Power systems are increasingly dominated by power-electronic converters, and this shift has brought a category of stability problems that conventional tools were not designed to handle: sub-synchronous oscillations and weak-grid interactions driven by the coupling between converters and the surrounding network. Real-time simulators such as RTDS/RSCAD support impedance scanning, but their built-in tools offer little beyond a frequency sweep. External analysis frameworks go further analytically, but cannot run natively inside a real-time environment. Neither approach assesses how stability changes as grid conditions and control settings vary, which is a significant gap when the operating space of an offshore wind farm spans a wide range of short-circuit ratios and controller configurations.

This thesis addresses that gap with an RSCAD-native, Python-driven pipeline that handles admittance extraction, MIMO stability assessment, and parameter-dependent robustness evaluation within a single automated workflow. Admittance matrices at one or more points of common coupling are reconstructed in the dq-domain using a two-run D/Q injection procedure. Before any frequency point enters the analysis, it is screened by a four-pillar verification framework that checks numerical conditioning, spectral purity, stationarity, and signal-to-noise ratio. Stability is then assessed by applying the Generalised Nyquist Criterion and eigenvalue decomposition of the closed-loop impedance together, yielding both a pass/fail verdict and a spatial-spectral picture of the dominant interaction.

Two diagnostic extensions build on this baseline. Parametric Stability Space Mapping (PSSM) re-runs the full RTDS scan across combinations of short-circuit ratio, X/R, and control-gain values, mapping how stability evolves across operating conditions rather than at a single point. The Robust Stability Margin Metric (RSMM) converts the binary Nyquist verdict into a continuous scalar, which a mitigation workflow then maximises over a detected critical frequency band to identify the controller setting that most improves the worst-case margin.

The pipeline is first verified against the RSCAD Frequency Scan Analysis Tool on a passive benchmark. It is then applied to two MMC-HVDC offshore wind-park models. Both are classified as stable at the nominal operating point, but the extended diagnostics reveal substantially different robustness profiles, dominant participating PCCs, and critical frequency bands which are located in the sub-synchronous range. The PSSM-RSMM results reproduce the expected coupling between grid strength and controller tuning and point to concrete, model-specific mitigation actions: PLL gain retuning for the multi-terminal HVDC model and inner current-loop gain reduction for the single-converter model.

Taken together, the results show that the proposed workflow is numerically reliable, scales naturally from single- to multi-PCC configurations, and produces diagnostics such as the critical frequency, dominant PCC, robustness margin, and recommended controller setting that are directly actionable, rather than stopping at an isolated stability verdict. ... Read more

Transmission system-level studies face a growing challenge: the distribution networks they interface with are no longer passive. The rapid expansion of rooftop solar, heat pumps, electric vehicles, and other power-electronic-interfaced devices has fundamentally changed how distribution systems behave during disturbances, making the simplified load representations that have long served as industry standard increasingly unreliable.

This thesis develops a methodology for constructing location-specific and time-dependent aggregated load models suitable for transmission-level dynamic stability studies. Working within the Composite Load Model (CLM) framework, residential, industrial, and commercial load profiles are built from the ground up using end-use decomposition — combining publicly available Dutch and proxy datasets to derive time-varying CLM parameters across different sectors. The resulting models reflect genuine differences in load composition driven by time of day, season, and sector-specific process characteristics.

A sensitivity analysis of the CLM reveals that induction motor dynamics dominate voltage recovery behaviour under fault conditions. Static load fractions improve post-fault recovery, while power-electronic components are shown to influence system behaviour mainly through their protection and reconnection logic rather than intrinsic electrical properties. Multivariate analysis confirms that these effects are strongly nonlinear and cannot be adequately captured by first-order regression models.

