The increased integration of renewable energy sources and power electronic converters has transformed conventional power systems into hybrid AC-DC systems, introducing faster and more complex fault dynamics that challenge existing protection schemes. While data-driven approaches have demonstrated high accuracy in fault detection and classification, their lack of prediction validation limits their reliability in critical protection systems. This thesis proposes a real-time data-driven framework for event classification and validation for Hybrid AC-DC systems. A comprehensive dataset of AC and DC faults was generated from an RTDS based grid model, with transient measurements acquired using a Python-based communication interface and processed to extract time domain and dynamic fault features. Independent machine learning classifiers were developed for the AC and DC subsystems. An additional waveform signature validation layer that uses representative transient signatures of event classes and similarity analysis was introduced to verify classifier predictions. Performance evaluation demonstrated that the proposed framework achieves accurate and robust event classification under varying operating conditions and moderate signal degradation, while providing additional confidence assessment for machine learning-based classifier predictions. The proposed approach offers a practical and reliable solution for real-time monitoring, event identification, and supervisory protection in future converter-dominated power systems. ... Read more

Power transformers are critical components of electrical power systems, and their behavior under high-frequency and fast transient conditions plays an important role in overall system reliability. Phenomena such as internal resonances within transformer windings can lead to significant overvoltages and localized electric field intensification, potentially resulting in insulation degradation or failure. Accurate modeling of transformer behavior over a wide frequency range is therefore essential for both design and transient analysis. However, conventional transformer models are often limited by either oversimplified analytical assumptions or the high computational cost and limited generalization capability of purely numerical approaches.

This thesis presents a comprehensive framework for the frequency dependent modeling of power transformers, with particular emphasis on high-frequency behavior. The work focuses on the development of white-box models derived from electromagnetic field theory, complemented by data-driven machine learning techniques to enhance computational efficiency while preserving physical consistency.

The first part of the thesis investigates the impact of conductor and core losses on the impedance characteristics of transformer windings. Numerical simulations are employed to quantify the influence of eddy current losses in both conductors and ferromagnetic cores. The results demonstrate that each loss mechanism dominates in different frequency ranges, and that neglecting conductor losses can lead to significant errors in impedance estimation and resonance prediction at higher frequencies relevant to electromagnetic transient studies.

Building upon these insights, the thesis develops an analytical framework for frequency-dependent impedance modeling of transformer windings. To validate the proposed analytical approach, several case studies are presented in which the derived impedance characteristics and parameters are compared against numerical simulations and experimental measurements, demonstrating good agreement across a broad frequency range. The analyses confirm the capability of the proposed approach to accurately capture resonance phenomena and frequency-dependent losses with substantially reduced computational effort compared to full numerical field solvers.

In the final part of the thesis, a machine learning-based methodology is introduced to further accelerate the estimation of frequency-dependent winding impedances. Using a dataset generated from the analytical framework, an XGBoost model is trained to predict the frequency dependent parameters. The results show that the proposed data-driven models achieve high accuracy while offering significant computational speed-ups, making them well suited for large-scale parametric studies and design optimization.

Overall, this thesis contributes a unified modeling framework that bridges analytical electromagnetic theory, numerical validation, and machine learning techniques for the high-frequency modeling of power transformers. The proposed methods enable accurate and efficient prediction of transformer winding behavior under fast transient conditions, providing valuable tools for transformer designers and power system engineers.
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Transformers are a vital component of power systems. As well-established electromagnetic devices, they change voltage levels and enable efficient power transfer while preserving the system’s frequency. Ensuring the reliable operation of these critical unit s is essential for the continuous transmission of electrical energy. Consequently, safeguarding transformers against various faults has always been a significant concern in power systems.

