Achieving carbon-neutral energy systems in industrial clusters necessitates fundamental restructuring of existing energy systems. This transition is accompanied by several significant challenges. In pursuit of carbon neutrality, there is an increasing demand for industrial electrification, as well as a rising demand for green electricity and sustainable energy carriers, such as hydrogen and ammonia. The integration of variable renewable energy sources (VRES) is critical to address the growing demand for clean energy and enable the critical shift away from fossil fuel dependence. However, the intermittent nature of VRES, in combination with grid congestion issues, poses a challenge to the reliability of energy supply, a crucial element in fostering an attractive investment climate. Moreover, the development of new energy infrastructure is constrained by several factors, including limited access to new grid connections, investment uncertainty, and spatial limitations. Conventional energy planning and operation approaches, which treat energy sectors in isolation, are unable to address these complex, system-wide challenges. These approaches limit the ability to optimize across various energy sectors and fail to harness the potential synergies between energy carriers. Conversely, a more flexible and integrated approach provided by multi-energy systems (MESs) has been shown to effectively mitigate VRES intermittency, alleviate grid congestion through alternative energy pathways, and enhance cross-sector synergies and infrastructure utilization. However, the realization of these benefits necessitates a deeper understanding of the operation and organization of such systems.

To provide these insights, this research develops a model-based optimization approach for the cost-effective operation of MESs. The modeled system represents a synthetic, future-oriented energy system for an industrial cluster, drawing inspiration from the Maasvlakte area in the Port of Rotterdam. The research introduces a new operation strategy to support the transition towards a carbon neutrality, addressing key barriers currently limiting the decarbonization of industrial clusters.

A detailed conceptual model for the synthetic MES was developed to reflect the existing infrastructure of the Maasvlakte area, planned projects, and potential future developments. This conceptual model was translated into an operational optimization model implemented in Python using the PyPSA toolbox. The MES integrates five energy carriers—electricity, natural gas, hydrogen, ammonia, and heat—within a unified model through the energy hub approach that facilitates sector coupling, conversion, and storage within multi-energy carrier networks. The electricity system is modeled with physic-based power flow constraints to capture technical feasibility in the power system, and the non-electrical carrier networks are modeled using the energy hub approach. The entire system is optimized through a single-objective cost minimization, with mixed-integer linear programming, using hourly resolution over a one-year horizon. To test the system's performance under varying renewable energy supply, three weather-dependent scenarios were formulated and optimized, reflecting variability in wind and solar conditions and its implications for system operation.

Based on the system’s optimal performance across all scenarios, this research proposes a new operation strategy that enables flexible and cost-effective operation of a multi-energy industrial cluster, representing a paradigm shift from conventional approaches. Instead of relying on static, price-driven, and siloed sectoral operation, the proposed strategy emphasizes cross-sector economic optimization, dynamic dispatch response to system states, enhanced system flexibility through integrated conversion and storage technologies, and continuous energy supply to industrial consumers.

Key outcomes include the development of an operation strategy that minimizes costs while ensuring energy supply to industrial consumers and technical feasibility, the identification of ammonia as key flexibility provider, and actionable insights into flexibility management, the role of conversion technologies, and infrastructure planning. The results have important implications for decarbonization pathway of industrial clusters, offering a cost-effective and actionable approach to integrated energy system operation.

The increased digitalization of the power grid and transition to cyber-physical power systems raise serious concerns about cyber security and secure operation of the power system. It is now well recognized that information and communication technologies are vulnerable to cyber attacks. Thereby, electrical power grids as critical infrastructures are susceptible to cyber attacks as well. Malicious cyber attacks on power grid infrastructure can detrimentally affect power system operation and stability. In the worst-case, it can trigger cascading failures across the system, leading to a blackout. A coordinated cyber attack across multiple locations can collapse the entire interconnected power grids of nations, or even continents. This is a real modern-day threat, as seen during the cyber attacks on the Ukrainian power grid in 2015, 2016, and 2022. Therefore, power grid resilience and cyber security are now recognized challenges for power system operation and security of electricity supply. The gist of this entire thesis can be summarized as follows.

“Analyze and demonstrate how cyber attacks on power grids may cause and accelerate cascading failures. Based on this analysis, develop suitable proactive defense measures to contain the spread of cascading failures.” Consequently, the core research focus of the thesis with a threefold objective is as follows:

Cyber security of digital substations 

This thesis investigated the impact of cyber threats targeting digital substations. Experiments demonstrate the catastrophic impact of spoofing and replay attacks targeting OT protocols and standards used in digital substations, leading to relay denial-of-service and malfunction. Subsequently, it is experimentally shown how these events may snowball resulting in cascading failures and blackouts. Based on this analysis, this thesis developed mitigation measures based on IEC 62351-6 using HMAC to secure critical control communications in digital substations, adherent to latency requirements of 4ms. The aforementioned studies are conducted using a hardware-in-the-loop cyber-physical experimental framework that closely resembles real-world conditions within a digital substation, including intelligent electronic devices and protection schemes. Thus, the outcomes of this research are of particular importance to both, vendors and utilities.

