Summary
The rapid adoption of renewable energy sources has accelerated DC microgrid deployment as efficient alternatives to traditional AC systems. However, power electronic converters introduce significant stability challenges through active impedance characteristics exhibited by constant power loads. This thesis addresses stability challenges in multi-converter DC microgrids through passivity-based design principles and impedance measurement techniques.
Problem Statement
DC microgrids rely on power electronic converters to interface renewable sources, energy storage, and loads. These converters can exhibit active incremental input impedance, violating traditional stability assumptions and causing oscillatory instability when interacting with grid resonances. The challenge intensifies in multi-converter systems where multiple feedback loops interact through the common DC bus, creating complex dynamics that traditional design approaches struggle to manage.
Research Contributions
This research makes four primary contributions:
Passivity-Based Stability Analysis: A theoretical framework was developed linking converter impedance characteristics to system stability. The analysis establishes that requiring positive real impedance above a threshold frequency enables stable interconnection regardless of system complexity.
Active Damping Control Strategy: A digital control approach was investigated that modifies converter impedance characteristics above a design frequency while maintaining low-frequency regulation performance.
Frequency Threshold Investigation: Through analysis of typical component values in practical systems, a frequency threshold range of 200–400 Hz was identified for stability considerations.
Impedance Measurement Platform: A broadband impedance characterization system was developed using pseudo-random binary sequence excitation as an alternative to traditional frequency response analysis methods.
Validation and Findings
The research employed theoretical analysis, simulations, and experimental verification. Simulation studies demonstrated significant improvements in oscillation reduction and settling time compared to uncompensated systems.
Analysis established that enforcing positive real impedance conditions above the threshold frequency prevents destabilizing interactions between converters and grid resonances. The control strategy successfully modifies impedance characteristics while preserving dynamic performance.
The measurement system demonstrated capability to characterize both power supply and device impedance from single measurements, though accuracy limitations indicate need for enhanced calibration approaches.
Impact
This work provides analytical frameworks for designing stable DC microgrids accommodating high renewable energy penetration. The passivity-based approach offers scalable stability analysis methods that remain valid as system complexity increases, addressing barriers to widespread DC microgrid deployment.
The research contributes to emerging standardization efforts and provides guidance for both converter manufacturers and system integrators in ensuring stable operation.

In this paper, a batch-based industrial load model is used to model the energy system of a hydrogen-based steel plant. It is formulated in Gorubi as a profit-maximizing Mixed Integer Linear Programming (MILP) problem. The addition of H2 units to the steel plant introduces new operational aspects in steel production. This requires energy efficiency constraints to optimizematerial usage, consideringwarm-up time for specific units, and exploring the impact of a fuel cell system with the plant. The existing industrial load model is modified and new constraints are added to obtain flexible behavior, where units have the choice to consume electricity as part of their normal operation or sell the electricity back to the market. 40 scenarios are generated to optimally manage the energy consumption of the plant. Sensitivity analysis reveals that a fuel cell has a low impact on profit in low price periods, hydrogen storage is essential to overcome losses for the assumed average price , and flexible operation achieves the highest profit when encountered with a peak price. After obtaining the energy consumption of the units, they are modeled as loads in Pandapower assuming the worst-case scenario. Then, a time-series load flow analysis is carried out to validate the rating of the main transformer for the radial network. Finally, the peak active and reactive power of the plant is modeled as a static load in a representative European high voltage grid, where load flow reveals that bus voltages and line loadings depend on the location of the plant in the system.