One phenomenon that threatens transformer performance is transient voltage in the power system. These transient voltages, containing a range of harmonic frequencies, propagate as electromagnetic waves through power lines and interact with transformers. Transients often result from lightning strikes or switching operations. Upon receiving these signals, transformers respond differently to various frequency components, necessitating precise modeling and frequency response analysis to predict their behavior under such conditions.... ... Read more

Dow Terneuzen, the second-largest site of Dow Chemical, relies on the ELSTA cogeneration plant to supply electricity and steam to its production facilities while contributing to the Dutch national grid. Ensuring stable operation is critical for safety and reliability. While internal disturbances are managed by existing protections, external grid faults pose challenges for detection and for enabling a controlled transition to islanded operation.
This thesis develops and validates an islanding tripping scheme for Dow Terneuzen. The objectives are to design a protection logic based on frequency and undervoltage detection, establish a load shedding strategy to maintain generator stability during islanding and validate the protection logic using online simulations and hardware testing. A dynamic model of the power system was created in ATP-EMTP, including synchronous machines with governors and excitation systems, transformers, and dynamic loads. Fault scenarios were simulated to assess stability, determine critical clearing times, and validate the protection logic. The protection logic was then programmed into a Siemens 7UM85 relay using DIGSI5 and tested with an Omicron CMC 356+, where COMTRADE signals from simulations were replayed into the relay. Relay responses were analyzed using the Fault Record tool SIGRA and compared with the online simulation results.
The results show how generator dynamics affect stability, confirm the need for rapid load shedding, and highlight challenges in designing a reliable islanding tripping scheme. The comparison between ATP-EMTP simulations and relay tests demonstrates the effectiveness of the proposed scheme and provides practical guidance for implementing reliable islanding protection at Dow Terneuzen. ... Read more

Series DC arc faults are hard to detect in low-voltage direct current grids because the change in line current is usually too small for classical protection devices. Undetected arcs can overheat conductors and start fires, so dependable detection is essential for future bipolar microgrids. In this thesis, an embedded method that combines the detailed energy from a short Discrete Wavelet Transform with the wide-band energy of a Fast Fourier Transform, then classifies each observation window with a linear support vector machine that runs on a single microcontroller, is developed. Laboratory and field tests confirm that the algorithm detects low-energy series arcs without nuisance trips and operates within the response time required by UL 1699B. The novelty of the work is the mixed wavelet–FFT feature, which captures both local transients and wide-band noise in a compact indicator, making accurate detection possible with modest processing resources. ... Read more

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In recent years, the electricity grid has evolved rapidly due to the large-scale integration of renewable energy sources and the growing demand for electricity. This development has led to more customer connections and grid expansion projects, resulting in a more dynamic and flexible system. To maintain safe and stable grid operation, frequent switching of equipment, such as reactive power compensation devices (e.g., capacitor banks) and cable circuits, is often required.

However, energising capacitor banks and cable circuits can cause severe voltage transients and inrush currents. Such transients could impose challenges such as dielectrically stressing the insulation of power apparatus and violating Grid Code limits related to Power Quality. Point-on-Wave (PoW) switching is a promising technique to suppress these unwanted effects, but its practical effectiveness is not yet fully understood by TenneT, the Dutch transmission system operator.

This study investigates the effectiveness of PoW switching for energising cable circuits and capacitor banks in a Dutch 150 kV grid scenario. It also examines how switching imperfections, such as “pole scatter” and an imperfect “Rate of Decrease of Dielectric Strength”, affect the PoW switching effectiveness. The central research question is: “Is PoW switching an effective solution for meeting the TenneT NL policy requirements when switching capacitor banks and cable circuits?”

To answer this research question, a state-of-the-art analysis is first carried out to provide the technical background of PoW switching. Next, TenneT’s current policy on PoW implementation and the voltage quality requirements of the grid are reviewed to assess whether the outcomes of this study align with these standards. Based on this foundation, a detailed simulation plan is developed, and the simulation results are analysed. Finally, a discussion section offers a critical reflection on various aspects, including alternative mitigation methods, the alignment of statistical and deterministic data, and the need for mathematical compensation of external variables.

It can be concluded that Point-on-Wave (PoW) switching significantly reduces inrush currents and transient overvoltages compared to switching without PoW. Based on 200 Monte Carlo simulations per configuration, it is shown that without PoW, all simulated capacitor banks and cable circuits exhibit Rapid Voltage Changes (RVC) exceeding the 10% limit set by TenneT’s policy. However, when PoW is applied, none of the investigated capacitor banks, rated at 25 MVAr, 50 MVAr, and 75 MVAr, nor any of the simulated cables up to 49.5 km in length exceed the 5% RVC limit specified in the grid code, whereas without PoW, these configurations do show a significant amount of exceedances above this 5% limit.
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On 19 December 2021, a single-line fault during energisation occurred in a grid segment in the Netherlands, which was caused by a defective earther fault that failed to disengage. During the fault, the implemented differential protection scheme failed to operate as intended, resulting in a delayed response of 189 ms.