Dynamical analysis of power system cascading failures caused by cyber attacks

This thesis proposed a data-driven method for dynamical analysis of power system cascading failures caused by cyberattacks. It provides experimental proof on how cyber attacks may accelerate the cascading failure mechanism, in comparison to historically observed blackouts. Using a dynamic power grid model, consisting of multiple, coordinated protection schemes,  the point of no return is defined and analysed in a cascading failure sequence by applying the Hilbert–Huang transform for time-frequency analysis. Numerical results indicate, cyber attacks may accelerate cascading failures at least by a factor of 3x. This is due to the excitation and non-damping of multiple frequency modes greater than 1 Hz in a short time span. This thesis demonstrates semi-analytically how cyber attacks can cause and accelerate power system cascading failures, thereby leading to a quicker point of no return.

Defense against cyber attack induced cascading failures

Cyber-physical power systems are vulnerable to cyber attacks that may lead to cascading failures and power outages. A promising solution to tackle this emerging issue is the concept of preventive/proactive controlled islanding before the cyber event occurs based on early detection of cyber attacks. Hence, this thesis developed a novel physics-informed graph convolution network to perform preventive controlled islanding. By incorporating power system physics into the neural network loss function formulations, the resulting islands were made self-sufficient and voltage and frequency stable. Experimental simulations using a modified version of the IEEE 39-bus test system with coordinated protection schemes prove that the islands formed using the proposed method can contain the spread of cascading failures. This results in minimization of loss of load by up to 90\% and 62% when single and multiple substations are compromised, respectively. Hence, this work paves the way towards automated cyber-resilience for power systems and provides system operators with decision making recommendations to curtail the spread of cascading failures. 

This thesis addressed the increasingly crucial topic of cyber security for power systems. It provides a comprehensive analysis of how cyber attacks may trigger and accelerate cascading failures in power grids, potentially leading to large-scale power outages. Furthermore, this research enhances our understanding of power grid cyber resilience by experimentally demonstrating the vulnerabilities of digital substations, proposing a novel data-driven method for analysing cyber-induced cascading failures, and developing an advanced physics-informed graph convolutional network for preventive controlled islanding. The findings of this thesis are highly relevant to utilities and vendors, as they offer practical insights into the pitfalls associated with power system digitalization and possible adverse consequences. Thereby, the proposed cascading failure analysis technique and preventive islanding defense strategy directly contribute towards enhancing the cyber security of power systems and ensuring better preparedness in the face of the ever-growing cyber threat landscape. Ultimately, this research contributes   to a more cyber secure and resilient power system.

Industrial electrification has a crucial role to play in reducing carbon dioxide emissions, and ensuring power reliability is an important factor in this process. Therefore, this thesis explores cost-effective storage to ensure the reliable operation of the renewable energy-based power supply of a 500 MW electrified industrial load in the 2035 Botlek area in the Rotterdam harbour. The study focuses on integrating electrical storage solutions to mitigate external power system risks that threaten reliability.

The research identifies key external risks to be energy shortages, power outages, frequency fluctuations and voltage instability. After a comprehensive review of current and emerging storage technologies, three storage mitigation strategies are formulated based on financial, technical, practical and other aspects. A synthetic industrial model consisting of generic component representations in DIgSILENT PowerFactory 2024 SP1 based on an electrified version of the Shell Pernis refinery is used. It is adapted to represent the Botlek 2035 study case, the storage assets are integrated and inputs are defined to represent on-site wind power generation and connection to the external future Dutch power system. 20% of peak demand is assumed to be flexible based on the residual load in the Dutch power system in 2035.
Via a dispatch simulation, the performance of each strategy is assessed. The loss of load expectation and expected energy not supplied are used as reliability metrics. The costs of plant interruption, storage system costs and electricity costs are used to select a strategy. Results are subjected to several input and parametric sensitivities.