To manage the dimensionality of temporal variability, K-means clustering is applied to compress thousands of hourly operating states into a small number of representative CLM parameter sets. Finally, a node importance assessment based on the Dutch transmission network admittance and impedance matrices is developed, showing that electrical distance to generating units outperforms purely topological centrality measures as a predictor of dynamic voltage rate of change. Together, these contributions provide a scalable and reproducible framework for parameterising distribution system equivalents in large-scale transmission simulations.
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As the European grid transitions towards renewable energy targets, new system stability phenomena are being observed through the electrical power system. The share of renewable generation is growing quickly as synchronous machine-based power plants are phased out. Unlike traditional synchronous machine plants, these Inverter-Based Resources (IBRs) do not provide inherent synchronous mechanical inertia. Consequently, the overall system inertia is decreasing, posing a threat to the frequency stability of the system. This trend is observed worldwide and addressed by organisations such as ENTSO-E through the introduction of future minimum inertia thresholds.

Grid-forming (GFM) technologies have emerged as a solution, providing an immediate active power support after a disturbance, via control methods. These technologies enable IBRs to contribute to frequency stability and mitigate the Rate of Change of Frequency (RoCoF).
The share of distributed energy resources has also grown, with utility-scale renewable Power Park Modules (PPMs) connected to the Medium Voltage (MV) network. These PPMs could help unlock further active power frequency support from the MV network. However, whether this support effectively supports the transmission system remains insufficiently explored.

This thesis assesses the effectiveness of synthetic inertia provided to the transmission network by GFM-controlled IBRs connected at the MV level. The study explores the metrics to assess the effectiveness of the synthetic inertia at the MV-HV interface, investigates the technical constraints of the provision from the distribution-connected resources and offers mitigation measures. Additionally, the comparison of the synthetic inertia support from the HV and MV-connected GFM assets is done.

Firstly, using DIgSILENT PowerFactory, a test benchmark is developed, where the response of a storage PPM with grid-forming controls is evaluated under different disturbances, in order to tune the GFM dynamic models and ensure compliance with grid code requirements. To test the synthetic inertia support of PPMs in a realistic model, a combined transmission and distribution system model is developed from an initial model, which has been adjusted to represent the Dutch grid characteristics. Multiple scenarios and disturbances are simulated with the GFM PPM connected at various locations within the MV network to explore the limits of synthetic inertia support.

The results demonstrate that for a frequency disturbance, the RoCoF and the frequency nadir/zenith improve regardless of the PPM connection point. However, the magnitude of the improvement is dependent on the available active power headroom and the current capabilities of the PPM. A critical limitation was observed regarding the parallel provision of active and reactive power when the PPM is connected to the MV grid. For connection points far from the point of interconnection, voltage stability became more important, as MV buses are more sensitive to active/reactive power injection. During large frequency disturbances, the PPM's active power and reactive power demand grew, which led to current limits being hit, as the PPM sustains the active and reactive current. This suggested a need to enhance voltage and reactive power control or alternative voltage stability methods to support the voltage during frequency disturbances for distribution-connected grid-forming units. ... Read more

The increasing penetration of converter-interfaced renewable energy sources (RES) in modern power systems has significantly reduced synchronous inertia, posing challenges to short-term frequency stability. As a result, fast active power response (FAPR) from power electronic converters, such as modular multilevel converters (MMCs) connected to offshore wind power plants (WPPs), has become increasingly important. However, transmission system operators (TSOs) often lack access to proprietary converter control settings, making it difficult to assess the available frequency support capability of these resources in real time.
This thesis proposes a signal-record-based estimation method using an artificial neural network (ANN) to quantify the fast active power response of a mixed generation system consisting of synchronous generators and MMC-interfaced wind power plants. The method relies exclusively on measurable system signals, such as system frequency, rate of change of frequency (RoCoF), and pre-disturbance operating conditions, without requiring explicit knowledge of converter control strategies.
A comprehensive synthetic dataset is generated using detailed RSCAD-RTDS simulations of a multi-terminal offshore HVDC network connected to a reduced onshore AC system. The dataset captures a wide range of operating conditions by systematically varying key system parameters, including
Synchronous generator inertia, initial loading levels, and wind speeds at multiple offshore WPPs. Controlled load-step disturbances are applied to excite system frequency dynamics and corresponding fast active power responses. An ANN is trained to estimate the active power response trajectories of both the MMC and the synchronous generator following a disturbance. The results demonstrate that the proposed approach can accurately infer fast active power response characteristics from frequency measurements alone. This work provides a practical estimation tool that supports TSOs in assessing frequency support capability in converter-dominated power systems under uncertain and time-varying conditions. ... Read more