The global energy transition poses significant challenges for urban infrastructure as it necessitates robust sustainable energy systems. In the Staatsliedenbuurt Oost neighbourhood of Hilversum, Netherlands, the grid is experiencing congestion due to a convergence of factors: rising electricity consumption from electric vehicles (EVs) and heat pumps (HPs), and the intermittent nature of local solar generation. This situation complicates the neighborhood's ability to reduce its dependency on fossil fuels. This thesis aims to determine optimal, economically feasible configurations for a multi-carrier energy distribution system for a block in the neighbourhood to meet projected energy demand by 2030, reduce grid dependence, and quantify its CO² emissions reduction potential.
A linear programming (LP) model was developed to minimize the net annual cost (NAC) of the system, optimizing the capacity of solar photovoltaics (PV), battery energy storage systems (BESS), air source heat pumps (ASHPs), and seasonal thermal energy storage (STES). The model utilised 15-minute resolution, simulation data and incorporated scenario-based analysis for varying EV and HP adoption rates, including an ambitious "Net Zero" scenario that eliminates grid import. Block 7 was selected for detailed analysis after an initial optimization across 14 neighbourhood blocks.
For Block 7, under a 50% EV and 50% HP adoption scenario, the optimal configuration included 121.467 kW_p Solar PV, 36.801 kW BESS power, 151.602 kWh BESS energy, 55.782 kW_th ASHP, and 526.053 kWh_th STES. This configuration achieved a NAC of €50,792.02, with grid-related costs forming the largest portion. The system demonstrated a degree of autarky (DoA) of 48.06%, with a levelized cost of electricity (LCOE) of 0.362 €/kWh and a levelized cost of heat (LCOH) of 0.120 €/kWh_th. Increasing EV and HP adoption generally led to higher unit costs and increased grid reliance, along with a decrease in DoA. The "Net Zero" scenario achieved 100% DoA but at significantly higher costs (€1.857/kWh LCOE, €0.634/kWhth LCOH) and an extremely high PV curtailment rate (PVCR) of 88.97%. Environmentally, the system showed substantial greenhouse gas (GHG) emissions reduction potential, saving 32,834 Kg CO² equivalent in the base scenario, which rose to 93,516 kg CO² equivalent in the Net Zero scenario.
This research provides a practical framework for mitigating energy challenges in urban environments, contributing to a more resilient, sustainable, and cost-effective local energy ecosystem. It addresses critical research gaps by offering a holistic techno-economic assessment of total residential energy demand within a specific national context, and by exploring the synergistic integration of diverse energy storage technologies and comprehensive sector coupling.

The accelerating Dutch energy transition faces a growing challenge: grid congestion is increasingly limiting the integration of local renewable energy and electrification initiatives. This thesis addresses this challenge by designing and optimizing a Closed Distribution System (CDS) for the Werf area in Hilversum, a mixed-use area that aims to achieve energy autonomy by 2028. In collaboration with the HET cooperative and stakeholders from the Vereniging Duurzame Werf (VDW), this research explores the optimal sizing and configuration of a multi-carrier energy hub integrating a fifth-generation district heating network (5GDHN), aquifer thermal energy storage (ATES), photovoltaic thermal (PVT) modules, battery energy storage systems (BESS), and additional photovoltaic (PV) generation.

A python based energy system model was converted to an MILP-based optimization model to minimize costs under a range of future grid connection scenarios, while meeting projected 2028 electrical and thermal demand profiles at a 15-minute resolution. The results of these scenarios are used to predict infrastructure capacity requirements for the future energy system.

The electrical and thermal demand patterns for 2028 were estimated and confirmed, accumulating to 1,244 MWh and 1,371 MWh respectively. The energy system is optimally sized for two connection categories; the AC5a connection category (535–630 kW) requires a relatively modest investment of €427k, while the SolarPark connection (300–350 kW) entails a significantly higher investment of €4.9M. However, this higher investment enables substantially greater energy autonomy for the area. The proposed load shifting technique does not improve the optimal cost solution for all possible connections, but the direct load control does. While parts of the existing electrical infrastructure can be reused, certain sections will need to be upgraded or replaced with higher-capacity components, depending on the selected grid connection size.

This study contributes a replicable framework for CDS-based energy hub design with an ATES in urban environments and demonstrates how energy hubs can at the same time reduce regional grid stress and contribute to the regional energy autonomy. This thesis enables sustainable urban redevelopment aligned with Dutch climate targets.

This thesis aimed to uncover the magnitude and effect of residential E-cooling demand on the Dutch energy market. Currently, little is known about the subject even though, due to rising temperatures and the increase in the amount of heat pumps, the amount and with that the effects of residential E-cooling demand is expected to rise sharply in the upcoming decades. First, the magnitude and patterns of residential E-cooling were uncovered by developing a thermodynamical model of the average Dutch residential houses. The effects of E-cooling were then tested by implementing the cooling demand in Pandapower and Plexos, testing the effects on local physical grids and on the overall power market respectively. The results showed a doubling of the cooling demand between 2025 and 2030 and a maximum annual cooling demand of approximately 0.4 TWh. The maximum cooling demand amounted to 2 TWh when alternative weather data was used reducing weather data limitations. In addition, it was shown how the demand for residential cooling has the potential to decrease local power quality when more than 40% of households actively cool their houses simultaneously, increasing network costs. Finally, it was also proven how power prices could increase due to higher demand and how revenue for certain generation components could double, or decrease by 20% in our grid during heat waves when accounting for residential E-cooling demand. This thesis provided among the first in-depth analysis of the magnitude and consequences of residential E-cooling demand on the Dutch energy market. It showed how cooling demand is expected to increase and what the consequences are of this increase.

