In this thesis, "Design & Reliability Assessment of AEA Propulsion Grid", the development of a reliable and efficient propulsion grid for All-Electric Aircraft (AEA) is investigated to reduce aviation emissions. Our primary objective is to design a lightweight Power Management and Distribution (PMAD) system that meets stringent reliability standards. By analyzing materials, heat transfer, and grid design, we propose optimized grid topologies that balance weight and reliability. The findings emphasize the importance of redundancy and suggest further research into subcomponent failure rates, control aspects, and real-world testing to enhance system reliability and performance. This thesis provides valuable insights into the future of electric aviation, highlighting the necessity for continued investigation and practical application to ensure ultra-reliable electric propulsion systems and make zero-emission flight a reality.

As the need for both clean electricity and reduction of carbon emission rises, all-electric airplanes have the potential to reshape the field of aviational transport to fit this need. The development of such airplanes necessitates the advancement of highly reliable and efficient electrical systems, among which circuit breakers play a critical role. This paper investigates design considerations and challenges associated with circuit breakers for all-electric aircraft. The study explores possible circuit topologies that are capable to interrupt a 3 kV and 500 A power flow when a fault in the system causes a short circuit. Through simulations and experimental validations, the paper aims to propose an optimised circuit breaker design that enables reliable electric power systems in all-electric aircraft.

This Master's Thesis is conducted in collaboration with Alewijnse, a leading maritime systems integrator in the Netherlands. The thesis aims to identify the optimal and cost-effective method of incorporating battery energy storage systems (BESS) into both new and existing DP-2 vessels, as well as DP-3 vessels. The objective is to determine the most efficient battery size and technology, establish the ideal time frame for return on investment, and design a power generation schedule that is ideal for the DP-2 cable laying vessel’s power system.

The primary objectives of this research are to optimize the battery system, ensure effective energy system operation, and establish a strong business case. Specifically, the study explores the feasibility of retrofitting a DP-2 vessel that operates in the North Sea and Taiwan with a battery system to create a hybrid system.

To determine the optimal sizing of the battery energy storage system, 12 different battery solutions from two European battery suppliers considering three different fuel price scenarios are analyzed. These solutions encompass a variety of battery technologies, such as High Power or High Energy Li-ion batteries or a combination of both.

The integration of BESS into vessels offers several operational benefits to operators, including the ability to operate diesel engines at higher or more efficient points of operation to maximize their performance. Battery systems can also act as ”virtual generators” during dynamic positioning (DP) mode for DP-2 vessels, reducing fuel consumption, lowering diesel engine ON-time, and decreasing maintenance costs.

However, hybridizing vessels involves more than just integrating an optimally sized battery system.The existing power management system (PMS) and energy management system (EMS) must also undergo upgrades to ensure effective operation. To address these challenges, the BOOSTER (Battery Optimization for Optimal Sizing and Throughput Energy Regulation) methodology is proposed, which incorporates the operation of an optimized management system based on fuel prices and the throughput energy cost of the battery system.

This master thesis explores the capacity of MIMO arrays for communication in the radiative near field through antenna design. This research applies an in-house MATLAB model based on free space Green’s function to calculate the channel matrix, revealing the potential increase of capacity through the use of incoherent arrays with directive antennas in the incoherent range without the need for interference cancellation.

The optimization of the equivalent aperture current and the design of lens antennas are the key points in realizing the ultimate goal of maximizing the capacity between antenna arrays. The accuracy of the channel matrix from the MATLAB model and the performance of the designed lens antennas are validated through full-wave simulation using CST. Furthermore, the internal reflections between the arrays are studied, offering solutions to mitigate the effects of the reflections for future array designs.

This work serves as a feasibility study, providing sufficient confidence in the application of communication systems in the radiative near field without the need for signal processing (e.g. interference cancellation, multi-path cancellation, etc.). Furthermore, the methodology in this thesis offers insights for future antenna designs for different applications. In summary, this study proposes and validates a potential solution for the design of next-generation communication systems.

