The pressing need to mitigate global warming and transition to sustainable energy solutions has accelerated the development of innovative energy systems. This thesis investigates the sizing and design of a photovoltaic thermal (PVT) system integrated with aquifer thermal energy storage (ATES) within a fifth-generation district heating network (5GDHN) for a case study in the Werfgebied district in Hilversum, Netherlands. The study focuses on the configuration, storage distribution, and optimisation of component sizing within the district heating network to minimise overall electrical power usage, thus reducing grid dependency and CO2 emissions. A Python model of the multi-energy carrier system is developed, embedding the physical principles underlying the thermal and electrical properties of the components. The research finds that an optimal configuration for the ATES and PVT combination involves a single ATES well rather than distributed thermal energy storage. The results indicate that the size of the aquifer significantly affects the overall operating temperature and its fluctuations. A larger ATES maintains a stable but relatively colder temperature. Optimal sizing is achieved at the maximum allowed operating temperatures of an ATES in these areas, resulting in the most favorable temperature for maximum COP in the heat pumps. This minimises grid exchange and CO2 emissions. The optimal ATES size is determined to be 380,000 m3, in combination with 800 PVT modules, leading to a total CO2 equivalent emission of 856 tonnes.

With the energy transition, electrical energy consumption is increasing heavily. Electric vehicles replace cars with internal combustion engines, and electric heating replaces gas-heated homes. The AC electricity grid becomes congested with the increase in load. Local electricity generation through PV panels or windmills also increases, but there is generally a mismatch in generation and demand. Besides, practically all electrical equipment uses DC directly or in the conversion process. This makes using DC grids much more efficient than AC grids. The distribution grid can not convert directly to AC. DC microgrids could prove an attractive solution to support the distribution grid and to move gradually to a DC grid. These locally operated grids combine load, generation, and energy storage. A bipolar DC microgrid further increases efficiency by providing an additional voltage level and doubling the power compared to a unipolar DC grid with the same pole voltage. A DC/AC converter will interface the LV AC grid and the DC grid to enable energy exchange between the grids.

Research is conducted to the design and modulation techniques for a transformerless bipolar 700 V DC grid interfacing converter. Mitigating the isolation transformer increases efficiency and reduces material usage, but will also provide a path for ground leakage current to flow. An NPC converter topology is selected and an 11-segment modulation scheme is implemented using sub-references and carriers. This scheme mitigates the oscillations in the DC neutral point, while simultaneously reducing the ground leakage current to acceptable levels. Furthermore, a novel dead time compensation method is implemented to reduce the ground leakage current further. Finally, a new concept to provide unbalanced power to the poles based on the pole voltages is introduced. Simulations and experimental tests show that the developed modulation technique can enable a transformerless connection.

The goal of this thesis is to analyze the limitations encountered in real-time smart charging during DPMand to integrate them into a smart charging algorithm that schedules EVs. A base case scenario willbe set up to reflect the present dynamics of DPM in a three-phase grid. This scenario will serve as a benchmark for evaluating the smart charging algorithm. The smart charging algorithm itself will employ mixed-integer linear programming (MILP) within a Receding Horizon Optimization (RHO) framework aimed at minimizing charging costs while maintaining a high State of Charge (SOC) for the EVs. To integrate the practical limitations, the grid constraints of a three-phase system will be analyzed and incorporated into the optimization.
Furthermore, a laboratory setup will be constructed to validate the charging behaviors that need to be incorporated into smart charging algorithms and to explore new EV charging behaviors in an experiment. The charging phenomena identified as significant will be integrated into the smart charging algorithm, with a lookup table, to assess their influence on the overall system performance.
The results of this investigation provide valuable insights regarding the charging behaviors and the impact of incorporating these behaviors into a smart charging algorithm. A degradation of the charging efficiency was noted at low charging currents, with the significance of the degradation varying between EV types. Additionally, a voltage discrepancy of the pulse width modulation (PWM) signal of the EVSE was observed, causing an offset between the setpoint of the charging current and the real charging current transmitted by the EVSE.
When these results were incorporated into a smart charging algorithm with a lookup table, clear improvements were seen in the total charged capacity compared to a smart charging algorithm that did not include the lookup table. At a grid capacity of 125 A, the smart charging algorithm with the lookup table provided an increase in charging capacity of 5.23% and an increase of 1.40% for a grid capacity of 175 A. Furthermore, it was observed that the smart charging algorithm with the lookup table could increase the total charged capacity for the low grid capacity of 125 A by 3.97% compared to the charging algorithm that performed immediate charging and DPM.
Both smart charging algorithms, with and without lookup table, show the same reduction in cost compared to the base case algorithm that performs DPM and immediate charging. A decrease in the average charging cost to 4.88% at a grid capacity of 125 A was noted. When the grid capacity is increased, the charging cost could be further decreased to 12.23%, as the increased capacity allows for greater flexibility in scheduling EVs during periods of lowest prices, optimizing the utilization of available power.