The integration of renewable energy sources and heating electrification strategies in households is an unavoidable component of the energy transition. Unfortunately, the pace at which such integration occurs has proven challenging for the distribution system operators. On the one hand, system operators design low-voltage networks for low, unidirectional power flows at the connection points with the consumers, with expected lifetimes of several decades. On the other, the decreasing prices, together with the economic and environmental incentives to install (mainly) rooftop PV systems and heat pumps, create highly stochastic, bidirectional and potentially high-power power flows at the connection points of the former consumers, transforming them into prosumers. This thesis studies the misalignment between the interests of system operators and prosumers, proposing realistic alternatives that are achievable in the short term. This thesis hypothesizes that the aggregation of residential multi-carrier energy storage systems would be capable of bridging the interests between prosumers and distribution system operators. To validate the hypothesis, this thesis is comprised of five research topics.

Distribution system operators commonly address the grid congestion through infrastructure reinforcements, which is slow and expensive. Chapter 2 studies how energy storage systems with different carriers can provide a collaborative solution involving prosumers as ancillary services providers at the distribution level. Specifically for the European urban context, this chapter analyzed renewable energy sources, batteries, supercapacitors, hydrogen fuel cells, thermal energy storage, and electric vehicles through a thorough review of successful implementations. The correlations found between individual energy storage technologies and ancillary services provided insight into the flexibility opportunities each technology can provide to the grid. It was concluded that multi-carrier systems would provide the most robust yet flexible solution.

Based on the previous premise, Chapter 3 evaluated four multi-carrier energy system configurations for a Dutch household. The chapter also provides analytical models for every component (including the thermal losses from the thermal storage to the ground) and the space heating and electrical demands. The results suggest that using a heat pump combined with a photovoltaic system and a battery provides the best trade-off for the prosumer. The photovoltaic-thermal system alone could not supply the thermal demand required for comfortable space heating nor reach temperatures high enough to charge the thermal storage. Combining the thermal storage with the heat pump allows a certain degree of flexibility for the heat pump activation at the cost of COPs between 0.8 and 1.38 when used to charge the thermal storage, thus increasing energy consumption and equivalent emissions considerably.

Chapter 4 then elaborates on different energy management strategies to control the multi-carrier systems as proposed above. Two adaptable energy management system strategies were proposed for any system architecture with a reduced number of constraints. The first strategy uses genetic algorithms with a discrete-continuous approach for the power setpoints, maximizing thermal comfort and minimizing energy cost and CO2equivalent emissions. The EMS employs random forests for short-term predictions of the PV generation and electric and thermal demand. The results demonstrate that the strategy can solve the power allocation problem in the order of 1 s, including forecasting 60 minutes. This strategy, however, is too computationally demanding for complex distribution systems with multiple houses. Therefore, the second strategy uses a policy-based heuristic method to control the multi-carrier system, minimizing energy costs and maximizing thermal comfort. Also, this strategy allows the EMS to follow, or not, an external power setpoint from an aggregator, resulting in control decisions in the order of 30 ms. In addition, an ageing-aware EMS was briefly introduced, demonstrating the importance of ageing the BESS during operation.

Chapter 5 investigates, from a cost perspective, what conditions can make it attractive for individual prosumers to participate in a low-voltage ancillary service market, specifically power curtailment and peak shaving. For the former, it was shown that there are conditions where curtailing power does not significantly reduce the system's revenue but greatly reduces the peak power injected into the grid. However, it was also shown that curtailing might affect the power electronic components of the solar converter, potentially reducing its expected lifetime compared to a normal operation without curtailment. Similarly, an estimation of the degradation of the batteries for the cases with and without providing peak shaving was done using a semi-empirical ageing model, concluding that doing peak shaving to ensure a fixed power exchange with the grid will drastically reduce the life of the battery. Therefore, following an external setpoint to reduce occasional peaks would extend the battery's life. The results suggest that power curtailment and peak shaving can be attractive for prosumers, thus creating opportunities for ancillary services business models at the residential scale.