This thesis aims to clarify the root cause of the malfunction and prevent any similar problems in the future. While the cause of the electrical fault was quickly identified, the reason behind the relay malfunction remained unclear.

The affected network segment was modelled using the Real Time Digital Simulator (RTDS), a tool capable of accurately replicating fault conditions. The RTDS surpasses conventionally used fault playback tools, as it can simulate a wide range of dynamic system behaviours. The protection relay was connected in a Hardware- in-the-Loop (HIL) setup to test its real-time response.

Testing with the RTDS revealed that tuning specific relay settings can effectively prevent the malfunction during future fault events. Nowadays, modern numerical relays offer a wide range of powerful protection functions. The intended behaviour of these functions, along with their impact on the relay’s response, must be carefully considered to prevent malfunctions. ... Read more

With the increasing integration of renewable energy sources such as Type-3/4 wind turbines and photovoltaic systems, fault current levels in power systems have decreased, weakening the performance of traditional distance relays. To address this, the Stockwell Transform (S-Transform) based fault detection algorithm has been proposed and has proven effective in identifying fault occurrences. While previous work has implemented the S-Transform-based fault detection algorithm in the Programmable Logic (PL) of the FPGA and validated it through AMD Vivado simulation, integration into a physical FPGA board and a Real-Time Digital Simulator (RTDS) environment has not yet been achieved. This paper presents a complete hardware-software co-design in which the exiisting implementation is deployed on an FPGA board and integrated with an RTDS system. The proposed system enables real-time communication between the RTDS and the FPGA via the IEC~61850 protocol. The PL of the FPGA platform executes the fault detection algorithm, while the Processing System (PS) handles IEC~61850 protocol communication, data exchange between the PS and the PL, and interrupt handling within a bare-metal environment. Experimental results demonstrate that the entire design meets strict real-time performance and delay requirements, validating the system’s suitability for high-speed fault detection in distance protection applications. ... Read more

This thesis investigates switching transients in a test system comprised of a single-core underground cable, vacuum circuit breaker, and (Y-Y) star transformer. This work presents six scenarios in which test systems are connected to the transformer in different load scenarios such as no-load, medium and high loads, low and high capacitance, and a combined impedance-capacitance case. Monte Carlo simulations have been employed to introduce random variability into the parameters of vacuum circuit breaker(VCB) to enable probabilistic analysis of extreme transients. Using EMTP and MATLAB software, the study confirms how probabilistic transient analysis can be utilized to improve power system reliability and design protective switchgear. ... Read more

The urgent need to decrease global carbon emissions to meet the Paris Climate Agreement calls for sustainable methods to manage growing electrical demands. This energy transition requires the decommissioning of large fuel-based power plants and simultaneously replacing them with power-electronics interfaced intermittent renewable energy sources and loads. These developments pose high stress on our ageing grid infrastructure, leading to an increased level of unanticipated electrical disturbances that, if left unchecked, might lead to total grid collapse. The thesis presents an expert system that fortifies the ever-evolving grid with advanced event identification and learning architecture engineered to protect against contemporary and evolving grid disturbances. The chosen design perspectives are intended to assure trust in academic algorithms and bridge the expanding gap between the academia-industry. In this context, the dissertation has three main contributions namely:
♦ A real-time PMU-based distribution state estimation.
♦ A near-real-time dynamic incremental learning-based event classifier.
♦ An adaptive human-in-the-loop event identification methodology.