Results indicate the combination of a Lithium iron phosphate battery, an alkaline electrolyser, magnesium hydride storage and a hydrogen turbine can ensure reliable operation most cost-effectively. Hydride storage is identified as a technology with much potential for industrial integration due to the advantages of waste heat utilization for hydride dehydrogenation. Extreme weather scenarios are advised to be covered with externally sourced fuel instead of on-site storage reserves. A 10.5 GWh or 315 tonne hydrogen storage system is expected to be required for reliable operation in the Dutch power system, when 20% of peak demand is modelled as flexible. This configuration yields to an average levelized cost of energy of 45.3 €/MWh during the year compared to 45.7 €/MWh without storage while also ensuring reliable operation without significant interruption costs.
This thesis provides insight into the integration of storage assets in electrified industrial networks in the context of the future Dutch energy system and lays a foundation for further research.

This research aims to tackle the dual challenges of power electronic uncertainties and the intermittency of renewable energy sources by developing a comprehensive reliability model and conducting a probabilistic evaluation of VSC-MTDC-based hybrid AC/DC power systems. With a specific focus on the North Sea region, the study emphasises enhancing the reliability of these systems, which are increasingly utilised for the efficient transmission of offshore wind power. The objective is to optimise key factors such as redundancy, modularity, and maintenance costs, which are crucial for the reliable integration of these systems into existing power grids.

While Modular Multilevel Converters (MMCs) within these systems offer multiple advantages, the proliferation of power electronic components introduces substantial uncertainties, compounding reliability concerns alongside the inherent variability of renewable energy sources. To address these challenges, the proposed composite probabilistic models account for wind speed variability, turbine drivetrain reliability, and the stochastic behaviour of component failures, providing a detailed reliability model.

The findings highlight substantial opportunities for improving system performance through targeted design and maintenance strategies. By investigating the reliability of offshore wind power, MMCs, DC transmission system and the overall AC/DC system, this research provides valuable insights into optimising system performance and ensuring the efficient integration of renewable energy. The research outcomes include a composite (generation and transmission) model, reliability and cost assessment, an optimal cost-reliability strategy for MMC systems, and a constant risk-minimised cost method of substituting conventional generators with offshore wind power contributing to more resilient and cost-effective renewable energy integration.

The outcomes of this study provide crucial insights into enhancing methods for the reliability of hybrid AC/DC systems. The methodologies and results not only align with global sustainability goals but also bolster energy security by laying a strong foundation for future power grid designs that increasingly depend on sustainable energy sources and advanced power electronics.

\textbf{Keywords:} Adequacy, composite power system, multi-state model, offshore wind power, power electronics, reliability evaluation, VSC-MTDC

This thesis creates open-source Python scripts for conducting generation adequacy analysis studies. First, scripts without wind considerations are constructed, and then the scripts have been modified to include wind considerations. Generation and load models have been implemented to obtain the reliability (adequacy) indices Loss of Load Expectation (LOLE) and Expected Energy Not Served (EENS). Two probabilistic methods have been implemented: an analytical method and a non-sequential Monte Carlo Simulation (MCS) method. Both methods use the IEEE load curve for their load model, but different generation models are used. The analytical model uses a recursive algorithm, where generation units are added one by one to obtain a Capacity Outage Probability Table (COPT). The non-sequential MCS method uses state sampling, where a uniform random number is generated for each hourly increment and a state is selected based on the state probabilities of a generator. Wind considerations have been added to the scripts by modelling the power output curve of a wind turbine.

The proposed scripts have been tested on two test systems - the Roy Billinton Test System and the IEEE Reliability Test System. The resulting reliability metrics have been compared with benchmark values in the literature and found to be closely matching. Furthermore, methodological clarity on how to obtain the presented scripts is given. Even though all elements of the implemented methods are present in the literature, not all are clearly explained or combined in one place. This work aims to overcome this limitation.