Whereas in the past, Distribution Systems played a passive role in connecting customers to electricity, Distribution System Operators (DSOs) will have to take in the future a more active role in monitoring and regulating the network to deal with the new behaviors and dynamics of the system brought by the energy transition. State Estimation, a task traditionally reserved for Transmission System Operators (TSOs), is, therefore, a needed tool for DSOs to properly monitor the distribution grid in the future. However, the implementation of Distribution System State Estimation (DSSE) faces several challenges. The distribution system lacks observability to get satisfying estimation accuracy, the denser network increases the complexity of the estimation process, and the lack of labeled data makes training Machine Learning alternatives difficult. To tackle these issues, we propose the Deep Statistical Solver for Distribution System State Estimation (DSS2), a Deep Learning model based on the Graph Neural Network (GNN) architecture and the Physic-Informed Machine Learning (PIML) framework.

The DSS2 model is based on the Deep Statistical Solver (DSS) framework, which seamlessly models power systems into GNN using Hyper-Heterogeneous Multi Graphs (H2MG), and emphasizes semi-supervised learning by learning to optimize, using optimization problem as a loss function. This thesis extends the DSS framework to the DSSE problem, using the traditional State Estimation algorithm as an optimization problem to learn, and incorporating the power flow equations in the loss function. This model is trained through a semi-supervised approach to learn the physics of the problem and alleviate the need for labels and uses the Deep Learning tools to improve accuracy and robustness in the DSSE task.

Case studies on 14-bus, 70-bus, and 179-bus networks show promising results, with the model outperforming the traditional WLS algorithm while showing better robustness. The model also competed in performance against supervised models and showed to be more suitable for the semi-supervised learning approach than simpler GNN architectures.

Advancements in the field of Information and Communication Technologies (ICT) has enabled the possibility to utilize the flexibility offered by responsive assets in a better way by employing Demand Response (DR) schemes. This thesis analyzes the performance of one such DR scheme developed at TU Delft called Forecast mediated Market Based Control (F-MBC), which aims to coordinate such flexible assets by communicating "self-fulfilling forecasts" [1]. The main aim of the project is to investigate the applicability of this method in real-world settings. To do so, several simulation scenarios were formulated to understand how well F-MBC coordinates heterogeneous populations of uninterruptible time shiftable loads over an extended time horizon, both from the system perspective and devices' perspective. The thesis also proposes an approach to test the mechanism in a rolling horizon setup. First, the performance of F-MBC is examined under several combinations of deferrable loads having identical deadlines. Then, its ability to coordinate devices with dynamic load profiles under a complex realistic setting is investigated. Trade-offs adopted when simulating such a setup is also highlighted. Results indicate that while F-MBC achieves good overall performance when coordinating devices with uniform power consumption profiles, its performance in scheduling heterogeneous populations of devices with dynamic load profiles was quite variable. When devices that consume high power when they start was considered for coordination, F-MBC was able found to allocate the devices in such a manner that steered towards overall cost minimization. However, its performance if used to schedule devices which consume low power when it starts was found to be undesirable. Hence, several recommendations were provided to deduce better conclusions about the applicability of the mechanism in reality. References: [1]Hazem A. Abdelghany, Simon H. Tindemans, Mathijs M. de Weerdt, Han la Poutré, Distributed coordination of deferrable loads: A real-time market with self-fulfilling forecasts, Sustainable Energy, Grids and Networks, Volume 23, 2020, 100364, ISSN 2352-4677. http://www.sciencedirect.com/science/article/pii/S2352467720302952

Using the energy system is part of our daily routine but the complexity of power systems and its understanding have both been confined to the experts in the field. Furthermore, the advent of the Information and Communication Technology (ICT) and the Internet of Things (IoT), power system integration is becoming even more complex for the system planners and operators. Various clean energy technologies like solar power, massive offshore wind, Electric vehicle as well as the increasing dependency of the Prosumers to move towards a future decentralized and transactive energy market. There is hence a need to educate the general public about the important problems encountered during the energy transition as well as to provide a demystifying version of the existing power system to exhibit its complexity and its benefits of intelligent multi-energy systems.

