To incentivize solar panel adaptation, a multitude of solutions are actively being researched. Among these solutions are colored solar cells, using coatings or filters to open the door for more architectural expression. In order to help architects explore these possibilities, it is necessary to enable flexible, fast, and realistic visualization. This work explores the modeling of color-coated photovoltaic cells using a physically based bidirectional reflectance distribution function (BRDF), with a focus on the pyramidically textured structures embedded inside many of these cells. The BRDF is analytically derived, modeling light interactions as recursively specular multiple-scattering. The model is parametric, characterizing the surface using its pyramid density and pyramid slant angle, making it generally applicable to homogeneous pyramidic surfaces with uniform pyramid heights. Evaluation indicates the model closely approximates the behavior of generated references at steep viewing angles. Clear avenues of improvement, including corrections at shallow angles, are discussed within the context of future work.

The decarbonisation of district heating networks (DHNs) is one of key ways in achieving the net-zero climate targets, especially in densely populated and energy consumption intensive regions like South-Holland in the Netherlands. As DHNs transition from fossil-based to renewable and electrified heat sources, the interactions with the electricity distribution network (EDN) becomes increasingly more critical. Nevertheless, current operational models and planning approaches often treat the development of heat and electricity networks separately, not considering their interactions and overlooking the operational and infrastructural challenges that arise from their growing interdependence.

This thesis addresses this gap by presenting an integrated modelling framework that combines an operational optimisation model of the South-Holland DHN, developed using PyPSA, with a time-series power flow analysis of the South-Holland EDN using pandapower. The South-Holland case study is carried out in which the implemented framework simulates hourly network operations across the future energy scenarios for the years 2030, 2040 and 2050. These scenarios are driven by real-world market data of electricity, natural gas and CO2 prices, weather patterns, as well as future heat and electricity demand profiles. This master thesis is part of the TU Delft research project "DEMOSES" and is done in collaboration with Eneco and Stedin.

The results highlight that the large-scale introduction of electrified heat sources in the South-Holland DHN, such as heat pumps, electric boilers and geothermal energy plants, substantially reshapes the operation of the DHN and the loading patterns of the EDN. The operation of the DHN shifts from a more demand-responsive to a market-driven network, with a large reliance on the electricity market signals. This flexibility and responsiveness is largely driven by strategically placed thermal energy storage, especially near electrified production units. Moreover, the electrification of heat supply vastly reduces the reliance on gas and CHP units, resulting in geothermal energy, industrial waste heat and waste incineration becoming the key heat supply technologies. However, it also significantly increases the loading levels of key distribution network components, particularly on medium voltage transformers and lines, leading to critical network stress under future demand scenarios. Conversely, in future scenarios in times of high distributed energy generation, the addition of power-to-heat sources reduce the loading levels of the critical EDN components. It was identified that in times of high distributed energy generation, which results in net negative demand, the power-to-heat sources can consume power locally, lowering the amount of electrical power that needs to be transferred to the HV network, consequently reducing line and transformer loading. The reinforcement of physical assets and coordinated planning efforts between DHN and EDN operators are identified as key factors in mitigating these risks effectively.

Overall, this study provides a detailed description and analysis of the development of the integrated South-Holland heat and electricity model. In addition, the models are applied to perform multiple experiments in the case study, which allows to gain practical insights regarding the effect of large-scale electrification of the South-Holland DHN on the heat network itself and the EDN. The need for spatial-temporal coordination between heat
and electricity network operators in the operational and network planning of integrated energy systems is highlighted. The proposed methodology serves as a practical tool for decision makers and policymakers seeking to balance the decarbonisation goals of the DHN with the EDN reliability.

This thesis presents the hardware development of the Qbead, an educational tool designed to make knowledge about quantum computing more accessible through a tangible representation of a qubit using a spherical LED display. The Qbead simulates the Bloch sphere, enabling users to visualize quantum states and gate operations in an interactive, physical format. The project focused on redesigning the Qbead’s hardware to address limitations in the previous version, including insufficient LED density, fragile PCB structure, and complex assembly. Key improvements include a newly designed flexible PCB with 107 LEDs arranged for more homogeneous coverage, a custom microcontroller shield integrating a 9-axis IMU and reducing soldering complexity, and an upgraded 3D-printed casing that improves structural integrity and simplifies assembly. These enhancements were validated through prototyping and testing, showing improved usability.