Chapter 6 incorporated households with single- and multi-carrier energy storage in a low-voltage distribution network to quantify the benefit of aggregation for the prosumers and system operators. The aggregator is generally assumed to have full observability and controllability of the assets, which is unrealistic in many cases. For this reason, this chapter considered separate controllers for the prosumers and the aggregator. Using a real 301-node low-voltage residential distribution network in the Netherlands, it was demonstrated that aggregated multi-carrier energy storage can ensure the voltage conditions established in EN50160 for penetrations of PV systems coupled with heat pumps up to 80 %. In contrast, aggregated single-carrier storage can reach 60 % and centralized storage only 40 %. Despite generating an economic benefit while supporting the grid, the high investment costs for both single- and multi-carrier storage result in unattractive conditions for prosumers compared to a case with only PV and heat pumps, requiring compensations for around half of the energy purchase costs for the single-carrier storage and higher than the total energy costs for the multi-carrier.

In summary, it was proved that, from a technical perspective, aggregated residential multi-carrier energy systems are a robust yet flexible solution for the voltage problems caused by the energy transition in residential low-voltage distribution networks. However, the current state of thermal storage makes the technology too expensive to be economically attractive.

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.

The rapid adoption of electric vehicles (EVs) poses significant challenges to low-voltage distribution grids, particularly in regions with high penetration rates like the Netherlands. As EVs increasingly draw power from and feed power back into the grid through technologies such as Vehicle-to-Grid (V2G) and mobile V2G, the stability and reliability of low-voltage grids are put to the test. This thesis investigates how uncoordinated charging behaviors, combined with real-world factors like commuting patterns, impact grid performance. The study focuses on key technical aspects such as grid congestion, voltage fluctuations, and transformer loading, aiming to understand the potential stress points in the grid.

Through a series of detailed simulations, the research explores different operational scenarios involving smart charging, V2G, and mobile V2G technologies. These simulations assess the grid’s response to varying levels of V2G penetration, seasonal demand shifts, and commuting behaviors, providing a realistic analysis of the challenges that low-voltage grids face. The study models suburban Dutch grids, emphasizing real-world conditions such as the asynchronous nature of charging and discharging patterns and how they can lead to localized imbalances.

This research reveals the complex interactions between EV integration and grid performance, emphasizing that user-driven charging behaviors and the growing penetration of V2G solutions can lead to significant grid instability without proper coordination. The findings highlight the necessity for advanced grid management strategies, infrastructure reinforcements, and innovative charging solutions to mitigate these risks. By offering insights into the technical challenges of grid integration under various real-world conditions, this thesis contributes to a deeper understanding of the infrastructure requirements and operational strategies needed to support the transition to electrified transportation on a large scale.

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).

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 Netherlands is currently undergoing an energy transition in an effort to decarbonize its electrical grid and build a more sustainable generation model. This transition is being led by the integration of non-controllable, sustainable generation sources such as wind and photovoltaic (PV) power. The Dutch wholesale energy market has an imbalance settlement period in which the TSO penalizes or rewards deviations from the last submitted trading program (based on whether the deviations aggravate or relieve the overall market imbalance), and therefore, non-controllable sources are at a higher risks of suffering undesired deviations. The consequences of this are twofold: on one hand, they impose a strain on the grid and an increased demand of ancillary services; and on the other, they risk the economic profitability of the plant.
This issue can be bridged by combining non-controllable generation sources with storage assets.

Although the the dispatch of non-controllable energy sources has been studied extensively, there is a research gap in the proposal of revenue-maximizing strategies for operating hybrid power plants (with wind and PV generation, and energy storage capabilities) in the Dutch wholesale energy market, that account for the stochastic nature of the weather resources and include financial contingency factors.
This thesis aims to bridge that gap by setting up an optimization-based dispatch, using Mixed Integer Linear Programming. The optimization was extended to a scenario-based stochastic optimization, and the Conditional Value at Risk was introduced to account for the intrinsic financial risk of the dispatch under random weather conditions. The resulting problem is a two-stage optimization which was solved using a modified Bender's cut. The intra-day optimizations were also adapted as rolling-horizon dispatches, permitting the operation with periodic updates to the weather forecasts.