Energy System Integration Development (ESID) kit could solve this issue.

This project concerns the design and development of a Middleware software system based IOT application, which runs on Raspberry PIs (RasPi), contribute to the layered bottom-top approach of the Illuminator - Energy System Integration Development Tool Kit and has the main goal to help in assisting the application layer to simulate energy system integration scenarios and will be prototyping simple proofs-of-concept for validation purpose. It’s realized as part of the master thesis curriculum of the author. On the completion of this project, there will be a generic middleware system that can be used by the end users/application layer to demonstrate energy system integration scenarios, which is scalable, reconfigurable, inter portable.

Illuminator - Energy System Integration Development Tool Kit aimed to become an open-source platform depicting energy integration problems, an education tool kit, and research to prototype control algorithms for counteracting the energy transition challenges. The general public and system integrators would benefit as well as the stakeholders as it can help them analyze the energy integration challenges in a user-centric fashion.vii

Although the idea of electric vehicles fell out of favour in the 1930s, it seems this phenomenon is now reversing and that many companies are willing to invest again on this technology. The advantages are clear: no emissions and the possibility to power vehicles by means of sustainable sources. On the other hand, a high number of simultaneously active charging stations would likely lead to severe problems in the electrical network, e.g. grid congestions and voltage issues. One of the main goals of this work is to estimate the impact that a higher EV penetration has on the power loading of the lines and transformers in a distribution grid. Once these effects are clear, the focus can move towards the investigation of possible strategies to limit it. Excluding an equipment reinforcement, the only possible way to keep a grid operating when the general working conditions approach the technical limits, is to improve the power management. In this regard, five control strategies were tested in different combinations. Among these, three were implemented on a single charging station level to control the charging operations of the single vehicles. These are the uncontrolled charging (the most commonly used strategy worldwide), the average power charging, where a constant low power is provided during the whole parking time, and the local optimisation charging, where a completely local optimisation analysis is carried out to calculate the cheapest operation possible. The other two strategies instead were implemented at central level, to curtail power in case of necessity. These are the Equal Curtailment Method, that prioritises an equal division of the curtailment among the chargers, and the Flexible Curtailment Method, that optimises the curtailment considering the flexibility of the charging stations. Several tests were run by means of simulations on real Dutch distribution grid models and they showed that simple charging strategies - such as the average power charging – can lead to both low charging prices and low loading percentages. It seemed hardly possible, though, to make the charging stations take greater advantage of the low prices at night, without causing overloading issues. However, this could be achieved if a curtailment scheme was also included by means of a central coordination unit. Therefore, it is clear that different levels of complexity may bring benefits to the network, but they may also present drawbacks. The purpose of this work is to shed some light on the different possibilities and to provide hints on how to choose the most appropriate strategy for each situation.

