Decarbonisation and efforts to reduce living expenses are driving interest in multicarrier energy systems (MCES) that integrate electricity, heat and e-mobility. These integrated networks require sophisticated energy management strategies to address uncertainties in energy supply, demand, and weather conditions.

This thesis seeks to develop a reinforcement learning (RL)-based energy management system (EMS) for a multicarrier residential building at TU Delft's Green Village. The case study household integrates photovoltaic and solar thermal systems, an electric vehicle (EV), lithium-ion battery, heat pump, and thermal storage. Current management uses white-box model predictive control (MPC) which, while effective, demands significant computational resources. In addition, its implementation requires expertise in optimal control and physics-based modelling.

The developed RL-based EMS provides a computationally efficient alternative, leveraging data-driven methods to learn system dynamics. The RL approach was benchmarked against the existing Expert, a day-ahead MPC planner. Performance was evaluated in terms of operational safety, grid energy exchange costs, and satisfaction of EV state of charge (SoC) demands.

The RL agent achieved performance comparable to that of the Expert in managing the MCES, while improving accessibility for developers lacking control theory expertise. The RL agent displayed consistent and near-optimal performance, resulting in only a 4% increase in grid exchange costs while improving both EV charging compliance and safety constraint adherence.

A literature review of RL applications for residential EMS is presented alongside an investigation of advanced policy update algorithms, deep neural network architectures, temporal feature engineering, and reward shaping strategies to analyse their impact on EMS performance.

The implemented RL-based control solution has been shown to manage electrical and thermal subsystems while maintaining safety and minimising costs. The computational efficiency and reduced modelling requirements of an RL agent highlight its suitability for small-scale MCES applications, such as residential or office buildings, where MPC may not be practical.

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.

This thesis investigates the design, analysis and testing of medium-voltage planar transformers for modular Solid State Transformer applications, with a particular emphasis on insulation for medium-voltage level. The renewable energy and microgrid implementation in the generation and distribution segments of power grids is motivated by the global urgency of the energy transition, particularly in response to the challenges in the Netherlands related to the phase-out of natural gas and grid congestion. Central to this work is the development of modular Solid State Transformers (SSTs) tailored for microgrid applications which are one of key components in the transition to more sustainable energy, for which planar transformers in high-frequency operations have to be designed.

A thorough review of high-voltage planar transformer design is conducted, focusing on core and winding losses, parasitic elements, and the complexities of achieving sufficient insulation within compact designs. The thesis outlines the design of a high-frequency planar transformer optimized for modular SSTs, highlighting key aspects such as core selection, loss minimization, and insulation design. Simulations are performed to assess the impact of high-frequency effects on transformer performance, with particular attention to the optimization of winding and shield configurations for improved field distribution and reliable insulation.

Multiple critical aspects in the design of insulation are pointed out and the experimental work is dedicated to testing these aspects.The PCB-based insulation under high-voltage conditions, with a focus on partial discharges and breakdown voltage in scenarios involving parallel conductors within a PCB layer. The results demonstrate the robustness of PCB insulation while revealing challenges posed by surface discharges and the effects of external conditions such as oil and air. These findings provide critical insights into the dielectric performance of FR4 laminates, contributing to the enhancement of insulation system reliability in planar transformers.

The outcomes of this research offer valuable contributions to the design and optimization of high-voltage planar transformers, underscoring the importance of balancing compactness, efficiency, and reliability. These advancements are essential for the development of resilient and sustainable energy systems in the context of the global energy transition.

With the increasing requirements of the semiconductor industry, ASML lithographic machines, essential for chip manufacturing, are becoming more complex. Consequently, the mains distribution system, a crucial part of these machines, is increasingly vulnerable to short circuit (SC) faults due to the growing number of system components. SC assessment of this system in compliance with international standards is vital as they are utilized by companies worldwide.

This thesis provides a standardized assessment method for industrial mains distribution system that complies with international standards. The assessment method includes the determination of available SC current and overall short circuit current rating (SCCR) and is implemented as a Matlab tool. Additionally, this thesis explores ways to increase the SCCR of the system by improving protection and limiting current considering current-limiting alternating current circuit breakers and various direct current circuit breaker (DCCB) technologies, including fault current limiters. Finally, the assessment results are validated through the physical testing results of a branch circuit within the ASML mains distribution system.