Multilevel inverters are widely used in industries for higher power applications due to low harmonic pollution and high efficiency. On the other hand, the phase-shift switching technique is well-known for its harmonic mitigation performance. However, phase-shift switching has not been regularly implemented on multilevel inverters due to complexity at a higher number of levels and difficulty in voltage balancing of the auxiliary capacitors in the configuration. In this project, the five-level Packed U-Cell inverter (PUC5) will be investigated to design and implement a phase-shift switching technique with an integrated voltage balancing algorithm. The developed technique will be implemented on the real-time simulator and hardware setup.

A literature review will be done on phase-shift switching algorithms and multilevel inverters. Afterward, a phase-shift switching algorithm with an integrated voltage balancing technique will be developed for the PUC5 inverter and simulated in Simulink. Hardware-in-the-loop (HIL) will be done using Opal-RT devices.

The number of satellites launched every year is ever-increasing. Satellites generate energy through solar panels, transferring it to the satellite hub using Slip Ring Assemblys (SRAs). However, SRAs suffer from limited lifetime and operating voltages. Therefore, this research investigates a Contactless Energy Transfer (CET) system for the satellite to eliminate these problems. The system consists of an input source, inverter, Alternating Current (AC)-link and rectifier. A single diode model is introduced for the solar panel input source to model its behaviour. After a brief comparison, the Inductive Power Transfer (IPT) method is favoured over the Capacitive Power Transfer (CPT) method. As a result, the AC-link includes a transformer to obtain the contactless energy transfer. The Single Active Bridge (SAB) topology is chosen after comparing the characteristics of the SAB and Dual Active Bridge (DAB) topologies. Afterwards, two SAB converters, the Single Active Bridge with Output Inductor (SABL) and LLC converter, are compared before choosing the LLC converter. With the CET system design completed, the design procedure for the LLC converter is presented, resulting in transformer requirements. A coaxial solenoid transformer design procedure where the inductance and losses are modelled is used to create a prototype transformer. The models are validated using Finite Element Method Magnetics (FEMM). The designed transformer met the inductance requirement. However, the losses were too significant to meet the overall CET system efficiency requirement.

The emergence of electric mobility in urban public transportation, with a particular focus on electric buses, presents a promising solution to address emissions and environmental concerns. However, a significant challenge lies in ensuring continuous bus operation without the need for frequent charging. In-motion charging (IMC), often referred to as dynamic charging, is a concept engineered to overcome this challenge.

A comprehensive study was undertaken to know the potential and practicality of intercity IMC buses. A bus model was developed to assess the power traction capabilities of these vehicles. This model served as the foundation for exploring four distinct charging scenarios, each characterized by varying charging powers and strategies. An investigation into the battery load profiles observed in intercity IMC buses across the different charging scenarios was done. This was essential for understanding the intricacies of power demand, especially in scenarios where the bus relies heavily on catenary charging. Notably, the introduction of in-motion charging in the first scenario (IMC only) underscored the critical role of catenary charging power in meeting operational demands. Subsequent integration of a stationary charging system at Arnhem Central showcased the potential to reduce catenary charging power, offering prospects for enhancing battery health. IMC with opportunity charging and overnight charging were also explored.

The second part of the thesis delved into the comparative effect of various charging scenarios on the aging of commonly employed battery chemistries in IMC vehicles. Using comprehensive battery models, the aging dynamics under diverse conditions were studied. It became evident that each scenario held distinct implications for battery aging.