Multi-junction solar cells with Si alloys have true potential for high conversion efficiency, because of the spectrum splitting capability. For optimal spectral utilization, a multi-junction silicon based device needs a silicon alloy with a bandgap between that of nc-Si (1.1 eV) and a-Si (1.8 eV). a-SiGe:H has a tunable bandgap between 1.4-1.6 eV by varying the GeH4 flow rate in the layer. An investigation of deposition parameters on PECVD processed a-SiGe:H films showed that variation of the GeH4/SiH4 flow rate is the most influential deposition parameter to achieve bandgap tuning. It influences the optical-, electrical- and material properties due to the fact that it directly changes the GeH4 flow rate in the material. Subsequently, a n-i-p substrate single junction a-SiGe:H solar cell is fabricated. This is the reversed p-i-n superstrate a-SiGe:H solar cell, fabricated by the PVMD group. It has a Voc of 508 mV, a FF of 0.39, a Jsc of 9.9 mA/cm2 and a final efficiency of 2.9%. Due to the low performance, manipulation techniques were introduced. The different proposed shapes consist of bandgap grading in the absorber through GeH4 flow rate profiling. A study on buffer type and thickness, different profiling schemes, grading widths and total absorber thickness strongly improved the device performance. The overall champion single junction a-SiGe:H solar cell has a 3.2 nm n/i i-a-Si buffer combined with a 5 nm n/i i-a-SiGe:H buffer, a V-shape GeH4 peak flow rate of 2.4 sccm, a 134 nm n/i grading width, a 36 nm i/p grading width and a total absorber thickness of 170 nm. This cell generates a Voc of 735 mV, a FF of 0.64, a Jsc of 13.23 mA/cm2 and a final efficiency of 6.18%. This is a relative increase of 113.8% in efficiency. The single junction solar cell fabrication is followed by demonstration of a two-junction device. The overall champion tandem solar cell consists of a 200 nm a-Si:H top cell and a 170 nm a-SiGe:H bottom cell with a V-shape GeH4 peak flow rate of 5.3 sccm. This champion tandem solar cell generates a Voc of 1395 mV, a FF of 0.69, a current limiting Jsc of 8.34 mA/cm2 and a final efficiency of 7.99%. Finally, research proved that the change in top and bottom cell thickness, the maximum GeH4 flow rate and the U- and V-shape profiles are interesting manipulation techniques in a multi-junction device due to their flexibility to increase the current limiting Jsc and improve current matching.

This BSc Thesis is about the construction and control elements of the airplane group of the Solar Drone project. The project aims to improve the flight time of aerial vehicles, using solar energy. This document is delves into the possibility of applying solar cells to small model aircrafts. It outlines the challenges and solutions involved in building and controlling such a system. A ready-available airframe and fitting components will be used, in combination with a custom photo-voltaic and energy system, to create a prototype. The prototype takes the form of an unmanned aerial vehicle, making it capable of extended flights without requiring extensive monitoring. It will serve as a testing platform for the performance of the PV modifications done to the aircraft.

Included in this document are simulations for calculating optimal solar panel placement inside a transparent wing with opaque ribs, in addition to software and hardware modifications that were required to make the other systems work well in combination with the custom energy system.

The increasing demand for electricity and the need to decelerate the use of fossil fuels to prevent a dramatic climate change have urged the need for new sources of energy. Thus, electrical sustainable energy is an ever growing field. Investigations into performance improvements and extraction of maximum benefits from Renewable Energy Sources (RES) is the need of the hour. In particular, wind power contributes to a significant share of renewable electricity generation and has seen great leaps in terms of implemented technologies. The advancements in wind turbine technology have introduced converter based generation, thereby affecting the electrical grid's inertia and short circuit current contributions. These short circuit contributions have been of particular interest for protection engineers in the development of protection systems worldwide. TenneT, which is the TSO of the Netherlands, faces the challenge regarding the protection scheme implementation for their upcoming offshore wind farm connections involving Type 4 Wind Turbines (WT). The lower magnitudes of current flow, post fault and the presence of balanced currents irrespective of the type of fault are some of the major challenges. The system starting from the busbar (where WTs are connected) is owned by the system operator and the WT along with the cable connecting to the busbar, or the Point of Common Coupling (PCC) is an asset of the Wind Park Operator (WPO). Non-technical issues such as the ownership of components at the point of common coupling between the wind park operators and the system operators together along with the technical challenges described earlier necessitates the development of a standard protection scheme that provides satisfactory performance. Implementation of end-to-end connection protection system for the individual component protection is also challenging considering the challenges associated with the ownership of the assets. Therefore , it is necessary to analyse the performance of conventional protection systems (single unit operation). The performance of definite time overcurrent, directional overcurrent, under voltage and distance protection have been studied for faults on PCC and the infeed WPO strings. The study aims at finding the right choice of primary and back up protections that are independent of the type of short circuit currents available by the generation technologies. In addition, the research aims to develop a new busbar protection scheme that can detect and identify the fault location with the challenges explained before. Following the undesirable behaviour observed with overcurrent and directional overcurrent protection system the author then proposes two new schemes using conventional protection systems. The considerations regarding successful operation of under voltage protection and distance protection are further addressed. Finally, a new scheme involving fault generated travelling waves to detect fault on the network is extensively tested. All the protection systems are then compared to describe their merits and demerits to make a decision about the primary and backup protection implemented.