For the delivery of Shore to Ship power, the 'status quo' of shore power delivered just from the grid results in the overcapacity of power installation, these resources need to be more optimally utilized.
This research investigates what configuration of electrical components to deliver shore power to vessels is the most cost-effective at the quay-side of Royal Roos.
This thesis ends with the answers to the research questions that guided the research, and thereby help explain under which conditions an implementation for shore power supply is more cost-effective than another

For the delivery of Shore to Ship power, the 'status quo' of shore power delivered just from the grid results in the overcapacity of power installation, these resources need to be more optimally utilized.
This research investigates what configuration of electrical components to deliver shore power to vessels is the most cost-effective at the quay-side of Royal Roos.
This thesis ends with the answers to the research questions that guided the research, and thereby help explain under which conditions an implementation for shore power supply is more cost-effective than another

The global shift towards sustainable energy sources, together with rapid technological advancements, has driven a significant increase in the demand for electric vehicles (EVs) over recent years. This surge in EV adoption highlights the critical need for robust supporting infrastructure, particularly in the deployment of efficient and accessible EV chargers. Gallium Nitride (GaN) is a wide bandgap semiconductor material that offers better performance characteristics compared to traditional silicon-based components in medium-power and high-frequency application. Its higher electron mobility, saturation electron velocity and breakdown electric field make GaN an ideal candidate for high-frequency power conversion applications in EV chargers. To explore the potential of GaN technology in EV charging applications, an 11kW GaN based isolated bidirectional multi-port EV charger with a two-stage architecture has been designed to interconnect bipolar DC grid and electric vehicles. The two stages of the charger consist of a three-level triple active bridge converter and a three-level interleaved buck converter. The TAB converter is an extension of conventional dual active bridge (DAB) converter, offering capability to direct power transmission among three ports. However, the addition of a third port introduces complexity in managing power flow. The TAB converter can operate under various modulation schemes, including three-level and five-level modulation. An analysis of the switching modes associated with each modulation scheme has been
erformed. In order or derive the soft switching range of the converter, the current expression
of series inductors of each port are derived based on generalized-harmonic approximation method and equivalent circuit models. A detailed analysis of the commutation process during critical switching transitions has been conducted, leading to the derivation of the soft
witching criteria for both three-level and five-level operations of the TAB converter. To validate the design and verify the soft switching range, simulations have been carried out. Moreover, the prototype of the 11 kW multi-port EV charger is designed based on calculation and simulation results. The prototype employs a top-side cooled GaN high-electron-mobility transistor (HEMT) to enhance thermal dissipation. Testing of the prototype indicates that the converter can transmit 1.2 kW from the primary to the secondary side at the rated voltage
of 700 V.

This report proposes a design of a 1-megawatt data center that utilizes hydrogen as the primary fuel for power and cooling. Currently, data centers rely on utility grids for their operation. The growing global efforts to achieve sustainability introduce intermittent renewable energy sources, such as solar and wind, into the power grid, which goes against the reliability principles of the data center industry. As computer technologies further permeate our everyday lives, their energy consumption and environmental impact become greater.

The feasibility study aims to investigate the potential of using hydrogen as a primary energy carrier in data center applications in terms of reliability, efficiency, electrical and hydrogen topology, infrastructure layout, and control strategies. A comprehensive review of commercially available and emerging hydrogen technologies related to storage, transport, electricity generation, and cooling was conducted. Based on this literature review, two designs for a hydrogen data center were developed. A modular approach to the design was proposed, where each module is self-contained and responsible for providing the servers with 1 megawatt of electrical power and cooling.

The first low-temperature design utilizes a hydrogen pipeline with pressure swing adsorption purification supplying hydrogen gas to a cogeneration system. This system combines a low-temperature Proton-Exchange Membrane fuel cell and a direct-fired hydrogen single-stage absorption refrigeration cycle into a single unit to deliver stable power and cooling to the servers. The findings indicate that the overall energy efficiency of this design configuration is high, and the technologies are mature enough to be used today. However, the study identified various technological limitations of purification systems that must be addressed with further research and development.
The second high-temperature design eliminates the need for a purification system, relying instead on high-temperature Proton-Exchange Membrane fuel cells coupled to a double-effect absorption refrigeration system. Unfortunately, this design is not feasible in 2024 because the high-temperature fuel cells are in the early stages of development.