This thesis explores the development of the software framework for the Qbead. A physical representation of a quantum bit (qubit) designed to be held in the hand. Shaped as a sphere, the Qbead visualises the Bloch sphere from quantum mechanics, with internal LEDs that illuminate to display the qubit’s state. The main goal of the Qbead is to provide students with a more intuitive and accessible way to learn about quantum computing.

While the concept shows promise, the existing software framework lacks the necessary features to function as an effective educational tool. This project focuses on further developing the codebase to create a solid foundation for future use. By expanding the software and implementing quantum-related experiments, the Qbead can better support hands-on education in quantum mechanics.

The new classes are added to create a better framework for other functions. The X, Y, Z, and Hadamard single-qubit gates are implemented. 3 ways to detect input, rotating, shaking, and tapping have been added.
Some experiments are developed to show off the single-qubit gate functions and decoherence of the state.

This study investigates the integration of Vehicle-to-Grid (V2G) technology with Electric Car Sharing Systems (ECSS) to enhance their profitability while implementing active peak reduction strategies. Focusing on a station-based ECSS with a fleet of 24 electric vehicles (EVs) across five stations, the research develops a mathematical model to maximize system profits by optimizing driving, relocation, charging, and discharging activities enabled by V2G functionality.

The analysis encompasses scenarios with and without V2G under varying electricity pricing schemes - uniform time-varying and location-dependent time-varying - and seasonal conditions, including summer and winter. Results indicate that V2G significantly increases profits by selling energy back to the grid during periods of low driving demand and high electricity prices, especially in cases of location-specific price variations. Active peak reduction measures effectively lower peak load demand with minimal impact on profitability. However, the inclusion of V2G introduces complexities, such as higher vehicle relocation costs and increased battery cycling, necessitating advanced management strategies.

The findings emphasize the critical role of dynamic electricity pricing and regulatory incentives in maximizing V2G benefits, highlighting the potential for ECSS to support grid stability while reducing peak load demand. Future research should address real-world challenges, including user demand variability, vehicle availability, and battery degradation, to refine the model’s practical applicability. By combining car-sharing with V2G, this study contributes to sustainable urban mobility and renewable energy integration, offering a promising direction for innovation in transportation and energy systems.

Since 2007, the impact of aviation industry emissions on climate change has garnered significant scientific attention. Electric aircraft (EA) are emerging as a promising solution to mitigate these effects. However, the design of battery packs capable of withstanding particular obstacles encountered by EA remains a challenge. During flight, critical challenges include meeting flight energy demands with batteries that have a lower energy density compared to conventional fuel aircraft, managing thermal conditions to ensure optimal battery performance, and reducing the weight of the battery system without compromising functionality. The integration of battery thermal management systems (BTMS) to maintain battery efficiency further increases the energy requirements and weight of the battery system. This paper aims to optimize mass energy density and Battery Thermal Management System ( BTMS ) energy consumption under the condition of meeting the energy, power and temperature requirements of large-scale battery packs for regional All-Electric Aircraft (AEA).
This thesis presents the design of an efficient and lightweight battery pack and its BTMS for pure electric aircraft. Based on a predefined flight cycle, the size of the battery required to meet the energy demands of the electric aircraft is calculated. Using experimental data on battery charging and discharging under varying temperatures and C-rates, an equivalent circuit model (ECM) of the battery cell is established. This ECM predicts the electrical and thermal behavior of the battery during flight. Subsequently, the material selection, specifications, dimensions, and structure of the battery module and BTMS are designed. With a focus on maintaining cell temperature and minimizing BTMS energy consumption, simulations of the packaged battery module are conducted. These simulations are used to explore and optimize various parameters. Finally, the modeling and simulation of the complete battery pack are performed. The simulation results demonstrate that the design effectively meets the operational requirements of pure electric aircraft in the targeted use scenario.