Most ocean-going ships are fitted with an impressed current cathodic protection (ICCP) system. The currents impressed by this system onto the seawater find their way to corroding parts of the ship’s hull, and prevent the hull from corroding. The electric field resulting from the currents around the ship is called the electric signature. This signature is a threat in seas with mines, as mines explode when they detect this signature. Therefore controlling the signature is important, especially to naval ships. In order to be able to control the signature the location and size of corrosion damage needs to be known. Today no method exists for corrosion damage estimation on a sailing ship. This study aims to develop a method for corrosion damage estimation using only measurements of an ICCP system. The research question is: To what accuracy and with what measurements can the damage distribution on a ship’s hull be reconstructed? The quality of the damage reconstruction is evaluated by how well the signature is estimated. First an analytical model is used to explore the theoretical limits of damage reconstruction. This shows damage reconstruction is limited by the number of measurement electrodes. Then damage reconstruction by numeric model inversion is attempted, but is shown to be unattainable. The proposed solution is damage reconstruction by repeatedly calculating for different damage configurations, comparing the calculated measurements to the true ones, and iterating until an optimum is found. This method works well on a ship geometry if 140 measurement sensors are used. In order to verify the damage reconstruction algorithm a scale model facility is developed. The produced field sensors show shifting offsets that are not explained, but good linearity with the electric field. Simulations and measurements with a calibration source show good similarity, but a factor of 1.6 difference that is not explained. Test with sacrificial anodes show large variations over time and a large dependency on the sailing speed. The results show that corrosion damage reconstruction using only on-ship measurements can be achieved. The resolution of damage reconstruction is limited by the number of measurement electrodes, at least one hundred are needed for the signature to be resolved. Current ships have between one and eight measurement electrodes; it is recommended future ships will have at least one hundred. These results furthermore indicate that time-dependent effects should be included in the physical model used for the simulations.

This report discusses one part of a project consisting of three parts. The goal of the project is to design a battery less sensor powered by RF energy fields present in an office environment. The sensor is able to measure the temperature and is able to communicate wirelessly using a low power communication protocol. In this project the use case of a building is explored. This thesis treats the RF energy harvesting part, which scavenges the RF power out of the ether and delivers it to the rectifier to convert and store the energy. First the spectrum has been analyzed to determine the most suitable frequency band. An antenna has been designed to harvest as much power at the chosen frequency. To make the power transfer from the antenna to the rectifier as efficient as possible, a matching circuit for matching the impedances is implemented. In this report, a Planar Inverted-F Antenna is designed to meet all the given requirements.

The physical integration of a battery system to the back of PV module provides solutions to the changing demands of the residential solar energy market. The PV-Battery Integrated Module (PBIM) concept is proposed and equips energy-users with a modular and user friendly solar system. With each PV panel equipped with its exclusive balance of system components, the PBIM aims to rival conventional solar home systems on an economic basis. With a potential to offer savings on the installation process and removing the need to customize every residential solar system the use of PBIM is a promising step towards the widespread implementation of solar systems.


This project contributes towards the PBIM design by exploring the effects of energy storage motivations and ambient conditions on the optimal PBIM energy storage capabilities and the subsequent impact on its performance as whole. To quantify these impacts realistic case studies are developed and test the PBIM's capabilities in Costa Rica and the Netherlands. The PBIM, for each location, was assessed for its application in a grid-tied system for peak shaving applications and its performance as a stand-alone solution.\\

As compared to conventional solar systems, the PBIM operates at higher temperatures, influencing the performance and lifetime of the incorporated components. This thesis commences by capturing the effects of elevated operating temperatures through the development of a PBIM model. The energy control strategy is devised to simulate the battery charging profiles for the identified applications. Location specific parameters are then implemented to asses the PBIM performance and the influence of different climates.