A cost analysis was conducted for both designs in the current (2024) and projected (2030) scenarios. The results indicate that at the current level of hydrogen technology development and manufacturing, the operational costs of the low-temperature configuration were comparable to the traditional data centers. However, if hydrogen technology continues to develop according to the projected trends, the proposed designs can achieve up to 50% cost savings compared to the grid-powered data centers. This research showcases the potential for hydrogen as an energy carrier in data center applications, encouraging further research and exploration of hydrogen technologies.

The motivation of this study stems from the reality that 2.2 million households in South Africa remain unelectrified, with the majority residing in informal settlements—communities that are remnants of the apartheid era, designed to enforce racially segregated living. While existing off-grid solutions provide basic electricity access to these households, they fail to meet the growing demand for higher levels of electricity access that local residents desire and can afford. This project aims to address this gap between the limited supply capacity of current off-grid solutions and the enhanced electricity services that communities are eager to receive.

Through site visits and consultations with local developers, specific design considerations and unique challenges were identified. These efforts revealed the limitations of existing open-source design tools, which do not comprehensively address the entire system’s design requirements for the proposed solution of a PV-powered DC microgrid. Consequently, a new framework was developed, integrating open-source tools and custom Python scripts based on established methodologies.

The comprehensive design framework was applied to the informal settlements of Oudtshoorn and Daveyton, demonstrating its ability to generate feasible, scalable, and adaptable microgrid designs. Overall, this project provides a solid foundation for advancing electrification efforts in underserved communities.

As the global shift towards renewable energy accelerates, it is crucial to address the inherent challenges and fully leverage its potential. Electric power systems have undergone significant transformations, transitioning from traditional generation methods to those incorporating renewable energy sources and power electronic interfaces (PEI). This transition necessitates extensive research to ensure future grid stability and reliability. This thesis work aimed to enhance a Root Mean Square (RMS) synthetic model of the future 380 kVDutch power system and conducted comprehensive research using this model. A scenario analysis was conducted to evaluate various future scenarios for the Dutch power system, highlighting deviations and uncertainties. The national scenario from the II3050-2 project was selected as the baseline for further work. This approach ensured a comprehensive understanding of potential future developments and their implications for policy and planning. The synthetic model was developed by updating the existing model with new dynamic models and parameters as defined by IEEE and CIGRE standards and aligning it with future public projections and investment plans for the Dutch power system towards 2050, rooted in the scenario analysis. This included upgrading infrastructure such as transmission lines and substations and incorporating new generation and flexibility resources. The model was designed to enhance the dynamic characteristics and facilitate extensive research by integrating DigSilent PowerFactory, Python, and Excel. Three different case studies were performed using the enhanced synthetic model to analyze the system’s response to various perturbations. These studies evaluated the impact of varying levels of renewable generation and load, the role of grid-forming converters, and the effects of different kinetic energy and inertia constant levels on system stability with respect to frequency and rotor angle stability. The findings underscored the significant potential of grid-forming converters to enhance frequency stability and system damping, the influence of controller parameters on system performance, and the critical role of kinetic energy and inertia in maintaining system resilience. By leveraging the capabilities of PowerFactory, Python, and Excel, the research demonstrated the utility of the enhanced synthetic model in facilitating a broad range of stability studies and other analyses. This work provides a valuable foundation for future research and regulatory planning, contributing to the ongoing efforts of Dr. J.L. Rueda Torres’ team. The findings have been submitted to international journals and conferences, emphasizing the importance of continued technological adaptation and research to ensure stable and resilient power grids. Future work should focus on developing smart control strategies, optimizing dynamic control settings, investigating the impacts of kinetic energy and inertia constants, enhancing the synthetic dynamic model with additional features, and assessing the role of flexibility resources in future scenarios. This research offers crucial insights into the evolving dynamics of power systems and sets the stage for further advancements to ensure their stability and resilience.

Over the past decade, global efforts to combat climate change have focused on transitioning from fossil fuels to renewable energy sources and battery-based energy storage. This shift is essential to meet the rising global energy demand and integrate renewable power into the grid. However, the current AC based grid infrastructure poses challenges for incorporating DC based renewable sources like photovoltaic (PV) systems and battery storage. A rapid transition from AC to DC systems is impractical, necessitating a grid system that leverages the existing AC infrastructure while integrating DC systems. Hybrid microgrids (HMGs) have emerged as a solution to this challenge.