The need for energy transition entails clear expectations of a significant increase in Variable Renewable Energy Sources (VRES) . However, increased renewable supply introduces challenges due to the integration of Inverter Based Generators (IBG), which can be effectively managed with control modules, such as Exciters.
To ensure power system stability and reliability amid significant advancements, an in-depth understanding of the dynamic behavior of the Dutch Transmission System is essential. This Master’s Thesis project aims to investigate the response of the Dutch power system to high penetration of Renewable Energy Sources (RES), with a primary focus on dynamic stability performance. By studying these dynamics, we can better understand and address the challenges posed by the increasing integration of RES.
The Thesis proposes a Synthetic Digital Model of the Dutch Power System in which the generator components are equipped with dynamic models that perform various control functions, to simulate the system’s response to any changes. DIgSILENT PowerFactory is a power system analysis software, used to develop this model and to perform various simulations. Dynamic Stability studies evaluates a power system’s ability to maintain stability under various operating conditions and disturbances. Following a disturbance, the controllers of the elements de- termine the dynamic response of the transmission system. While stability is determined by multiple factors, such as the type of a disturbance and its duration, the number of sources in the power system and the power system operating condition (pre-disturbance), controller settings ultimately determine how quickly and effectively a sys- tem can respond to disturbances. They help to maintain stability and preventing faults from escalating. Therefore, the design and calibration of these control modules are primarily focused to address the stability challenges and indirectly facilitate smooth integration of VRES.
A case study involving operating under specific conditions of current and future generator dispatches is per- formed to investigate the impact of change in type of generation, in various scenarios. Successful initialisation of the dynamic models is achieved after multiple parameter tuning and model calibrations. The most basic form of stability assessment is the observation of time response of a specific variable in the model. Thanks to these Dynamic models, the time response of variables like frequency, voltage and rotor angle is observed to be within acceptable limits. However, there are cases in which the model becomes unstable, which are assessed for opti- mization. Critical disturbances during which the responses are uncontrollably divergent (from original operating point) are identified and recommendations are made at the power system level to effectively beware these faults.
Finally, Voltage Stability Performance is comparatively performed to reflect on the stability performance under low and high predominance of renewable power generation. This evaluates a certain variable under specific operating conditions and checks whether the variable is within acceptable limits. While introducing a fault at each system component, these variables are calculated to recognise all the vulnerable areas of the model. Based on the number of unstable components in the results obtained, recommendations are made on how to decrease this number.

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.

The transportation sector continues decarbonizing with the increasing number of Electric Vehicles (EVs) replacing gasoline and diesel cars every year. However, the integration of vast amounts of EVs introduces complexities in energy distribution and grid stability. Charge Point Operators (CPOs), positioned at the intersection of EVs and the grid, play a critical role in managing these complexities. They ensure that the charging infrastructure meets the needs of both EV users and the grid, highlighting the importance of smart charging strategies.

In this thesis, a smart charging approach is proposed from the point of view of a CPO. The proposed approach aims to optimize the charging schedules for EVs parked at a commercial building's parking lot. The objective of the optimization problem is to minimize the Power Setpoint Tracking (PST) error, which indicates the error between the contracted energy in the day-ahead market by the CPO and the aggregated consumption of charging stations the next day. This optimization involves complex sequential decision-making, where the uncertain nature of EV arrivals and departures demands a fast and adaptive solution. Thus, this thesis proposes a Markov Decision Process (MDP) formulation and solves it using the Deep Deterministic Policy Gradient (DDPG) algorithm to minimize the PST error by scheduling the charging of EVs. DDPG is chosen for its ability to efficiently handle complex problems with continuous state and action spaces, making it ideal, considering the uncertainties inherent to the arrival of EVs and the charging process. Additionally, DDPG's application in a commercial building's parking lot, where EV arrival and departure patterns are usually consistent, further solidifies DDPG as a strong alternative.

Evaluating the proposed DDPG approach with alternative benchmarks, such as the uncontrolled "charge as fast as possible" (CAFAP) and the optimal solution obtained through a Mixed Integer Non-Linear Programming (MINLP) formulation, signifies DDPG's superior performance in several metrics. Specifically, it outperforms the CAFAP algorithm by achieving a reduction in PST error by an average of 34% for a parking lot with 10 chargers over 12 hours of charging for a day. This highlights DDPG's efficacy in optimizing EV charging schedules over the CAFAP algorithm. Moreover, DDPG's model benefits from the ability to be trained offline with historical data and deployed online once trained. This approach allows for rapid, dynamic rescheduling of charging in real-world operations, offering speed advantages over the theoretically optimal solution, which requires prior knowledge of arrival and departure times and State of Charge (SoC) of EVs. All experiments validating these findings were conducted within the EV2Gym, a Gym environment specifically designed to simulate the EV charging scenarios.

Lastly, this thesis contributes to the field by demonstrating how RL, through the use of DDPG, can optimize PST for EV charging in a commercial building's parking lot. By offering a detailed comparison with other algorithms and showcasing the scalability and adaptability of DDPG, the research provides valuable insights for CPOs and stakeholders in the energy sector.

Decarbonizing industrial processes by transitioning to carbon-neutral energy sources poses significant challenges for industrial operations. The integration of technologies such as Power-To-Heat (PtH) with electric boilers and furnaces, Power-To-Gas (PtG) facilities employing electrolyzers, variable speed drives for energy-intensive machinery, and the increased use of renewable energy sources like wind and solar power plants are reshaping the grid and industrial landscape. This transformation adds complexity and risks, making it a significant endeavor to address emissions from daily operations while maintaining operational security. The industrial sector is crucial in achieving future greenhouse gas (GHG) emissions reduction targets. In Rotterdam's Pernis-Botlek area, where fossil gas accounts for 55\% of the 130 PJ/yr average energy consumption for operational needs, the magnitude of this challenge is evident.