A sizing methodology is used to derive the appropriate battery capacity for each case study. A comparison is made between the dynamic characteristics of the optimally sized system for each of the locations, indicating the fulfillment of the respective system objectives, minimizing battery degradation and maximizing autarky. Furthermore, the technical and economic feasibility of the PBIM concept is assessed with respect to a conventional solar home system, leading to the conclusion that the PBIM, at this point in time, possesses technical characteristics comparable to that of a convectional PV system. The PBIM concept is still in the early stages of development and there are still many challenges that need to be overcome before its widespread usage.

Managing electrical distribution assets entails making the decision on how to proceed with an ageing asset. The three options that asset managers have are run to fail, perform maintenance or repairs and lastly to replace. This decision making process is becoming incrementally more important due to the threat of replacement waves. This a phenomenon that comes forth from the fact that a large portion of the assets were installed around the 1970's, the so called installation wave, combined with the fact that these assets have a life expectancy of 40 to 60 years. It is up to the asset managers to accurately asses the condition of these assets and prioritize investments due to budget restrictions. Asset management has been evolving from time based maintenance (TBM) to condition based maintenance (CBM) and risk based maintenance (RCM). To aid in the decision making process for the latter two methods, accurate condition assessment and failure probability methods are needed. At Stedin, one of the three largest network operators in The Netherlands, the asset managers require a better condition assessment method for transformers, as the one being used now lacks certain capabilities; trend analyses and proper prioritization is difficult and time consuming. Furthermore, there lies the question whether the condition of the transformer can be used to improve the failure or survival probability model. The assumption is that the condition indicators of an individual asset can be used to adjust the population based probability models, which are then comprehensive and more accurate. In this thesis, an improvement to the transformer condition assessment is implemented and the effect of the condition indicators on the survival probability of the transformer is studied. Several condition assessment methods were reviewed, with the chosen method being the so called health index (HI). The results from this method is accurately reflected in the transformers which are to be replaced by Stedin. However, it has become clear that using one single number for decision making is not recommended, as the subsystems that are in moderate or bad condition might be masked by those that aren't. This can be compared to the analogy that a chain is only as strong as its weakest link, and thus the condition of that link should not be masked by the condition of the rest. For the survival model, machine learning and classic statistical methods were reviewed. The chosen method was Cox's Proportional Hazard Model, which has the advantage of being applicable to situations in which the underlying probability distribution of the events is unknown. Due to missing failure data, the survival model was used to model the effect of the condition indicators on the probability of corrective maintenances. Further constraints in the data quality lead to the confidence bands of the model's parameters to be relatively large. However, the univariate models do prove the significance of the effect of these condition indicators. The conclusion is that there is a relationship between the condition and the observed failures, but that proper documentation of failures is necessary to increase the accuracy of the model.

Rise in distributed energy resources has prompted a shift in the way electricity market operators function. Traditionally, centralized optimization techniques are used by such operators to plan for economic dispatches of power tominimize the overall operational costs and increase system social welfare. Due to the dispersed nature of renewable energy sources as scattered nodes in a system, it can get difficult to accommodate them in a centralized optimization problem. Also, sharing of complete information for such nodes can create privacy issues. This motivates research in the field of distributed optimization techniques. This thesis aims to develop a distributed optimization algorithm for a DC distribution system which would take into account network congestion and line losses and ultimately provide a more precise optimal solution. Based on past research for distributed optimization approaches for AC systems, the Consensus and Innovations approach was used to model an algorithm and provide nodal optimization for a DC system with minimal data exchange. The developed model was implemented on various DC network topologies like meshed grids, single line networks, T Shaped networks, etc. and a converged output of system variables was accomplished. The results were also compared with a centralized optimization approach to check for deviations. The decision variables for the developed approach were found to be well within the deviation range of 2 percent. The algorithm managed to provide distributed optimization within a DC system while minimizing power generator operational costs and cost associated with network losses.