Lastly, the study addressed the pivotal question of cost-effective battery selection for intercity IMC buses. An exploration of four distinct scenarios, in conjunction with different battery chemistries, yielded valuable insights into their respective performances. Lithium-titanate (LTO) batteries consistently emerged as the preferred choice. Their extended lifespan, reduced replacement frequency, and overall cost-effectiveness positioned them as the frontrunners in the context of intercity IMC bus systems. This consensus held across most scenarios, underscoring the practicality of LTO batteries.

In conclusion, the transportation sector's substantial impact on greenhouse gas emissions and urban air quality necessitates innovative and sustainable solutions. Intercity IMC buses, along with optimal battery selection and charging strategies, represent a promising avenue for sustainable urban transportation. Among battery chemistries, LTO batteries was proven to be the most cost-effective choice for powering intercity IMC bus operations.

This thesis titled "Addressing voltage sag contribution of an optimally sized Industrial Hybrid Power System" introduces a framework for sizing an industrial Hybrid Power System (HPS) to minimise Cost and CO2 emissions relative to connecting the industrial site directly to the grid with the help of a genetic algorithm, specifically NSGA-II. The framework utilises an Energy Management System (EMS) that is based on a rolling average principle which attempts to restrict the change in grid consumption from one time step to the next. The optimally sized configuration and its new grid consumption profile are analysed in the CIGRE MV Distribution Network to assess the effects of the new consumption profile on the bus voltages. The combination of a rolling average-based EMS and an optimal sizing with NSGA-II resulted in a $47\%$ reduction of the CO2 emissions while not worsening the voltage behaviour in the system (with a focus on voltage sag introduced by large loads).

There will soon be a huge influx of EV chargers required in the coming years. Therefore it is important to find out the lifetime of EV chargers like the DC Fast Charger for business cases. These chargers are a combination of multiple power converters to help regulate the grid AC voltage to something that can be used to charge the battery. Multiple Industrial surveys have shown that the most vulnerable parts of power converters are the power semiconductors used inside them. Moreover, research shows that most of the failure in these EV chargers is due to thermal cycling which causes thermo-mechanical fatigue. While there are studies that estimate the lifetime of these semiconductors, it is seldom done in the context of EV charging load profiles. These EV charging load profiles are responsible for long-term power cycling contrary to short-term power cycling which is generally done to estimate the lifetime of the semiconductors. This thesis shall thus choose a popular DC Fast Charger power converter, feed in
a load profile and analyse the effects of thermal degradation of the switches and rectifier diodes present in the circuit. This data will then be used to make an estimate of how long the whole power converter will last thus leading to the lifetime of the DC Fast Charger.

This master's thesis presents the design and analysis of the inverter stage and controller architecture for a modular Solid-State Transformer (SST) to interconnect DC microgrids and a 10kV AC grid for bidirectional power flow. The research focuses on inverter topologies, modulation techniques, and modular controller architecture.

The inverter stage, a crucial stage of the modular SST, converts DC power from microgrids to AC power suitable for the 10kV AC grid. The most popular inverter topologies for modular converters are researched and investigated based on their compatibility with the specific application. Factors such as efficiency, power quality, harmonic distortion, number of components, control complexity, and scalability are considered for this process. Along with the topology, modulation techniques are important in producing high-quality output waveforms and efficient power transfer. Different modulation strategies, including pulse width modulation (PWM) techniques and space vector modulation schemes specifically for multilevel converter applications, are reviewed and discussed in terms of how they affect the system's performance.

In addition to the inverter stage, the thesis focuses on designing a modular controller architecture for the SST. The controller design prioritizes maintaining flawless data flow and synchronization between all controllers for converter and AC grid coordination. The central controller and distributed control architectures are studied and evaluated for scalability, modularity, and flexibility. The distributed architecture enhances the system's overall flexibility but is subject to synchronization issues and limitations in communication bandwidth. These issues are addressed in the developed design.

To evaluate the performance of the proposed inverter stage and controller architecture, extensive simulations and experimental validations are carried out. The simulations consider various operating conditions, such as islanded and grid-connected modes, to assess the system's stability, control, harmonic content, and power quality in the output waveforms. The simulation results indicate that the chosen inverter design and modulation strategies successfully attain high efficiency and minimal harmonic distortion in the operation of the converter. The modular, distributed controller design demonstrates its ability to provide seamless operation and effective coordination between DC microgrids and the AC grid.