Our research focuses on a crucial component of HMGs: the Interlink Converter (ILC). Ideally, the two subgrids in a hybrid microgrid generate power to meet their respective demands. When one subgrid cannot meet its demand, the other supports it through the ILC. This system works effectively most of the time. However, during simultaneous power deficiencies in both subgrids, current standards prioritize AC loads, transferring power from the DC to the AC subgrid. This can lead to voltage fluctuations or blackouts in the DC subgrid, which is increasingly problematic as critical DC loads like EV charging stations and data centres grow.
The thesis titled ‘AC-DC Priority Control of an Interlink Converter’ aims to develop an optimal control strategy for ILCs, enhancing their ability to prioritize power transfer between AC and DC subgrids based on priority modes. This research is crucial for future grid stability and the integration of renewable energy sources.

LVDC Distribution systems are becoming popular due to the avenue of integrating renewable energy sources on a large scale. Predominant DC based power system architecture has been predicted to serve the needs of a sustainable society that holds the capability to self-generate, share, and trade power produced from renewable energy sources. Bottom - up approach beginning from development of products that run on DC till microgrids and integration of rural communities using LVDC distribution presents as a promising avenue for adoption of DC grids worldwide. Many areas in DC distribution system are yet to undergo rigorous study both theoretically and practically. Touch protection is one such area which is largely unexplored. Residual current devices (RCD) are traditionally implemented at the load side to trip at specific residual current levels ranging from few to hundreds of milli amperes. Current trip thresholds and time within which the fault must be isolated are different for DC. There is dearth of standards for DC RCD. In this thesis project we attempt to design a compact, reliable, and cost-effective RCD. The designed and developed prototype is tested at DC Low Voltage levels for various residual current magnitudes to determine important parameters like reaction time and accuracy.

The proliferation of Distributed Energy Resources (DERs) is decentralizing the power system, with more and more capacity installed in the distribution grids. Concurrently, the energy sector is embracing the Internet of Things (IoT) paradigm, resulting in the emergence of the Internet of Energy. However, this transformation introduces new concerns regarding cyber security. As the number of interconnected devices increases, the possible attack surface for malicious actors expands. Recognizing this challenge, researchers are investigating the potential cyber security benefits of applying blockchain in power systems. Blockchain offers some secure-by-design features, such as the immutability of the stored data, that can be leveraged to improve the cyber security of smart grids.
In this work, a blockchain-based application for the monitoring and control of a feeder in the Low-Voltage (LV) distribution grid is designed and tested. A smart contract is created and deployed in a private Ethereum blockchain utilizing the Proof of Authority (PoA) consensus mechanism. The blockchain application enhances the cyber security of the LV distribution system in three ways. First, it detects cyber attacks targeting DERs by comparing the setpoints received by prosumers with smart meter measurements. Second, it prevents cyber attacks by enabling the exchange of measurements and setpoints on-chain and by preventing unreliable prosumers from participating in the voltage regulation market. Third, it mitigates the effects of cyber attacks on the steady-state voltage magnitudes by enforcing a novel voltage regulation mechanism, in which a new metric is proposed to quantify the power-to-voltage relationship while considering the location of the power exchange.
The efficacy of the blockchain application is tested in a co-simulation environment together with a modeled LV distribution network, simulated in DigSILENT PowerFactory. The distribution network model is first used to assess the impact of cyber attacks manipulating the setpoints of Battery Energy Storage Systems (BESSs), which have been identified as the most critical DERs. The simulation results demonstrate that the considered cyber attacks can force the disconnection of inverters by causing violations of the acceptable steady-state voltage magnitudes. One of the scenarios demonstrates that a cyber attack targeting half of the BESSs in a feeder can lead to the collapse of the voltage, causing a local outage. Finally, the results of the co-simulation of the blockchain-based monitoring and control system, achieved by the Open Platform Communications Unified Architecture (OPC UA) communication protocol and by a series of clients managing the data streams, demonstrate its efficacy in detecting cyber attacks and mitigating their impact on the voltage magnitude across the feeder, thus reducing the number of disconnected DERs.