This master's thesis explores the dynamic security of highly electrified industrial hubs integrating Power-To-X conversion facilities through model and simulation-based analysis. The research focuses on developing an industrial site network that integrates individual electric loads while anticipating challenges from the evolving electrical grid. Utilizing DIgSILENT PowerFactory, the study simulates operational scenarios and network disturbances to evaluate the impact of these technological changes. Additionally, the thesis proposes mitigation strategies and operational enhancements to ensure continuous and efficient operations.

The developed model aims to provide a versatile and adaptable representation of industrial sites, drawing on existing literature and reflecting the static and dynamic performance of real power systems within the industrial sector. Through numerical simulations and the analysis of performance metrics, critical issues arising from disturbances are identified and examined to find possible solutions.

The electrical power system is a critical infrastructure that provides a reliable energy supply for daily businesses. Designing resilient and reliable power grids is of paramount importance to prevent blackouts and their adverse economic impact on society.

Resiliency is fundamentally defined as the ability of a system to respond to high-impact disturbances with a low-probability of occurrence. Evaluating resiliency in power systems is usually done in three stages. The first phase is the disturbance progress. During the first phase, the resilience level deviates from its pre-disturbance level. This can be observed by analyzing different metrics in the network. Secondly, in the case of effective primary control actions, a new steady state operating condition is reached, which differs from the pre-disturbance operating condition. Finally, the system reaches the restorative stage. The recovery starts and the system returns to normal operation.

The assessment of resiliency is a combination of assessing all three previously mentioned stages (during-disturbance, post-disturbance, and restorative). Depending on the focus of the study, different technical aspects of a system are assessed. This thesis focuses on the assessment of the during-disturbance phase because, in future grids with lesser reserves available and limited control capabilities, the initial response of the system following a disturbance becomes more critical.

This thesis presents a basic qualitative study of the dynamic performance due to an active power imbalance during a disturbance on the AC and DC sides of hybrid power systems with an emphasis on an MTDC interconnected offshore-onshore system. The widely used RoCoF (Rate of Change of Frequency) is adopted as a performance metric to assess the active power-frequency response from the perspective of the AC side. In addition, a modified quantification of the Rate of Change of Voltage (RoCoV), which is usually applied in the design of protection schemes, is suggested as an attempt to better capture the response of the DC voltage.

The suitability of these metrics to properly reflect the resulting dynamics is analyzed by considering different disturbances, such as generator outages, line outages, converter outages, and faults like line-to-line and line-to-ground short-circuits, at either the AC or the DC sides. The different disturbances are executed using real-time digital simulations on the EMT model of the CIGRE BM1 DC-AC test system in RSCAD\textsuperscript{\textregistered} FX. The performance metrics are well able to capture the impact of different disturbances on the response of the system. However, the performance metrics are not able to capture oscillating responses.

A study on the parametric sensitivity of the control parameters in the outer control loop of the converters is executed to see the influence of these parameters on the dynamic response and whether the performance metrics are able to capture the influence. The parameters of the outer control loop determine the reference currents for the converter, and thus directly influence the output of the converters. The results show that, for a DC line-to-line short-circuit, the adjustment of the control parameters in the outer control loop has no influence on the response of the DC voltage. For each control setting, the DC voltage still immediately drops to 0. This is also reflected in the performance metrics.

Whereas, adjusting the control parameters in the outer control loop influences the DC voltage response when subjected to an AC 3-lines-to-ground short-circuit. The proportional gains of the controllers mainly influence the overshoot of the DC voltage and have a small influence on the settling time. This corresponds to the role of the proportional gain in PI control, to respond quickly to faults. On the other hand, the integral gain responds slower and integrates the error over time to eliminate the residual error. Therefore, the results show that the integral gain mainly has an impact on the settling time of the response, and almost none on the overshoot. This is not captured by the calculated performance metrics. The performance metrics capture the response after the initial overshoot and this results in an unfair comparison between performance metrics.

his thesis aims to investigate the change in frequency performance of the Nordic Power System in 2030 caused by the replacement of synchronous generation by NSG. To do this, the Nordic Power System is modeled in the simulation software DIgSILENT PowerFactory 2022 SP1 for modeling and simulation. For the Nordic Power system, periods of low demand and high penetration of wind-generated power and HVDC import are expected to have the lowest amount of inertia. An operational scenario of 60% NSG is therefore developed.