Overall, this master's thesis contributes to the advancement of solid-state transformer technology by delving into the design of the inverter stage and controller architecture for interconnecting DC microgrids and a 10kV AC grid and providing useful insights. The findings and recommendations can be a valuable framework for future research and development of modular SSTs for grid-connected applications.

The EU strives to lower greenhouse gas emissions. To reach this goal, many energy intensive processes in the residential sector such as heating and transportation will be electrified using heat pumps and electric vehicles (EVs) respectively. Simultaneously, a transition of electricity generation to sustainable sources will take place, necessitating an increased adoption of rooftop photovoltaic (PV) systems.

The adoption of PV systems, heat pumps and EVs, also known as low carbon technologies (LCTs), can increase three-phase unbalance in low voltage (LV) distribution networks as many of these components will be connected to a single phase of the three-phase network. Threephase unbalance is undesirable in a three-phase system, as it causes among others, energy losses and a suboptimal use of network capacity.

The aim of this thesis is to evaluate the impact of different combinations and penetration levels of LCTs on three-phase unbalance in different real LV distribution networks through simulations and how unbalance is affected by LCT location, season and LCT control schemes.

Simulations were performed on six different grids, varying in level of urbanization and loading, with increasing levels of LCT penetration (0%, 50%, 80%, 100%). In these simulations, LCTs were integrated in varying combinations (PV & EV, PV & HP and PV & EV & HP). For every simulation, the maximum and mean voltage unbalance factor (VUF) was determined. Seasonal effects and the effect of an LCT control scheme were also evaluated.

Simulations showed that the voltage unbalance factor exceeded the legal limit of 3% for two of the six grids for high levels of LCT penetration when all LCTs are integrated. Combining all three LCTs resulted in the highest unbalance levels. Varying the locations of the LCTs resulted in significant differences in unbalance levels. Comparing a winter week with a summer week, the overall unbalance is similar, however, the contribution of the PV systems to the unbalance is increased, while the contribution of EV chargers and heat pumps is decreased.
The effect of the LCT control scheme was limited.

As the integration of LCTs will increase considerably in the near future, three-phase unbalance levels exceeding the limit of 3% will occur more often. To prevent unbalance levels from structurally exceeding the legal limit of 3%, more effective control schemes should be designed and implemented.

As demand for clean and renewable energy around the world increases, solar photovoltaic (PV) technology becomes substantially popular, especially in low-voltage (LV) distribution networks. However, the integration of PV in LV distribution networks requires careful planning as it introduces voltage violations. To maintain network voltage, distributed control of residential-scale battery energy storage systems (BESS) is a possible option. Previous studies considered only one-day simulations with limited testing conditions. However, it is important to evaluate voltage control capability over an extended period of time. Moreover, it is important to estimate battery lifetime for the economic feasibility evaluation of distributed control.

This work aims to present a distributed control method for BESSs at a residential scale to provide voltage support in a highly PV-penetrated LV network while providing insights into their lifetime estimation. A control method based on a consensus algorithm with the addition of SOC balancing control is proposed and tested on a modified CIGRE LV distribution network using MATLAB/Simulink. Evaluations on the voltage support capability and control behavior are performed in various testing conditions and are extended beyond one day of simulation. Moreover, a battery lifetime estimation is performed using the resulting cycling profile from the proposed control.

The proposed control strategy can provide voltage support in most case variations with the exception of cold seasons and extreme addition of PV power generation. Concerning battery lifetime, there is only a small observable capacity fade from the proposed strategy’s cycling profile. It is important to investigate calendar aging because of the small cycling current from the operating conditions presented in this work.

The transportation sector is moving towards a green future with a rapidly growing EV market and consequently, the demand for EV chargers is rising too. With the increased interest in 800V batteries and the current presence of 400V and 600V batteries, the voltage range for EV chargers is wide (150V-1000V). In this thesis, a wide-output EV charger based on two DAB converters with series-parallel output is proposed. A novel method of reconfiguration is introduced to allow live transitioning between series and parallel mode. The circuit of a 25kW converter is optimized to achieve optimal efficiency during a charging cycle. A comparison between advanced DAB modulation strategies is made and Triple Phase Shift (TPS) modulation in combination with Minimum Current Stress Optimization (MCSO) improves the efficiency of the DAB at low voltage and low power operation. The converter operates at >97.6% efficiency in the full range of 150V-1000V with a peak efficiency of 98.8%. A 25kW converter is modelled and simulated in PLECS, and a 200W hardware prototype is built to verify the new method for live transitioning.