Renewable energy sources, such as thin-film silicon solar cells, show a lot of potential as the technology promises low production temperatures, low cost and low material usage. Other benefits are the flexible and very lightweight modules that can be fabricated, which enable a wide variety of applications. Other benefits include the low-temperature coefficient and low toxicity of the materials used to create thin-film silicon solar cells. The downside of using thin-film silicon modules is the relatively low power conversion efficiency inherent to the amorphous and nanocrystalline silicon. Another downside of amorphous silicon solar cells is their significant initial degradation, known as the Staebler-Wronski effect. This initial degradation will stabilize after time but does limit the ultimate conversion efficiency, especially for single-junction devices.
Hydrogenated amorphous silicon (a-Si:H) and nano-crystalline silicon (nc-Si:H) solar cells can be added in series to form a tandem device, thus increasing the efficiency of thin-film silicon solar cells. Although the current will be limited for 2-terminal tandem devices, a significant increase in open circuit voltage can be achieved resulting in higher efficiencies. To achieve highly efficient thin-film silicon solar cells a combination of good optical, electrical and material properties need to be combined. Extensive research has been done to achieve such high-efficiency devices focussed on the silicon deposition conditions, glass texturing for effective light scattering and light incoupling through anti-reflection coatings. Further research is focused on Transparent Conductive Oxides (TCO) improvements and the creation of triple or quadruple junctions.
Firstly, this thesis will focus on a literature study on amorphous silicon with a high-energy bandgap, deposition conditions in PECVD chambers and an i-SiOx buffer layer. A top cell of amorphous silicon with a high-energy bandgap can improve the conversion efficiency of a-Si:H/nc-Si:H solar cells by increasing its overall V oc. The amorphous silicon is processed at high pressure (3-9mbar) and high power densities (150-400mW /cm2) in a VHF-PECVD chamber at 40.68M Hz. To improve the poor blue response of these solar cells, a buffer layer of i-SiOx is explored as such a buffer layer has proven itself under normal deposition power densities (28mW /cm2) and pressure (0.7mbar).The i-SiOx did not prove to be effective in improving the blue response. A narrow range of deposition conditions around 5mbar and 25W is found to give high-bandgap energy solar cells with a good blue response.
Secondly, literature findings on a bilayer TCO configuration of IOH (Hydrogenated Indium Oxide) and i-ZnO (intrinsic Zinc-Oxide) to improve nc-Si:H single junction solar cells are provided. Prior studies on the use of a back reflector made out of different ZnO(Zinc-Oxides) are presented. Findings in literature on micro and nano-textured glass are presented and a comparison is made in an experiment to justify the use of a specific texture. Further experiments are carried out to measure the effect of implementing the bilayer TCO and an i-ZnO back reflector and an experiment on the performance and reproducibility of a-Si on MST (modulated surface textured) glass substrates is performed. ITO textured glass is chosen as the best performing substrate and a thick 1μ i-ZnO layer as part of a bilayer TCO is shown to be most effective at light scattering. The i-ZnO as part of a bilayer TCO can also significantly improve the spectral response of a-Si:H solar cell on MST textured glass. Furthermore, the i-ZnO as a back reflector is shown to be more effective when its thickness is increased.
Thirdly, a study is performed on the functioning of the a-Si:H/nc-Si:H tandem cells with respect to the thickness of the p-layer in the tunnel recombination junction (TRJ). An experiment is carried out to improve the reproducibility of a-Si:H/nc-Si:H solar cells by increasing the hickness of p-layer in the TRJ.
The conclusion is made that the glass texturing is more influential than the thickness of the p-layer in this experiment. Further investigation of the p-layer at the front interface of the device is done by an experiment on both MST and Asahi substrates. It is shown that thicker front players do not improve the reproducibility of tandem solar cells, but a trend of more parasitic absorption is seen. Finally, a study on micro and nano-textured glass for a-Si:H/nc-Si:H solar cells is shown. The chosen ITO substrate is finally chosen to demonstrate the progress of ongoing research on the performance of a-Si:H/nc-Si:H solar cells. The bilayer TCO vs a single layer TCO is used in combination with and without a SiNx ARC.
The electrical performance of the solar cells deposited in the final experiment is likely limited by poor IOH depositions and a large contribution of parasitic absorption is shown for the samples with the SiNx ARC. Either interaction of SiNx with the IOH or a poor IOH deposition are the most likely causes. Good 1-R curves are obtained for the solar cells on ITO textured glass substrates, especially the sample with the bilayer TCO and SiNx ARC.