First, to conduct extensive simulations on variety of model-driven and data-driven algorithms, a close to real-life simulation environment needs to be set-up. Using RTDS a cyber-physical replica of a 50 kV ring network operated by Stedin B.V. in the Zeeland area of the Netherlands is developed. Further, the grid is upgraded in 3 operational stages to meet steady-state, quasi-steady-state and dynamic-state conditions. This forms the benchmark grid for all further studies. Subsequently, as a first step towards real-time grid situational awareness, state-of-the-art EKF- and UKF-based state estimation algorithms are developed, tested and validated to achieve complete grid observability in terms of determined node voltage phasors for the grid. With enough confidence in terms of SE accuracy and computational efficiency in the steady-state, the PMU-based state estimator increases complexity by QSS operation and finally, by adopting an anomaly detection, discrimination, and identification module, the PMU-based state estimator is enhanced to co-simulate within the fast refresh rates of PMUs under a fully dynamic grid with abrupt SLC and multiple bad-data events.

Second, with PMU-detectable events addressed, events with complex temporal signatures are systematically identified using data-driven models. Recommendations are developed for a forecast-based event detection model and subsequent real-time data pre-processing, which collect disturbance signatures. A multivariate 1D CNN classification model is designed to identify event types using disturbance signatures in real time. In the first stage, simulations are performed for events which are known and previously trained by the model. In the next stage, the DIL strategy is used to adapt the data-driven model for unforeseen and statistically drifted event types. The classification accuracy, memory consumption, and computational efficiency are used as performance metrics to validate in near-real-time conditions.

Third, in order for data-driven models to meet industrial expectations, an AdInFier expert system is developed, which primarily adds a validation stage to verify the classification results using an unsupervised learning approach. A Soft-DTW technique is used for event representatives that will be compared with incoming disturbance signatures to provide a similarity score. The classifier-validator duo provides a two-stage approach for event identification so that control actions can be actuated in real time in high-stakes environments of control centres. Subsequently, we inculcate a human-in-the-loop approach within an AI environment to deal with complex, contradictory situations where the grid collected data is not mature enough for models to decide on the event type. This step is mainly to add domain expert knowledge in the solutions of over-deterministic data-driven models.

The main purpose of this dissertation is to get a step closer to real-life implementation of state-of-the-art model-driven algorithms and ensure trust in the new cutting-edge data-driven domains with the ultimate goal of meeting industrial requirements. As future recommendations, we propose further enhancements to the AdInFier expert system in terms of control actions and solution fulfilment capabilities, so that we can safely manoeuvre in today's fast-paced technological landscape. ... Read more

This thesis proposes an automated method for generating, executing, and assessing an interlocking test in a digital substation using a Python script designed for that specific purpose.

The goal is to expedite the process of performing the factory acceptance test (FAT) and the site acceptance test (SAT) of a substation automation system (SAS). This work requires a good understanding of the IEC 61850 standard, which is the international standard applicable to protection, automation and control systems (PACS). An account of the relevant parts from this series is therefore given, in addition to an overview of the benefits of digital substations in general.

The workflow for automatically generating a test case is based on previous work that made it possible to execute and assess an interlocking test automatically but not to generate a test case automatically for this purpose. Therefore, that is the main intention of the thesis.

It is done by having knowledge of the underlying interlocking logic of the system subject to test. From this logic, a test sequence can be created, where the position of the various switchgear is changed sequentially. This and the signal addresses for these devices are needed to generate a test case.

For additional robustness, the script can cross-check the signal addresses provided with the signal addresses in the substation configuration description (SCD) file and validate the final test case generated using a suitable schema. It is furthermore capable of generating a test case irrespective of the number of test steps, switching devices, and bays present in the substation.

A test file generated using this script is further validated by executing the test it describes in the SAS laboratory at the Norwegian University of Science and Technology (NTNU). This test was carried out remotely to showcase the possibilities of IEC 61850, which can be valuable for distant or offshore substations. Another benefit of this workflow is that it allows for the simulation of all devices of the test except for the device under test (DUT). This is particularly useful during commissioning if all devices have not yet been delivered or installed. In this case, the missing equipment can be compensated for by simulating the signals expected from these devices.

The final assessment of a test case relies upon the presence of the IEC 61850 LN (Logical Node) CILO (Control Interlocking). The output of this LN controls the interlock status of the DUT. If the DUT is allowed to operate, it sends a release signal or, alternatively, a blocking signal. In addition to this, information is gained based on the position of the switchgear under test to check that the CILO signal is consistent with the actual switchgear control command. This control command is known as the AddCause in IEC 61850 and will provide additional information on whether or not the DUT is interlocked.