This research focuses on a critical challenge in modern power systems: the effective coordination between transmission system operators (TSOs) and distribution system operators (DSOs) to harness distributed flexibility for grid stability and efficiency. As energy systems undergo a fundamental transformation toward decentralized, decarbonized, and digitalized operations, the ability to accurately estimate and activate aggregated flexibility in distribution systems is becoming a cornerstone of secure and sustainable grid management..... ... Read more

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.
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In the forthcoming decades, an increasing share of energy is projected to be generated by offshore wind power plants (WPPs). Adverse interactions involving multi-converter systems and passive network elements could lead to subsynchronous oscillations (SSOs), possibly damaging grid components or otherwise interrupting the power flow. Secondly, the development of analytical models for converter-dominated grids is hindered due to nonlinear dynamics and proprietary specifications of converters. Therefore, the aim of this thesis was to investigate SSO phenomena in converter-dominated offshore systems with the measurement-based impedance stability method.

This thesis considered a multi-energy offshore system. At the offshore side, WPPs and ELs are located, totalling 2~GW and 500~MW, respectively. They are interconnected to the onshore grid by a bipolar DC link. Four control strategies have been integrated into the wind turbine (WT) converters; standard grid-following (GFL) and three grid-forming (GFM) strategies: droop, virtual synchronous generator (VSG) and synchronverter.

Subsequently, the impedance-based stability method was utilised. This method entails obtaining the impedance response by performing impedance scans. The next steps dictate the calculation of the return-ratio matrix and eigenloci, required for application of the generalised Nyquist stability criterion (GNSC). In order to improve the accuracy of the stability assessment, a frequency domain vector fitting algorithm is adopted, which provides continuous transfer functions. Thereby, stability indicators such as sensitivity peak, oscillatory frequency and damping ratio can be inferred. One drawback of the algorithm is the possible occurrence of spurious poles, which might result in incorrect stability conclusions, especially when fitting nonlinear eigenloci functions.

This thesis sought to contribute to the assessment and quantification of SSOs. To this end, it was studied how operating conditions based on parametric differences influence SSOs. It highlighted that critical oscillatory modes (OMs) could be extracted and quantified and that the offshore system is responsive to SSOs due to the presence of parallel-connected converters and passive cable elements. Furthermore, it revealed that interchanging GFL with GFM improves the oscillatory stability to a sufficient level. Thereby, reduced sensitivity and improved damping were observed for short offshore cable distance and WT underloading. Importantly, it was shown that 50/50 deployment ratio of GFL/GFM yields the best oscillatory performance and activation of EL saw additional enhancement upon the baseline. Altogether, it was illustrated that the impedance-based stability method enables insightful analyses of the oscillatory performance for converter-dominated systems. ... Read more

The ongoing transition toward low-carbon energy systems is marked by a rapid expansion of renewable energy sources, particularly offshore wind. However, the variability and limited predictability of wind generation introduce significant operational challenges, especially when conventional fossil-based units that historically provide stability and dispatchability are reduced. Ensuring continuous supply, while maintaining system efficiency and minimizing curtailment, requires new forms of flexibility that can balance supply and demand over different time scales. Hydrogen technologies have emerged as a promising candidate for this purpose due to their ability to store large amounts of energy and reconvert it when required. Yet, their effective deployment depends on coordinated planning and operational strategies, which are often treated separately or simplified in existing studies.

This thesis proposes a bilevel optimization framework that jointly considers long-term planning and short-term system operation for a wind-integrated power system employing hydrogen fuel cells and a hydrogen-fired gas turbine. The planning stage determines the siting and sizing of these units using Particle Swarm Optimization (PSO), while the operation stage employs a Mixed-Integer Linear Programming (MILP) model to dispatch generation and assess feasibility under network constraints. To represent realistic renewable variability, a stacked Long Short-Term Memory (LSTM) model is trained to generate a one-year offshore wind profile that captures daily and seasonal fluctuations. The interaction between the planning and operation layers ensures that the final configuration is both economical and operationally robust.