Climate change is real. Energy transition plays a crucial role in addressing climate change where solar fuels have emerged as a critical player in reducing the dependence on fossil fuels in industries that cannot transition into renewable electricity as an energy source such as aviation, industrial feedstocks etc. Green methanol is a promising solar fuel if it is sourced via carbon capture technologies. This thesis aims to build and use a model of an integrated methanol synthesis microplant as a tool to predict methanol production and the performance of the microplant under multiple system architectures at Zero Emission Fuels B.V (ZEF) who are developing a solar powered green methanol synthesis plant. The research commenced with data preprocessing which utilised historical weather data from the C3S database. Subsequently, individual subsystem models were developed such as solar photovoltaic (PV) modules, direct air capture (DAC), fluid machinery (FM), alkaline electrolysis cell (AEC), methanol synthesis (MS), distillation (DS), buffer tanks, and battery system. To ensure the microplant's functionality, a sophisticated control algorithm was devised, operating on two distinct levels: battery management and power distribution. Moreover, diverse microplant architectures were designed, to address unique operational scenarios and environmental conditions. The investigation further explored the influence of temporal granularity, and component sizing on microplant behavior. Ultimately, this thesis establishes the feasibility of the ZEF microplant, offering valuable insights for practical implementation across multiple locations. Consequently, it underscores the potential of the ZEF microplant as a promising solution in the transition towards sustainable energy alternatives.

Emissions caused by regular vehicles with fossil fuels are problematic for the environment. The integration of electric vehicles in public transportation can potentially cause zero emissions. This paper will focus on the implementation of electric buses together with inductive chargers at bus stops. These chargers will charge the bus battery while passengers enter or leave the bus. This is also known as opportunity charging. Opportunity charging could result in the easier implementation of electric buses within public transportation since it solves the range problem that electric vehicles have. The first parts of this paper will provide a discussion about the powertrain model made in Mat- lab/Simulink. The powertrain model input is the driving cycles from the Arnhem Trolleybus data. The outputs are the energy consumption during the driving cycle and the state of charge of the bus battery. The opportunity charger will then be added to the model to analyze the effects of opportunity charging on the bus. The implementation of opportunity charging increases the operational range of the electric bus, while also lowering the energy consumption. The chargers will operate at a high power rating which spans from 100 kW to 200 kW. These power ratings could cause congestion of the grid. This is why the feasibility of PV systems at bus stops is analyzed using a PV model. A PV system is insufficient to power the chargers on its own. The PV system can still provide a significant percentage of the charger power demand.

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.

In this thesis two new modulation methods are proposed for a wide output voltage range dualactive bridge (DAB) converter for bidirectional EV charging application. The objective of theproposed modulation method is to maximize the number of ZVS events over the operating range,while maintaining low current stress. The first modulation method achieves this with fixed aswitching frequency, while the second achieves full ZVS operation using a variable switchingfrequency combined with alternative charging profiles. The design of the modulation method isdone through an analysis of the operating modes and the ZVS behaviour of the DAB converter.To verify the improvements to the ZVS behaviour of the proposed modulation method, the modulation method is implemented in a simulation and on an 11 kW prototype with an input voltagerange of 640 to 840 V, and an output voltage range from 250 to 1000 V, to ensure compatibilitywith various types of EV’s. A control system and a transient mitigation method are designedto facilitate the experimental verification. The proposed modulation method is compared to apeak current optimization for the DAB converter found in the literature. Measurements doneon the 11 kW prototype confirm that the improvements in ZVS are achieved. These improvements in ZVS of the proposed modulation method also result in increased efficiency comparedto the peak current optimization, especially in the low-power operating regions. The full powerefficiency over the entire voltage range of the peak current optimization, the proposed fixedfrequency, and the proposed variable frequency modulation are 97.895%, 97.879% and 97.964% respectively.

Global electricity usage has been increasing exponentially over the last 40 years and with the current pace of population and economic growth, the same trend will continue in the coming years. However, the current electricity generation is predominantly fossil fuels based, which makes the overall process unsustainable and polluting, and is contributing directly to the menace of global warming. The need of the hour is to transition to renewable and sustainable sources of electricity generation such as solar, wind etc.

However, the major bottleneck in the large-scale implementation of RESs is the intermittent availability and their integration into existing AC grids as the RESs are predominantly DC sources. In order to tackle the issue of intermittency various energy storage solutions are being developed. Further, as a solution to the issue of integrating RESs into the current electricity distribution system, DC distribution grids are being developed.