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.

As more and more solar panels are installed on households, a problem arises when the power from the solar panels fluctuating throughout the day due to clouds passing over the solar panels. This in turn causes voltage flickers in the household, which can be visible/irritable to the human eye and damage appliances in the household. These voltage flickers can exceed limits set by the IEC standard 61000-3-7 or the visible flicker threshold on the Low Voltage (LV) network set by Qualtech [1]. This problem can be solved by making use of an Energy Storage System (ESS) which delivers active power in order to reduce and avoid the voltage fluctuations above the visible flicker threshold. In this report, a novel control algorithm is designed and implemented in two different ways to control the active power dispatch of the ESS. The main goal for the control algorithm is to reduce or avoid any visible voltage flickers from occurring and minimizing energy usage asmuch as possible in order to open the possibility for a Supercapacitor Energy Storage System (SESS) application in the future. For this, a power to energy ratio of higher than 70 is needed to achieve this. The primary control algorithm makes use of a moving average with a weight distribution that is optimised for smoothness and accuracy. Furthermore, extra layers of control was added to the control algorithm tominimize energy usage. The first implementation of the control algorithm, called power control, makes use of the Photovoltaic (PV) system output power to dispatch the appropriate amount of power from the ESS. The second implementation, called voltage control, makes use of the measured voltage at Point of Common Coupling (PCC) to dispatch the ESS power. Simulation results using pre-existing PV system data showed that the power control implementation was not able to fully eradicate all of the measured visible and annoying voltage flickers. The voltage control implementation was able to do so within the window of operation. Furthermore, simulation results showed that the energy usage from the control algorithm with a power control implementation uses 87% percent less energy than a control algorithm using conventional moving average. The energy usage from the control algorithm with a voltage control implementation uses 95% less energy than the conventional moving average control algorithm. Furthermore, the power to energy ratio of the control algorithm with a power control implementation was around 98.9 and with a voltage control implementation the power to energy ratio was around 190.2. This shows a clear implementation of a SESS in the future. Two different experimental setups were built and commissioned. The first setup having the Battery Energy Storage System (BESS) connected via an inverter on the same Alternating Current (AC) bus with the PV system. The second setup has the BESS connected on the same Direct Current (DC) bus with the PV system which is then connected to an inverter. Experiment results showed that the DC connected ESS experiment setup operating in power control mode had the best performance in terms of avoiding any visible voltage flickers from occurring. While the AC experimental setup and mode of operation (voltage and power control mode) did not operate properly due to the slow inverter response time. In terms of energy usage, both experimental setups had very low ESS energy usage. Although the results showed that power to energy ratio from both experimental setups using both power and voltage control did not exceed the set goal of 70 due to the limitations of both experimental setups. Finally, a conclusion based on the results is given with future work and as well as recommendations for the continuation on this research topic.

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 increasing adoption of renewable energy sources, particularly photovoltaic (PV) systems in residential sectors has raised important energy balancing challenges due to the intermittent nature of energy generation. To address these challenges and prioritize cost savings for residential consumers, this research investigates the integration of battery energy storage systems (BESS) and dynamic pricing strategies through an intelligent energy management system (EMS). Given the stochastic nature of PV generation, market prices, and load profile it is still challenging to achieve optimal control. Therefore Reinforcement Learning (RL)-based EMS is proposed in this research to make real-time optimal control decisions. RL is a machine learning approach where an agent learns to make decisions by interacting with an environment to maximize cumulative rewards. In this study, a deep deterministic policy gradient (DDPG) RL architecture is chosen due to its capability to handle continuous action spaces. In addition, deep learning-based models are employed to forecast uncontrollable load, PV generation and market prices for the integration into the EMS for which Bi-directional LSTM (Long Short Term Memory) was found to be the most accurate for all three uncertain variables. The DDPG algorithm is trained with data from a single household from the Lucerne region, Switzerland for 30 days and tested for a week. The results showed that compared to a deterministic rule-based approach the RL-based EMS increased cost savings for the end consumer by 14.2% but reduced the benefits for the grid operator to alleviate grid congestion quantified in terms of load factor, peak power consumption and ramping. Further work could be undertaken in testing the model on more extensive data and finding the best trade-off between customer and grid operator benefits.