Application of the framework to a modified IEEE RTS-24 system with offshore wind from Ijmuiden Ver Alpha demonstrates clear benefits. The coordinated hydrogen-to-power configuration reduces annual wind curtailment from 4.42 TWh to 1.65 TWh, decreases load shedding from 452.9 GWh to 18.0 GWh, and lowers total system operating costs from \$313.88 million to \$239.29 million. Additionally, the system maintains adequate supply across seasonal conditions, confirming the value of hydrogen-based flexibility in high-renewable environments.

Overall, this research contributes a structured planning–operation methodology that integrates realistic wind modeling, hydrogen conversion dynamics, and power system constraints. The proposed framework provides a scalable and practical approach for supporting the reliable and cost-effective transition toward future renewable and hydrogen-integrated energy systems. ... Read more

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. ... Read more

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. ... Read more

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 ... Read more

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.
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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. ... Read more

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. ... Read more

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. ... Read more

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. ... Read more

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.


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The growing deployment of geographically close Voltage Source Converter-based High Voltage Direct Current (VSC-HVDC) links enables their interconnection into meshed or multi-terminal HVDC networks. Ensuring the interoperability of such networks, particularly when they evolve from progressively expanded point-to-point links, is a complex task that requires a detailed understanding of control strategies and their influence on power system stability. Simulation models play a critical role in evaluating how expanded VSC-HVDC systems support AC grid stability. However, existing models often require modification to represent multi-terminal operation and to comply with modern grid code requirements. Therefore, upgrading simulation models for analyzing the multi-terminal expansion of VSC-HVDC links remains an important research challenge.

This dissertation addresses this challenge by extending a VSC-HVDC simulation model within a root-mean-square (RMS) simulation framework through the development of several supplementary power controllers. The controllers are implemented in DigSILENT PowerFactory and modify the active and reactive power regulation of a VSC-HVDC link depending on the stability phenomenon being analyzed. Reactive power regulation is adapted to support voltage stability through dynamic power factor control and polynomial-based reactive current injection control. Active power regulation is modified to provide primary frequency support through a power-line communication-based controller, a post-fault active power recovery control, and an open-loop frequency controller.

In addition to these modelling improvements, the dissertation proposes methods for performance assessment and control design. A directional derivative-based method (DDBM) is introduced to evaluate the quasi-stationary voltage support provided by reactive power controllers without requiring time-domain simulations. This method helps identify the most suitable control strategy under different power flow conditions and network strengths. Furthermore, a dynamically adjustable fault impedance (DAFI) concept is proposed to improve the active and reactive power response of VSC-HVDC links during fault ride-through (FRT) and post-fault operation.

The results show that expanding a point-to-point VSC-HVDC link into a multi-terminal configuration affects both active and reactive power responses and their interaction with the AC system in steady-state and dynamic conditions. For example, dynamic power factor regulation can lead to AC voltage deviations of up to 3% during active power reversal events. The DDBM analysis indicates that dynamic power factor control is generally less effective in supporting quasi-stationary voltage stability under the studied operating conditions. The DAFI concept demonstrates that inductive system characteristics can be emulated through first-order dynamic responses, improving controller performance during fault and post-fault periods.

Additional control strategies are proposed to support frequency stability. A power-line communication-based controller using harmonic amplitude modulation enables primary frequency support and reduces the rate-of-change-of-frequency and frequency nadir during network split events. An open-loop frequency controller is also introduced to coordinate frequency responses between asynchronous AC systems under severe power imbalances.

Finally, the study shows that multi-terminal HVDC expansion requires transient DC voltage control to manage post-fault active power recovery. A multi-terminal DC voltage controller based on an exponential function is proposed to regulate DC voltage during recovery periods. Simulation results demonstrate that coordinating this controller with DC choppers can reduce AC/DC power imbalances by up to 80% while restoring active power within 200 ms.

Overall, the proposed modelling and control approaches improve the analysis and operation of multi-terminal VSC-HVDC systems and contribute to the reliable integration of HVDC networks into future power systems. ... Read more

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. ... Read more