With an increase in higher power (ultra) fast EV charging stations and a new EU law for mandatory deployments of EV charging stations, an optimal MVAC grid connection for these charging stations is desired. Considering this connection, the use of a solid-state transformer (SST) performs better in terms of weight, size and efficiency with a similar cost, compared to the conventional low-frequency transformer (LFT) for MVAC to LVDC conversions. This study compares three MMC-based SST topologies where a DAB is connected to each submodule: Double-Star, Single-Star and Single-Delta. The cost of an MMC mainly depends upon the required energy storage and the switch stress. The topologies are therefore mainly compared based on these parameters, but other parameters are considered as well. With the goal of minimising the required energy storage, an 80% MMC energy storage reduction compared to the theoretical minimum requirement has been achieved by control.

A novel mathematical model has been proposed for each SST; this uses an MMC model based on the switching function and a DAB model based on the single phase-shift control. The model has been implemented in simulation and proven to accurately determine the average behaviour of the SST while significantly reducing the simulation complexity and time. This model helps to understand the SST's behaviour and furthermore allows for control system tuning both manually and automatically using the Genetic Algorithm.

Three different control systems have been designed. Control system A, where the MMC current is controlled by the average submodule voltage and the DAB controls the LVDC bus voltage. Control system B, where the DAB controls each individual submodule voltage and the MMC current is controlled by the LVDC bus voltage. Control system C, which is similar to control system B, but uses a stable DC voltage source on the LVDC bus and a set MMC current. An improved DAB control has been designed for control systems B and C, resulting in control systems B* and C*. This control is based on the use of a current feedforward and a PI controller combined with the inverted equations of the DAB model. The three topologies have been successfully simulated with this improved DAB control system using an 80% MMC energy storage reduction compared to the theoretical minimum requirement. This improves the general behaviour and significantly reduces the cost of the SST. The improved DAB control system has been tested using a hardware DAB with a current step input, which has shown that the new control system performs better in voltage peak reduction compared to PI control.

Out of the three topologies, the Single-Star topology performs the best. It has the lowest energy storage requirement and switch stress. Furthermore, its behaviour lies the closest to the ideal model. The best result for the Single-Star SST is achieved with the proposed improved DAB control, which leads to the lowest energy storage requirement, switch stress, THD, submodule voltage deviations and settling time. Out of these two control systems, C* performs the best.

The impedance-based approach is promising to analyse the harmonic emission and stability of a converter-based system, e.g., an EV fast charging station. When extracting the accurate impedance model of an EV charger, the knowledge of the charger’s circuit and controller parameters is indispensable. However, EV chargers’ manufacturers do not disclose the design parameters of chargers since they are confidential designs. Therefore, developing an approach to estimate the charger’s design parameters is practically beneficial for establishing the charger’s impedance model and thereby analysing the harmonic and stability of the charger-grid system.

Recent works on physics-informed machine learning provide a promising data-efficient approach to estimating unknown parameters of a system with a known physical model. However, to the author’s knowledge, such a technique has not been explored extensively in the power electronics domain. Thus, exploring whether PINN is also suitable for the parameter estimation of power electronic converters and how to implement this technique is worthwhile. In this thesis, to begin with, a Physics Informed Neural Net model is developed as a proof of concept to estimate the parameters of the boost converter. And subsequently applied to the AFE converter of the Fast-Charging Station to explore the scalability and generalisation of the model developed.

Implementing the physics model within the neural net is still an open problem; hence the physics parameters are estimated similarly to the weights and biases during the training process using the existing optimiser. This approach requires diving deeper into the development of the neural net, and hence instead of eager execution, TensorFlow’s computational graph method is used to build the neural net and the physics model. This allows complete flexibility to build the network from scratch with added complexity.

In the PINN model developed for the boost converter, the mean estimation error was 0.89%, and the parameters were estimated in 25.76 seconds. Because of the complexity of the physics model, optimizing the PINN model was challenging for the AFE converter. With a mean estimation error of 30.25%, the PINN model for the AFE converter took 361 seconds to execute. For both models, less than 150 data points collected over 25 switching cycles peak-to-peak values are used. The proposed PINN model developed in this thesis thus proves to be highly data-efficient with quick convergence. Despite the success of the developed PINN model, several drawbacks of PINN-based parameter estimation are also noticed and summarised.