With the increasing appearance of DC loads and DC sources in the MVAC distribution grids, the need for DC power systems is getting more and more pronounced. As a result, the MMC has become a promising and innovative technology that can serve as the interface between a DC and AC network. The MMC-based MVDC distribution link is one of the solutions to incorporate DC in power grids. This link consists of two back-to-back configured MMCs connecting two possibly asynchronous AC networks. Generally, an MVDC distribution link is operated at a fixed rated DC voltage set through the MMC. This work explores the possibility of enhancing the DC link voltage beyond the nominal value to improve the power transfer capacity of the distribution link. The enhancement is achieved while preserving the average energy stored in the MMC and maintaining the AC-side harmonic performance.
First, a control strategy was developed that qualified for the static operation of back-to-back configured MMCs. This control strategy was designed using multiple sub-control modules, each regulating one or multiple circuit quantities using a closed-loop PI or PR control strategy. Second, the analytical limitation to the DC link voltage enhancement was determined. This provided the enhancement boundary expression, which revealed the dependence between the enhancement limit and the grid-injected reactive power. Third, the MMC control strategy was adapted to dynamically incorporate the DC link voltage enhancement. This was performed using the open-loop DC link voltage control, which dynamically enhanced the link voltage by using the reactive power input reference. The controller is realised using a finite state machine that provides an event-driven control system with conditional state transitions. Simulations verified the performance of this controller. Finally, the dynamic DC link voltage controller is implemented for a lab-scale MMC and optimally tuned using the MO tuning method. This is to provide experimental verification of the DC link voltage enhancement. Three experiments were performed to: demonstrate the workings of the enhancement concept, verify the analytical enhancement boundary expression, and show the performance of the dynamic DC link voltage controller. The experiments concluded that the open-loop dynamic control successfully achieved the DC link voltage enhancement and limited the grid injection of harmonic elements during system transients.
So it is concluded that the power transfer capacity of an MMC-based MVDC distribution link can be enhanced by applying dynamic DC link voltage control. This while operating with the same submodule stresses and preserving the AC-side harmonic performance. When the DC current of the distribution link is fixed at the rated value, the power transfer capacity of the link increases linearly with the controller enhancement function. For system transients, the dynamic controller uses smart control logic to avoid harmonic element injection. Combined, this concludes that the dynamic DC link voltage control achieves a proper DC link capacity enhancement that meets the requirements for both steady state and dynamic conditions.

With the popularity of electrical vehicles (EVs), the demand for EVs charging is also increasing. Compared to traditional wired charging, wireless charging can avoid many safety issues. The efficiency of wireless power transfer (WPT) system is determined by many factors, the coupling factor is one of the most important factors. Therefore, estimating the coupling factor of WPT system is necessary. The research objectives of this work are to review and benchmark different methodologies of coupling factor estimation. Besides, a comprehensive method is selected and simulated. This work is focused on magnetic inductive WPT systems. Five different methodologies of coupling factor estimation for static WPT system and one methodology for dynamic WPT system is reviewed and analyzed. The methodology that uses alternative capacitors to estimate the coupling factor of a static WPT system is analyzed in detail. By using the zero crossing unit, the primary side and secondary side of WPT system are under full resonant. The WPT system will work in two different modes by changing the primary side capacitance. The two sets of circuit parameters will be recorded and calculated by a PLL unit. Based on theoretical analysis and the calculated parameter, the load and mutual inductance of WPT system can be identified. Therefore, the value of the coupling factor can be determined. The accuracy of coupling factor estimation of this methodology is higher than 97 %.
Compared to the literature that proposed this methodology, this work made a sensitivity study. The circuit parameters are made to fluctuate in a certain range. The accuracy of estimation of mutual inductance is still higher than 95% when the primary side resistance, secondary side resistance and load fluctuate. However, the system becomes unstable when the primary side capacitance, inductance and secondary side inductance fluctuate. The reason is that when the capacitance and inductance change, the operating frequency will deviate from the resonant frequency. However, the mutual inductance identification unit is not able to detect this deviation. If the deviation of circuit parameters is updated, the accuracy of coupling factor estimation will remain at about 97%.

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.