediction of the model.
Analysis of rear irradiance aspect of the bifacial yield model through simulations at low tilt angles and elevations should in practice result low rear irradiance but the results showed the opposite. From the literature, a new factor called acceptance was implemented in the rear irradiance model which led to correction in estimation of rear irradiance. For the temperature model, initially indoor measurements of three laminates of bifacial cells and three laminates of monofacial cells were performed under solar simulator. The experiment resulted in finding differences in measured and cell temperatures for all six laminates. According to measured temperatures, the bifacial cell laminates were hotter than their monofacial counterparts, which may not be correct due to higher absorption of irradiance by backsheets in bifacial cell laminates. The differences in calculated cell temperature and measured temperature were investigated and were found to be different. The heating behavior of all laminates was modelled and heat capacity and heat transfer coefficient found through modelling were found to be in good agreement with literature values. Outdoor measurements were used for temperature analysis of bifacial panels and again the differences in calculated cell temperature and measured temperature were found. Non-steady state temperature model was found to be more accurate for low resolution meteorological and insolation data of less than ten minutes as compared to the steady state model used by current ECN model. The difference between measured and cell temperature was translated in terms of heat transfer coefficient and for this difference, the annual energy yield results showed a variation of 1.45 %.
The results of the project showed improvement of the bifacial yield model by ECN through an improved rear irradiance estimation. Furthermore, non-steady model should be used in case the input meteorological and insolation data is in less than ten-minute interval.