The DC distribution architecture is of two types, Unipolar and Bipolar distribution systems characterized by the number of wires used for power transmission; 2 wires for unipolar and 3 wires for Bipolar. Out of the two, Bipolar systems have inherent advantages of flexibility, stability and efficiency over unipolar systems.

Current thesis focuses on series connected switch configuration of voltage balancing converter for bipolar DC power distribution systems.

For this thesis, various topologies of voltage balancers for bipolar dc distribution systems were studied and a buck boost-based series switch-connected voltage balancer topology was chosen for the final design. For this topology, using MATLAB the parameterization and optimization of magnetic components of the converter were performed. The optimized configuration was then modeled and simulated using LTSpice.

Post this, a comparison between different methods adopted to account for the unbalanced voltage sharing across the series-connected switch configuration of the balancing converter owing to the non-linearities present in the circuit was done. Based on this study, the most prominent of the methods is then integrated to the LTSpice model.

Electric vehicles (EVs) equipped with vehicle-integrated photovoltaics (VIPV) and EVs with vehicle-to-grid (V2G) technology can support in overcoming power grid challenges emerging from the energy transition. Despite the widespread benefits that VIPV and V2G have to offer, their potential impact on battery life governs their economic viability. Current studies on the impact of VIPV and V2G on battery life are often simplistic, use unrealistic battery data, and rarely investigate methods to reduce battery ageing. To fill this research gap, this study combines validated models to determine the impact of VIPV and V2G on EV battery life and investigates methods to reduce battery ageing.

First, an EV battery data generation model was developed to simulate EV load profiles with and without VIPV and V2G. Afterwards, a one-year mobility and charging profile was constructed based on EV driving data in the Netherlands and Germany. Subsequently, driving cycles were simulated using Lightyear’s Vehicle Performance Model (VPM) to generate realistic per-second EV battery data. Following this, VIPV power generation profiles for the Netherlands and Spain were modelled using Lightyear’s SolarSimulator tool. Thereafter, two load profiles of V2G services in the Netherlands were modelled, namely day-ahead electricity trading and automatic frequency restoration reserve (aFRR), both with a battery capacity retention limit during V2G of 50% state of charge (SoC) and 20% SoC. The VIPV and V2G load profiles were merged with EV battery data to generate eight EV battery datasets. Finally, the EV battery datasets were implemented in a semi-empirical NMC-based ageing model (NMC-AM) and a semi-empirical LFP-based ageing model (LFP-AM) to determine the impact of VIPV and V2G on battery life.

Results from the EV battery data generation model show that gradual VIPV charging can reduce the annual grid charging frequency by 23% in the Netherlands and 44% in Spain. Reduced grid charging frequency due to VIPV caused the battery to range at lower SoC, which is beneficial for battery calendar life. Consequently, NMC-AM suggests that VIPV could extend battery life by 6 months, while LFP-AM suggests a battery life extension of 2 months. However, additional irregularity in the load profile due to gradual VIPV charging is likely to have caused the ageing models to overestimate cycling ageing. Furthermore, the ageing models suggest that additional cycling due to V2G, with the aim of maximising profits for the EV owner, could shorten battery life by 7.8 to 12.5 years for NMC and by 1.2 to 3.9 years for LFP. The results of the ageing models indicate that LFP batteries are more resistant to additional cycling than NMC, which is in line with literature.

Additionally, simulated scenarios in which the SoC was kept at 50% or 100% for one month per year, showed that SoC regulation could extend battery life by up to 2 years, allowing for 38,000 km of additional driving range before the battery reaches its end of life (EoL). Furthermore, results suggest that VIPV could lower battery temperature by 10 °C within one sun hour and can keep the battery cool when parked in the sun, by 23 °C in the Netherlands and 35 °C in Spain. Ageing simulations in which VIPV was used to cool the average annual battery temperature by 5°C, suggest that VIPV can extend battery life by up to 4.6 years, allowing for 88,000 km of additional driving range before the battery reaches its EoL. SoC regulation can be performed by delayed VIPV charging, delayed grid charging, or V2G. Battery temperature regulation can be performed using VIPV or grid power. Taking electricity cost into account, grid-powered battery temperature regulation could prove to be a cost-effective method to extend battery life, especially for EVs experiencing extreme temperatures.