Climate agreement goals set by the Dutch government increase the urge to reduce our greenhouse gases. To fulfil these goals on a residential level a reduction of the emission of carbon which is produced during household demand and transportation (commute) is required. On a residential level, the amount of photovoltaic systems (PV) and electric vehicles (EV) is increasing rapidly to meet these requirements. All these individual changes in the low voltage (LV) grid will have an impact on the aggregated load profile in the medium voltage (MV) network.
The MV network consists of underground cable connections, which play a vital role in the transmission and distribution of electrical power. Currently, the distribution network operator (DNO) uses a fixed ampacity which is based on fixed site conditions to rate their MV cables. The current methodology only considers the current peak of the load profile, but the ampacity of a cable connection is governed by its temperature.
Ampacity ratings for MV cables are specified for a continuous load applied on the specific underground MV cable in certain ambient conditions. When a cyclic load profile is applied the temperature of the cable will not remain constant over a 24 hour load cycle. Since this introduces moments of lesser loading the underground cable has moments during its load cycle to be able to cool down. If this method is applied the whole load profile which is applied on the MV cable could be raised by a factor so that the peak of the profile safely exceeds the nominal ampacity, but stay within the specified thermal limits.
The area in which the DNO operates is quite expansive, the material surrounding the underground MV cable connection will differ for each area. There is a big uncertainty in terms of ground conditions for the majority of the MV cables. The effect that this has on the ampacity of the cable connection will be examined. By running multiple simulations with different ambient conditions, the impact that this uncertainty has on the ampacity can be concluded.
The simulations will be done with an analytical- and a finite element model (FEM). With these models, the effects of uncertain ground conditions and the possibility to use an cyclic rating factor for specific load profiles can be calculated. This will be used to study the impact of the changing cyclic load profile due to the increase of PV and EV in the network. The interplay between these factors is interesting since the uncertain ground conditions have a negative impact on the overall ampacity while the cyclic rating factor can (partly) compensate for this loss.

Wind energy is a growing energy resource in the current energy transition. Massive new amounts are planned to be built in the face of the climate and energy crisis. The current state-of-the-art type-4 Wind Turbines (WT) uses a Fully Rated Converter (FRC) to decouple the rotor speed from the grid frequency. In recent years this type of WT has been involved in so-called sub-synchronous events. The Grid Side Converter (GSC) of the FRC is very similar to other Inverter Based Generation (IBG) such as: Photovoltaics (PV), Battery Energy Storage Systems (BESS) and HVDC-links. As this research is focused on the GSC, it is very relevant to the integration of other Renewable Energy Resources (RES) as well.
This thesis investigates Sub-Synchronous Control Interaction (SSCI), a relatively new phenomenon. The GSC interacts with the grid, which can cause a Sub-Synchronous Oscillation SSO, an oscillation below the system's fundamental frequency. This oscillation can lead to damage, increased components wear or triggering protection systems. After different facets of SSCI are discussed, a new solution is put forward in this thesis. By feeding wide area Phasor Measurement Unit (PMU)-based measurements into the control system of the WT, an algorithm is constructed to mitigate SSCI. This algorithm is tested on the ability to mitigate sub-synchronous event risks.

First, a WT model is selected in the DIgSILENT PowerFactory software to recreate sub-synchronous behaviour. This model is tested in the weak radial grid. The influence of the different control parameters on the sub-synchronous behaviour is investigated and comped to literature studies. Different tools are used for this research. PowerFactory is used for small signal analysis to obtain a linear dynamic model of the system. RMS-time simulations are used to test the oscillatory behaviour of the system. These results are further analysed using eigen-analysis on the linear model and Fourier and Prony analysis on the time simulations.
Then, the same WT-model is implemented in a modified IEEE-39 bus system to see the behaviour of SSO propagation in a transmission network. The results are compared to an analytical method to determine voltage oscillations based on mode shapes. However, as SSCI has a fundamentally different driving force, this method is not valid in this case. In the same transmission network, the influence of grid operations is tested. Different variations are tested: the connection point, power output of the WT, grid loading and disconnection of nearby connections. As all these features can vary during normal operation, it is vital to understand better which circumstances increase the risk of SSO event.

At last, using the knowledge obtained, a new control algorithm is proposed. This algorithm uses wide-area voltage angle measurements. These measurements can be provided by PMUs. A remote signal is fed into the control system. Minimal modifications are made to the control system for this. Additional damping is performed on the local voltage reference angle depending on the movement of the remote signal. This prevents the initialisation of SSCI. This implementation of a WAMC is tested using eigen-analysis and time simulations and shows promising results.