The study case for this research was the SWITCH lab, a small-scale laboratory developed by TNO to conduct empirical research on the integration of renewable energies and storage into the grid. TNO also provided the basis for a non-optimized dispatch strategy based on price benchmarking, which was used to compare the performance of the optimized strategy.

The optimized dispatch proved to be an effective strategy for producing maximal-revenue trading programs on all market closings. The optimized revenue provided revenues between 85.8% and 260.1% higher than a generation-alone plant configuration; and an increase in revenue with respect to a generation-only baseline between 300.0% and 8962.9% compared to the non-optimized strategy. Operation under a hybrid configuration using the optmized dispatch also yielded the best economic outlook, having the highest 10-year Net Present Value projections, an average Internal Return on Investment 57.2% higher than the hybrid plant under a non-optimized scheme and a 47.5% lower payback time.

The optimized strategy provided the most profitable trading programs for both the case of deficit and surplus of generation at delivery, turning a positive revenue even under unfavourable market conditions. Conversely, the non-optimized dispatch had the lowest economic outlook of any configuration, with worse NPV, IRR, and payback times than the generation-only plant.

These results highlight the importance of developing dispatch strategies that consider the long-term behaviour of generation and prices, as opposed to here-and-now strategies whose performance was shown to be comparatively deficient; and the synergy between storage and renewable generation sources to bridge the non-controllability problem.

This thesis focuses on analysing, troubleshooting and testing a USB-C to AC Inverter with USB-C power delivery, as well as implementing control- and protection systems for the flyback converter and implementing the H-Bridge switching control. The starting point of this project is a design that has already been manufactured as a PCB by DC Opportunities. A description of the existing design will be given, complemented with the implementation of the control and protection systems. Furthermore, an overview of the testing process will be portrayed and the results will be presented and interpreted. The USB-C input will use the power delivery protocol and a Flyback converter to get to 400V DC, followed by a full-bridge inverter for a 230Vrms AC output.

The inverter is part of a rural electrification project in which the goal is to provide electricity to people in rural, unelectrified areas. Initially, electricity is to be provided in the form of a charging station at a central kiosk or shop where appliances such as phones can be charged. Gradually, people can climb up the electrification ladder by purchasing power banks that can be charged at the charging station to provide the user with electricity in their home. Eventually, people will move further up the electrification ladder all the way to local generation via solar panels with battery storage at home. When enough people have local generation, a DC micro-grid can be constructed. The USB-C to AC inverter is there to give people the possibility to use AC powered appliances while the number of available DC powered appliances is limited. This gives people more options, while still keeping the advantages of a DC power system

In rural areas, a stable electricity supply is in 2022 still not a certainty. To provide these areas with constant power, components to create a DC micro-grid are developed. This paper discusses the possibilities to create insight into the performance, the power which is drawn, and the productivity of the components. These parameters are fundamental for the users, operators, and developers. For offline data logging, the software is written for a micro-controller to log relevant data to a microSD card. The microcontroller is programmed in C, and the communication between the controller and the micro-SD card will be taken care of by the SPI protocol. The control of the file system is realized with FatFS, saving comma separate value files (.csv) containing all the desired data. For real-time insight and easy control of the device, an app framework is developed. This framework makes use of MQTT, Flutter, and Dart, to create a user-friendly and structured environment. The bi-directional communication between the app and the controller is done with the use of a wifi module, which communicates with the microcontroller via UART. The paper stands out with the integration of multiple controllers, program languages, communication protocols, and physical components.