Furthermore, as semi-empirical ageing models often lack clarity regarding their implementation, are usually not based on ageing tests with irregular load profiles, do not consider path dependency, are based on accelerated ageing tests under limited operating conditions and on a particular battery cell chemistry and size, applying these ageing models on irregular load profiles or other cells may lead to ageing estimation errors. Consequently, to determine how VIPV impacts battery cycle life, it is recommended to conduct battery ageing tests under identical operating conditions, with and without VIPV. Further research on the impact of VIPV on battery life would help develop strategies that optimally balance VIPV power used for battery charging and for battery temperature regulation.

Concluding, this research shows promising initial findings on methods to reduce battery ageing using VIPV and V2G, which could further improve their business case, accelerating the transition to sustainable mobility.

Vopak has the vision to become climate neutral by 2050 (Scope 1 and 2 emissions). Currently, over 99% of its CO2 emissions originate from storage terminal activities. Action must be taken to reduce these emissions by converting the current (fossil fuel-based) generation of electricity to sustainable energy.

This study aims to research how we can develop a methodology to evaluate the cost-effectiveness of an autonomous solar and storage system to electrify Vopak’s storage terminals? The objective of the method is to develop a system that is clean, reliable, autonomous, and payable (cheap). The selected autonomous system comprises a photovoltaic (PV) system, a battery energy storage system (BESS) and a hybrid inverter to satisfy the energy load of the storage terminal.

The developed method is a techno-economic model using three interlinked components. First, a PV model uses meteorological data and specific technical characteristics to simulate different PV systems. Second, based on the cost of different components of the PV system and BESS, a grid-search system selection method is used to determine the lowest-cost sizing of an autonomous PV and battery
system. Third, the sizing of the system is used to calculate the levelized cost of solar plus storage (LCOSS).

The method is evaluated for three selected storage terminals located in different climates. The lowest cost developed system for Vopak Fujairah Horizon terminal (desert climate), which has a LCOSS of 0.33 [$/kWh]. For Vopak Terminal Laurenshaven (maritime climate), a LCOSS of 0.96 [$/kWh] is calculated. Vopak Panama (tropical climate) has a designed system with a LCOSS of 0.53 [$/kWh]. The calculated LCOSS shows that these autonomous systems are not cost-effective, as they are 3 to 14 times more expensive than average energy prices from the grid for the storage terminal locations. A sensitivity analysis of the system costs and the weighted average cost of capital shows that a 50% decrease in battery costs results in a 38% decrease in the LCOSS. Furthermore, a decrease of 2% of the WACC has the same effect as a total system cost reduction of 10%–15%. Ultimately, enabling the system to
use its dumped energy by selling it to the grid shows the most significant reduction in the LCOSS.

This study clarifies that the cost-effectiveness of an autonomous PV and battery system strongly depends on the climate and seasonal variation of the location as it affects the energy yield of the PV-generating technology and the sizing of the system. Furthermore, the battery system costs are currently two to three times more expensive than a PV system; therefore, to size the lowest-cost system, the sizing strategy rather increases the (cheaper) PV system size to satisfy the load than install an additional battery. This results in oversized PV systems generating a large amount of unused energy. A solution is to enable the system to sell its unused electricity to the grid. An alternative solution would be to add a secondary “clean” energy source, such as a hydrogen generator, to combat these oversized systems and thus reduce the lifetime system costs.

In this thesis, a simulated annealing algorithm is implemented to optimize the efficiency of a tandem solar cell. The efficiency of a tandem solar cell is approximated by the current of the tandem solar cell. This current is determined by the simulation program GenPro4. Firstly, the general concepts of simulated annealing is described. After understanding these concepts, a simulated annealing algorithm is implemented for our specific problem. This algorithm includes the handling of discrete variables which describe the structure of the solar cell. The results contain multiple variants of the newly implemented simulated annealing algorithm, which differ in the used temperature schedule. Finally, a conclusion is made that a temperature schedule with a slower convergence gives the best results. However, one should consider a slightly faster convergence whenever there is a need to reduce the computational time. Moreover, one should write their own implementation of a simulated annealing algorithm when dealing with discrete variables, thus not use the provided function of MATLAB.