The results of this thesis research are also modelled in the NextGen GridOps Framework of DNV. The framework aims to stimulate a fast deployment of the finding of this thesis research in the field. This is accomplished by sharing knowledge in an accessible, structured environment. This allows taking the findings into consideration for solving the complex problems encountered by transmission and distribution system operators.

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.

Given the urgency to shift to a cleaner energy mix, offshore wind energy is bound to be quickly deployed on a large scale in the next years. In order to meet the Paris Agreement, the current role-out rate of wind energy in the North Sea, that is 2 GW/year, needs to be increased to an average value of 7 GW/year over the period 2023-2040. This rapid increase of the share of uncontrollable, renewable sources in the energy mix raises a certain number of challenges, among which sustaining energy balance and transient stability. To organise the large-scale deployment of offshore wind in a strategic manner, the concept of hub-and-spoke has been introduced. It envisages modular offshore renewable power generation clusters (a.k.a. offshore hubs) designed to be easily and safely operated and interconnected.

Dealing with large power fluctuations constitutes a major challenge for each offshore hub. The variability of power supply needs to be mitigated through the integration of storage solutions. Offshore power-to-gas conversion for storage purposes has been widely investigated in the literature, under techno-economic or power balance points of view. However, detailed analysis of the effective connection of large scale electrolysers in offshore hubs are missing.

This thesis proposes a real-time simulation model of a 2 GW offshore hub integrating electrolysers in order to investigate their impact on the dynamic active power management of the hub. Two locations for the connection of the large-size electrolysers are studied: i) connection of an electrolyser to the AC common bus of the hub and ii) connection of electrolysers to the DC link of the back-to-back converter of each Type-4 wind turbine of the hub. An Electromagnetic Transient (EMT) simulation based analysis, necessary to capture the fast dynamics of the zero-inertia hub, is performed under different severe disturbances, such as a three phase fault and sudden large wind speed fluctuations.

In a second part, the thesis investigates the connection of the hub to the shore via a bipolar High-Voltage Direct Current (HVDC) link. It has been shown in the literature that bipolar links are more reliable than monopolar ones, as they can still be operated to transfer half of their nominal capacity in case of failure of one cable or converter. The work of this thesis is focused on developing and implementing a power sharing strategy between the two Modular Multi-level Converters (MMCs) constituting the offshore terminal of the link.

It was found in this thesis that both investigated locations for the connection of the electrolysers can be beneficial in different ways. Connected at the AC common bus, the electrolyser can provide centralized ancillary services, while an electrolyser connected locally at the wind turbine can consume the power generated during an islanding event. Regarding the power sharing in the HVDC link, two different strategies were developed, both enabling to unload one of the poles of the link. Further studies should be carried out to provide in-depth understanding of the potentialities of the two methods.

Royal IHC is known for building large dredging vessels which collect soil from the seabed. The vessel needs to remain in position, called dynamic positioning, which is done by large thrusters. These are mostly electrically powered thus the total amount of required power can range up to 50 MWs. Royal IHC wants to investigate the possibility of a DC vessel where the synchronous generator’s AC voltage is rectified via a passive rectifier. The question is how stable this is and what influences the voltage stability.

The thesis focuses on building a model of a DC powered propulsion system that allows analysis of voltage stability of the vessel. The model is generalized and consists of two parallel diesel generator sets with a passive rectifier. These generators are connected to a common DC bus with constant power loads which represent the loads of the vessel. The model is built in Matlab Simulink using the specialized power system toolbox and is verified with an RScad simulation. A measurement-based analysis tool is developed utilizing prony analysis. This allows analyzing the results of the simulation model and data from the field. Both cases are tested, the tool allows to get insight into the stability of the vessel.

Due to the much needed energy transition as agreed under the Paris climate agreement, it is expected that large amounts of variable renewable energy supply will be connected to the Dutch Transmission Network. Future social, economic and technological developments will determine both the amount of electrification as the central or decentral nature of the future supply of electricity. By investigating different reports with scenarios for 2030 and 2050, key uncertainties for the Extra High Voltage (EHV) network can be identified. As of now, no open source model of the Dutch EHV network is available for research. In this thesis a synthetic model of the Dutch EHV network is created from only publicly available data in DIgSILENT PowerFactory. The created synthetic model can be used as a tool to investigate future steady-state power flows considering the sensitivities of the topology, component parameters and different operational scenarios. Besides this, a method is created for generation of future scenarios in Python. Using this model and method, simulations were done to gain key insights into the Steady-State security of the future Dutch EHV Transmission Network. For the case study, it is investigated what the effect of future additions of variable renewable energy sources (VRES) and selected locations of 10 GW installed capacity of electrolysers would be on the Dutch EHV transmission network for 2030.