Most nations have agreed to limit the emission of greenhouse gases within the Paris Agreement. The agreement relies on the assumption that all participating nations have accurate means of estimating carbon emissions and offsets accurately. However, global carbon emission accounting methodologies lack accuracy in approach and required carbon intensity data of utility grid electricity. From this, a need for developing a standardized accurate carbon emissions assessment methodology arises. The aim of this research is to develop an accurate carbon offset assessment methodology and determine the effect of using marginal, hourly average and annual average emission factors. The methodology is applied to a solar carport system in the Netherlands, consisting of a 465 kWp solar PV system, a 345 kWh nickel metal hydride battery and 16 DC charge points for EVs, in order to quantify the emission offset potential of the respective system components. This research presents a comprehensive literature review of existing carbon accounting methodologies based on which a new accurate methodology to calculate carbon offsets is developed. This methodology uses marginal emission factors from observed power dispatch and computes offsets on an hourly timestep. Application of marginal emission factor results in a 30 % and 23 % increase in carbon offset compared to hourly average emission factors and annual average emission factors, respectively. The carbon offset attributed to the battery system is roughly 100 kg CO2eq annually in 2019 and 1.5 -1.7 tons CO2eq in 2030. Relative to the lifecycle emissions caused by the battery system of about 200 tons CO2eq, including the battery system is not beneficial in terms of mitigating carbon emissions in solar carport applications. 99.96 % of the total offset is attributed to the solar PV system and lifecycle emissions of the solar carport can be mitigated after operation of 1.5 years when excluding the battery. Including the battery, lifecycle emissions are mitigated after 2 years and 3 months. To conclude, the results show that using marginal emission factors results in significant impact on the assessment results and are conceptually more accurate. Hence, they should be applied for carbon offset studies. Additionally, the carbon offset potential of the PV system is high while the contribution of the battery is low and installation of battery systems at solar carports is, therefore, not recommended.

A large contribution to the total share of electricity generated in European power grid will come from renewable sources of energy in the near future due to European initiative to become carbon neutral. RES are connected to the grid with PE devices, which if not modelled correctly provide lower level of system stability and security of supply. The existing power grid with mainly synchronous generators will not be suited to operate in the future, when synchronous machines will become less important sources of energy. An increase in dynamic behaviour of the system could cause significant challenges for the existing system, which calls for new monitoring and control strategies. The aim of the project is twofold; firstly, to enhance system stability by deploying WAMS in power system with a massive share of RES to total electricity generation. Secondly, it focuses on developing and proposing a tool which will improve consultancy in future power grids. A tool developed is Next Generation Grid Operations (NextGen GridOps) Knowledge Framework which is conceptually designed by DNV. The effectiveness of WAMS applications on system stability improvements and damping enhancements will be evaluated by studying rotor angle stability as well as effect of WAMS on damping of electromechanical oscillations. The response to a disturbance of the remaining synchronous generators will be studied to evaluate the effect of different types of control schemes (grid-following, grid forming control) on the rotor angle stability. Rotor angle stability will be examined to show whether different control structures and WAMS will show enhancements of the overall stability through time domain simulations. WAMS structure in this project consists of PMUs as well as WADCs. While PMUs are sensors deployed in the system to provide synchrophasor measurement, WADCs are damping controllers deployed with an intent of enhancing damping in the system. This project build upon findings from Horizon 2020 MIGRATE Project. The effectiveness of grid-following control and grid-forming control on stabilizing the grid with massive penetration of PE devices are conducted to set the base case for evaluating the effect of WAMS. Modelling software used in the project is DIgSILENT PowerFactory 2021 SP1 and the PowerFactory Thesis Licence was provided by DIgSILENT GmbH for research and educational purposes. Based on the off-line numerical simulations conducted in IEEE 39 Bus New England test system it was found that WAMS functionality with corresponding PMUs and WADCs can decrease oscillations in the system. It has been verified that grid-following control enables 60% of RES penetration and grid-forming control enables penetration of RES above 80%. There have been two grid-forming controllers used in the system, where DVC is able to receive the stabilizing signal while VSM grid-forming controller has a supporting role. WAMS and corresponding WADCs deployed on DVCs are able to enhance damping of the low-frequency modes with frequencies below 2.0 Hz, which is supported by time domain simulations and by conducting Prony analysis. Eigenvalue analysis results for some cases with WAMS deployed show no additional enhancements, which is a consequence of newly introduced controllers and interactions among them and existing controllers. The practical implications of this Master's Thesis study have been modelled in the NextGen GridOps Framework with an intent to make a step towards real world implementation of the findings developed during the project. Framework modelling focused on implementing client maturity classification of WAMS deployments, contributing towards development of WAMS roadmaps and further deployment of WAMS solutions for grid operators as part of the DNV Next Generation Grid Operations advisory services. Work done and information implemented will be valuable for DNV while solving the complex process of future grid operations and at the same time bringing newly developed knowledge into practice. The framework development part of the project ties in with scientific contribution by allowing newly developed information to be further explored. Effectiveness of WAMS and WADCs on improving selective damping and consequently enhancing system stability has been identified in this project through use of DVCs. It has been proven that VSM control has a better stabilizing effect and would allow even further enhancement of damping critical oscillation modes. Higher damping in the system increases the stability and consequently higher security of energy supply.