In a future energy system, chemical energy carriers that can easily be stored, like hydrogen, are of vital importance. One possible way of producing carbonneutral hydrogen is by direct solar to hydrogen conversion in a photoelectrochemical cell (PEC). Silicon based multijunction solar cells are a possible candidate for the photovoltaic stack of these PEC devices. To make high efficiency PEC devices, the photovoltaic stack has to be optimised, especially with respect to reaching high current densities in the middle (ncSi) cell. In this work it was attempted to increase the current density of a triple junction device based on cSi/ncSi/aSi absorber layers by varying the ncSi absorber thicknesses and implementing various intermediate reflecting layers (IRLs) between the middle and bottom cell. These layers were based on silicon oxide, transparent conducting oxides (TCOs) and thin silver films. For each method it was attempted to give a quantitative comparison of how much the electrical performance is affected per unit of current gained in the middle cell. Both increasing the ncSi absorber thickness and the silicon oxide reflector thickness were found to be feasible methods of increasing the middle cell current density. The ncSi absorber thickness leads to an initial rapid current gain, of about 2.6mA/cm2 between 2.5 and 3.75 μm, reducing to just 0.8mA/cm2 between 3.75 and 5 μm. The electrical performance cost between 2.5 and 3.75 μm was calculated as a 2% reduction in 푉 oc*퐹퐹 product per mA/cm2 current gain. This cost increased to about 5% per mA/cm2 between 3.75 and 5 μm. Increasing the absorber thickness beyond 5 μm is not considered feasible due to reducing current gains and mounting electrical performance losses. Increasing the silicon oxide thickness can result in a current gain of about 1mA/cm2. This comes at an electrical loss of 3% 푉 oc*퐹퐹 product per mA/cm2. TCO based IRLs were found to quickly result in shunting, and in the case of indium doped tin oxide (ITO) based IRLs also damage to the surrounding cell structure resulting in poorly performing cells. Aluminium doped zinc oxide (AZO) based reflectors with proper electrical isolation from the edges gave only slightly reduced electrical performance, but failed to lead to a current gain in the middle cell. Thin silver films were found to quickly rearrange into nanoparticles, effectively forming a plasmonic IRL. This IRL however suffered from high parasitic absorption, and as a result also did not lead to a current gain. A very thin silver film was however shown to slightly improve the electrical performance, at the cost of bottom cell current density. Finally, a device was fabricated with both a thick ncSi absorber as well as a silicon oxide IRL. The resulting device achieved a current density of 9.5mA/cm2, a 푉 oc of 1.947V and a FF of 0.789, giving an efficiency of 14.6%. To the knowledge of the author this is the highest efficiency reported for this device configuration to date. Furthermore, attempts were made to incorporate these stacks into PEC, by fabricating an microstructured anode, cathode and ionconducting pores, to form a porous membrane PEC (PMP). The cathode and anode were successfully demonstrated, but the pore etching is yet to be optimised.

Virtual Power Plants can aggregate and dispatch distributed energy sources (DER) to gain revenue in the Day-Ahead market, however as a Balancing Responsible Party they can risk imbalance cost due to deviations between the Day-Ahead forecast and actual production of their renewable energy portfolio. This study analyses the ability of industrial processes to minimize these imbalances by flexibly adjusting the energy consumption, which is also known as industrial demand response. Firstly, the advantages and disadvantages of major industries to provide demand response in a short-term redispatch scheme were identified by means of a literature survey. Secondly, the capability of the chlor-alkali and hydrogen production industry to minimize imbalances in a Virtual Power Plant was analysed. A simulation setup was developed in Python of a Virtual Power Plant with photo-voltaics (300 MW), onshore wind (300 MW), a chlor-alkali (203.5 MW) and hydrogen plant (193.4 MW) and a controller based on Model Predictive Control. The MPC integrated industrial process dynamics using data-driven Hammerstein-Wiener models which enabled rescheduling of load consumption without violating process constraints. The results show that industrial demand response provided by the chlor-alkali and hydrogen plant can minimize imbalances significantly between -89% to -99%. Furthermore, a sensitivity analysis revealed the effect of important plant and controller parameters on the imbalance minimization which notably indicated that the storage capacity of hydrogen/chlorine and high utilization rate (>95%) of the industrial plants can be a major limiting factor for minimization of imbalances. The findings of this study are expected to contribute to the development of renewable energy based Virtual Power Plants and the wider participation of industrial processes in distributed energy systems.