Power systems nowadays are experiencing a significant energy transition characterized by the progressive increment of power electronic interfaced units. Voltage source converters are extensively utilized to interconnect renewable energy sources at various transmission levels, facilitate the asynchronous interconnection of system areas through HVDC links and enable the installment of responsive demand units into the grid. The latter increase of power electronic interfaced units in the power system has significantly altered its dynamic behavior as the system is characterized by low inertia conditions, fast and more frequent dynamics, lack of inertial response, limited short circuit capability and uncertain generation and demand mixes. Under these new operating conditions one of the main concerns of TSOs is the ability of the system to withstand active power-frequency imbalances. To cope with the frequency stability issues encountered, power electronic interfaced elements introduced, can be effectively utilized to offer ancillary services such as fast frequency support to the grid due to the high controllability levels and the rapid response capability they exhibit. This thesis project deals with the optimization of the frequency response of a multi-area, multi-energy hybrid HVAC-HVDC power system when common active power-frequency disturbances occur. The system analyzed consists of 3 electromagnetically decoupled areas through MMC-HVDC interconnection links with different generation and demand mixes characterized by different inertia levels due to the integration of fully decoupled wind turbines type IV and proton exchange membrane electrolyzers. The controllers of the power electronic interfaced elements have been modified with the active power gradient control scheme to provide fast frequency support in case of commonly occurred active power-frequency imbalances. However, to avoid insufficient or over regulation of the systems’ frequency when multiple elements target the same variable, a coordinated tuning strategy is more than necessary. For this reason, in this study two different problem formulations have been proposed aiming at a coordinated tuning of the parameters of the frequency controllers of the synthetic inertia elements participating in the frequency regulation. To effectively solve the optimization problem and enhance the frequency stability of the system a powerful metaheuristic optimization algorithm, the mean variance mapping optimization algorithm has been used. The optimization results can effectively highlight the tuning strategy that achieves the best frequency response of the system under various commonly occurred active power-frequency disturbances and provide further insight on the proper utilization of various synthetic inertia sources with respect to their response capabilities and location.

At present, the energy transition is increasingly being driven by the integration of renewable energy into the grid. However, this weather-dependent energy generation imposes challenges to the system operators since the deviations between the forecasted and the actual generation keep increasing due to this intermittent generation. Moreover, new consumption patterns and the emergence of new types of loads in the distribution grids, such as heat pumps and electric vehicles, increase the dynamics and complexity of the power system. Therefore, distribution grids need to become more active, being able to monitor the real-time changes and controlling the different network elements. In this context, operational flexibility is seen by the DSOs as a suitable solution for keeping the power balance of the system during a specific time period, coping with fluctuations and responding to variations of electricity supply and demand. For this purpose, the impact of the integration of different flexibility sources in the distribution grid has to be assessed by the DSO in order to overcome the operational challenges that it is currently facing. In order to assess the performance of flexibility in a network, this thesis proposes how to model an active distribution network based on the Dutch standards. Taking as a reference a distribution grid built on the software Vision Network Analysis, a converter was developed in order to export the network data to the input data needed in the data matrices of the open-source tool Matpower. The second step was centred upon the development of controls that simulated the action of different flexibility sources, applied to the Matpower network. For this research, flexibility from the PV distributed generation, flexible loads with demand response and short-term flexible storage have been considered. With the aim of performing a comparative assessment of the impact of these flexibility sources, the operating limits of the test network have been simulated under three different demand levels for a complete day. The base line scenario keeps the demand levels already set for the network, while the under-scaled scenario assumes a 40\% lower demand for the complete day. Additionally, an over-scaled scenario has been proposed, which considers the expected demand increase for 2030 with the corresponding integration of heat pumps and electric vehicles. In general, higher demand rates imposed longer undervoltage peaks. Then, the effect of the flexibility sources was assessed by means of the 1-hour resolution controls. It was found that the voltage regulation performed by the droop control applied to distributed generators was minimum and not useful for this type of study. On the other hand, the combination of demand response and flexible storage can deal with all the voltage deviations beyond the allowed limits. The analysis for each case will depend on the limit set for the power curtailment by demand response and the size of the necessary flexible storage system to reach a complete voltage regulation along the network. This analysis demonstrates the influence of reactive power in voltage control, as well as the influence of active power in the loading levels of the network branches. Based on these factors and in order to provide the DSO with operational indicators for the quantification of short-term flexibility, four indicators have been proposed in order to compare the needs of flexibility between networks and the performance of flexibility sources in terms of voltage regulation and loadings of the branches.