One of the main reasons that the efficiency drops from cell to module is the conduction losses. To increase the efficiency of the PV module, the produced charge carriers in the semiconductor materials should be transferred to the PV module terminals with minimum conduction losses. As an alternative to the conventional cells and modules interconnections, in this thesis project, efficient ways to incorporate Wireless Power Transfer (WPT) techniques into PV cell and module architecture are being sought.

The main objectives of this research are to understand how WPT techniques can be efficiently incorporated into PV devices, such as PV cells and modules, find out whether these techniques in theory and in practice are efficient enough and suggest the best design approach as a guideline for near future prototyping.
Many different WPT methods were studied in theoretical level, such as the Capacitive Power Transfer (CPT), the Inductive Power Transfer (IPT) and the Magnetic Resonant Coupling (MRC). Based on the main advantages and disadvantages of these methods, the most efficient seems to be the MRC, which eventually was used as the main method of transferring power wirelessly in the systems of this thesis project.

The systems that were developed and studied consist of a PV generator made of a single IBC solar cell or a PV generator that consists of 16 connected in series IBC solar cells, an inverter that converts the direct current (DC) of the generators into alternating current (AC) and two resonant circuits, the primary and the secondary one. Between these circuits, the power is transferred wirelessly from the primary to the secondary one, through the magnetic field that is created.

During this project, the main mathematical models were developed and were used for simulations in both Matlab and Simulink. The main goals of these simulations were to find out which type of coils, as far as the shape, the cross section and the values of turn width, turn spacing, distance between the coils and number of turns are concerned, and which compensation topology would help the systems to develop higher efficiencies.

According to the results, when ideal DC to AC conversion at the primary side of the system is assumed, the most ideal option seems to be the Series-Series compensation topology with planar coils of circular shape and rectangular cross-section, for which the systems developed efficiencies higher than 85% when the circuits were connected with one solar cell and above 98% when the circuits were connected with one module of 16 solar cells.

In urban environments, more and more building added and building integrated photovoltaic (PV) systems are found. These systems use conventional solar modules which have a poor performance under non-uniform illumination conditions. When the module is partially shaded, either at least one
subgroup is bypassed or the module current is limited by the current of the worst performing cell. This leads to significant and disproportionate power losses. One way to address this issue is to implement a solar module made of low reverse breakdown voltage (BDV) solar cells.
A thermo-electric simulation framework was developed in MATLAB to replicate two types of commercially available low BDV solar cells: Sunpower Maxeon gen2 and gen 3 cells. Using the above model the potential and performance of solar modules in urban landscapes has been evaluated. A comparative study of solar module models built with these cells and placed on three different locations on a single rooftop having completely different irradiance profiles has been assessed. A solar module with 3 bypass diodes made of gen 3 solar cells has a better performance than module made of gen 2 cells. This accounts not only for better forward parameters of gen 3 cells but also its improved mismatch losses owing to lower reverse breakdown voltage and better temperature coefficients.
The usage of low reverse breakdown solar cells is beneficial in conditions where partial shading is predominant. Other advantages of using these solar module over other technologies is there is that there is no need of any additional electronic components.