Concentrator Photovoltaics (CPV) employs optical elements such as mirrors to focus solar flux to a small target area with a photovoltaic (PV) receiver. CPV system design is hindered by the fact that there is no standardised workhorse model to accurately evaluate CPV topologies. The spectral irradiance standards - the backbone of PV system analysis - could be used, but lose in validity the higher the concentration as the Sun is not a point source. The sunshape, a different model widely used in Concentrated Solar Power (CSP), considers the Sun as an extended source but does not consider spectral information. It follows that CPV system analysis requires a spectral radiance model of the Sun that contains both spectral and directional information. In this thesis, a model from the astronomical literature is combined with the spectral irradiance standards to establish the spectral sunshape, a spectral radiance model of the Sun. The spectral sunshape is proposed as a workhorse model of the Sun for CPV system analysis.

In dit project is gewerkt aan een manier om de reflectie van het licht op de textuur van een zonnecel te berekenen. Deze reflectie is berekenend voor de verschillende hoeken van inval en uitval en omgezet in een reflectie matrix. In dit
project is verder gewerkt aan een al bestaand wiskundig model. Dat model was
in staat het door de verstrooiing ontstaande verre veld te berekenen. Dit model maakt gebruik van de methode van momenten, en past deze toe op eerder
ontwikkelde integraal vergelijkingen , die volgen uit de wetten van Maxwel.
Tijdens dit project is dit model aangepast zodat het ook bruikbaar werd voor
het door ons gemodelleerde substraat, van het Asahi-U type. Ook is in dit project gewerkt aan een manier om de bekende data van het Asahi-U substraat om
te zetten naar een wiskundig model .Dit is gedaan door het Asahi-U substraat
om te zetten naar een graaf van knopen en takken, met behulp van het programma GMSH. Vervolgens is gewerkt aan een manier om de berekende data
van het verre veld om te verwerken tot de reflectie matrices. Dit is gedaan met
behulp van een numerieke methode om integralen uit te werken. Tenslotte is de
reflectie matrices opgesteld, waaruit de reflectie van het licht op het substraat
kan worden afgelezen. Deze opgestelde matrix is anders dan de verwachting
niet symmetrisch. De waardes verschillen ook van de waardes die gevonden
zijn met behulp van een empirische meting.

Multijunction devices based on thin film silicon are useful for a range of applications due to their low costs, better performance at higher temperatures, potential for flexibility, and light weight. One particularly interesting application of such devices is in solar-to-fuel conversion. In light of this, the goal of this thesis was to suggest ways to better design multijunction devices based on thin film silicon. Three main research objectives were identified.
The first objective was the development of a high VOC top junction. Cells based on a-Si and a-SiOX were optimized by varying gas flows during the deposition of the intrinsic absorber layer. A maximum VOC of around 890 mV was obtained from cells based on both absorbers. Based on these results, it was possible to identify unique advantages of using either a-Si or a-SiOX as the top junction. For the second research objective, solar cells based on a-SiGe were studied. The impact of varying the bandgap profile in a-SiGe absorbers on the device performance was investigated with a set of experiments. Subsequently, a set of semi-empirical equations were motivated and fitted to the experimental data. These relations could approximately show how bandgap profiling affects device performance in a more general way. The presented approach may be used to expedite the design of a-SiGe based cells for use in different types of multijunction devices. Finally, a systematic optimization of tunnel recombination junctions (TRJ) was conducted. Experiments were done to study the impact of using different TRJs in two types of tandem devices: a-Si/a-SiGe and a-SiGe/nc-Si. Different features of the TRJ were varied separately: p-doped layer(s) used, thicknesses of the p-doped layer(s), and the n-doped layer(s) used. The best performing p-doped layers was identified among the studied combinations. For the n-layer(s), the experimental data suggested the different roles played by n-a-Si, n-nc-SiOX, and n-nc-Si in the TRJ. This observation could be used to design an optimized combination of n-layers for the TRJ. Collectively, the work done as part of each research objective aims to contribute to the better design of multijunction devices based on thin film silicon alloys.