The rapidly growing number of renewable energy technologies has started changing the infrastructure of the conventional energy sector, which was based on one-directional power flow. Bidirectional flows are created in the network with the integration of renewable technologies. The electricity network and system operators face many new challenges created due to renewable energy sources. Renewable energy sources are characterized by an intermittent and stochastic character which affects the power production from renewable energy technologies. Thus, the produced energy may pose challenges to the grid when it is higher than demand since the excess power is injected into the grid and it causes overvoltage problems.
BESS can contribute in facing the problems created by renewable energy technologies. They offer environmental benefits, they contribute to the integration of renewable technologies and they enhance grid’s reliability. These factors have as a result an increase in the integration of batteries in the electricity network. This research has as a goal to develop a control and coordination method for multiple BESS in a low voltage distribution network in order to address overvoltage and undervoltage issues caused by high penetration of PV units. There are many control strategies used in order to control the increasing number of batteries so that normal operation of the energy system is sustained. The main control strategies are centralized control, decentralized control and distributed control.
In this thesis study, a coordination control strategy of multiple BESS was developed to address the network's voltage violation issues caused by the high penetration of PV units. The coordination control strategy is based on a consensus algorithm that determines each battery's contribution to the network. The goal of this control strategy is to maintain the voltage within the limits. When a battery is not available due to a state of charge limit violation or maintenance, the amount of power that this battery would contribute under normal operation is distributed equally from the neighboring batteries until the battery becomes available again. This control strategy is a combination of distributed control, as it entails communication between neighboring batteries which share information together, and local control. The developed coordination control strategy is compared to a decentralized control strategy, which is widely used in distribution networks in order to control the contribution of batteries. Moreover, one of the batteries is emulated in the laboratory in order to examine the behavior and contribution of the battery, with the coordination control strategy implemented, in real-time application in comparison to the simulation.
The findings of this thesis study contribute to the research of mitigating voltage limit violations caused by renewable energy technologies by demonstrating the effectiveness and benefits of the proposed control and by providing a comparison of the proposed control to a decentralized control strategy, commonly used in distribution networks for controlling the contribution of BESS, for voltage regulation. Furthermore, the laboratory results contribute in the potential implementation of the proposed control in real distribution networks.

To enable affordable and environmentally friendly eletrical energy storage, a battery was designed using sea-water as electrolyte. The performance of this battery was tested through repeated cycling under a variety of circumstances. The Coulombic and energetic efficiency were around 80% and 68% respectively. The battery saw a strong drop in performance after ~60 cycles. This was corroborated with results gained from four separate cells. Efforts to model the battery were limited by the accuracy of the utilized model itself.

The construction of reinforcements of the electricity grid cannot keep up with the increasing demand for transport capacity caused by the energy transition. This leads to increasing congestion of the grid. Therefore, the feasibility of battery energy storage systems as a solution is researched in this thesis. To make this a financially viable option, the free capacity of the battery energy storage systems is used to participate in the FCR and passive balancing market. Four (mixed integer) linear programming models are proposed to optimise the battery sizing and market participation. The feasibility of the solution is investigated through three case studies, which are based on three nodes of the distribution grid where structural congestion is expected. The study shows that for two of the three case studies a profitable business case can be theoretically accomplished.

The majority of Dutch homes currently use natural gas boilers to meet their space heating demand. Changes in this significantly large sector are required to achieve the sustainability goals established by the Paris Agreement. Since most renewable energy sources produce electricity, transitioning residential heating systems might cause problems managing national electricity grids. Furthermore, the intermittent nature of renewable energy sources leads to an imbalance between supply and demand.

These challenges can be overcome by combining different storage techniques. An example of such a technique is the thermal energy buffer developed by Borg, which focuses on single-household use. This thesis looks into the feasibility of such a system by comparing different scenarios for residential heating systems.

Three scenarios were modelled using Simscape. In scenario I, a natural gas boiler provided all the heating demand of the house. In scenario II, the heating system consisted of Photovoltaic Thermal (PVT) panels and the thermal energy buffer. In scenario III, the house was heated by PVT panels, the thermal energy buffer, and a heat pump. In all scenarios, the same house was connected to the heating system.

In scenario II, the system sizes were 0, 1, 2, and 3 PVT panels, combined with buffer capacities of 0, 2, 4, and 6 m3. In scenario III, the system sizes were: 3 PVT panels with 6 m3 buffer capacity, 1 PVT panel with 4 m3 buffer capacity, and 3 PVT panels with 2 m3 buffer capacity.

The total yearly heat consumption of the modelled house was 5109 kWh. In scenario I, 378 kg of CO2 was emitted. In scenario II, CO\textsubscript{2} emissions were highly dependent on the sizing of the PVT system and the TESS and ranged from 20 to 405 kg, based on a heating demand of 9444 kWh.

Scenarios I and III maintained a comfortable temperature during the entire year. The heating system of scenario II was insufficient to heat the house throughout the year for all modelled system sizes; however, the scenario could be acceptable with larger PVT and TESS sizing. By comparing CO2 emissions and payback time, the optimal capacity of the thermal energy buffer was found to be 6 m3.

The uncertainty of the future gas price causes a challenge in comparing the cost of electrified heating systems to traditional heating systems. Additionally, it underlines the necessity of decarbonizing residential heating systems to secure comfortable, affordable housing.