Finally, the thesis will describe ongoing work in the IEC 61850 that could lead to a more streamlined approach and touch on the utilities' attitude towards SAS.

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This thesis explores a Travelling Wave (TW) parameter fitting-based approach for both fault location and protection in a multi-terminal High Voltage Direct Current (HVDC) network. Utilizing a three terminal HVDC network model within a Real-Time Digital Simulator (RTDS) environment, a custom parameter fitting control component is developed using the Adaptive Multi-step Levenberg-Marquardt (AMLM) algorithm. For fault location, the methodology analyzes the line-mode backwards travelling voltage wave (Vb1) following an internal DC cable fault. Despite the successful integration of the AMLM parameter fitting algorithm into the real time environment, the achieved average absolute error of 9.80% (29.4 km) for faults spaced 50 km along a 300 km cable was above the acceptable threshold, rendering the proposed
method impractical for precise fault location. Improvements through specific signal truncation and optimal cable parameter selection reduced the error to 5.15% (15.45 km), which remains insufficient for practical applications. In contrast, the TW parameter fitting method proves highly effective for fast and fully selective protection. The protection scheme accurately discriminates between internal and external faults using the Vb1 signal and determines fault types through Vb0 signal analysis. Extensive testing revealed a fault detection rate of 100%, with an overall accuracy of 99.91% for fault resistances up to 200Ω. Severe internal faults are isolated in 1.68 milliseconds, while non-severe internal faults are typically isolated in 3.84 milliseconds. The method completely eliminates relay deadzone, providing robust performance even under noisy conditions with an accuracy of 99.85% for faults with an impedance up to 50Ω. These findings highlight the potential of the TW parameter fitting approach to significantly enhance the reliability and promptness of fault isolation in HVDC systems, while offering insights into the challenges and limitations of fault location accuracy on a real time platform. ... Read more

Climate change is one of the most dangerous and simultaneously most complex threats humanity has ever faced. The key response to this threat has been an unprecedented strategic shift in the energy sector, known as the energy transition. Electricity powers the modern world and is at the very centre of the energy transition. The shift to sustainable electricity production, transmission, distribution, and consumption is therefore vital. However, such a change brings significant technical challenges that should be addressed. The objective of this research is to uncover and investigate some of the key challenges in this regard and propose solutions for their mitigation.

This thesis largely focuses on two technical aspects and related challenges: power system vulnerability and stability. The emphasis lies on modern power systems, where conventional synchronous generation is increasingly replaced by inverter-based resources (IBRs). The first research objective is to improve the understanding of both system vulnerability and stability, particularly in the context of voltage stability and system strength and their intricate relationship. Relying on this improved understanding, the second objective is to develop advanced and novel evaluation methods and algorithms.

The developed methods form a basis for advanced voltage stability and system strength evaluation of modern power systems. Such an evaluation can play an important role in the overall stability and dynamic security assessment performed by power system operators, with the goal of cutting through the complexity of numerous possible contingencies and operating scenarios. The evaluation automatically identifies the most vulnerable weak grid sections and dangerous operating scenarios that may lead to cascading faults and possible instability. Consequently, once such grid sections and scenarios are observed, more detailed simulations and analyses can be performed by power system stability experts in a much more time-efficient and targeted manner. Subsequently, proactive mitigation measures can be taken to avoid the risk of instability and blackouts.
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A secure, equitable, and environmentally sustainable energy system is a critical global challenge in pursuing a sustainable future. As dependence on fossil fuels wanes and the integration of renewable energy sources escalates, traditional power grids are confronted with unprecedented challenges, particularly in system inertia. This situation necessitates a substantial upgrade in energy transmission infrastructure. Such infrastructure must evolve to bridge the expanding geographical gap between renewable generation sites and consumption centres, all whileaintaining power system stability. The solution to this complex puzzle may well reside in developing the ’Express Energy Highway’—a concept that envisions a trans-national High Voltage Direct Current (HVDC) grid as the backbone of a modern, digital-era energy network. HVDC grids are at the forefront of this transformation, providing an efficient solution for long-distance power transmission and capable of integrating a diverse range of energy sources with lower losses compared to traditional HVAC power systems. The expansion of HVDC technology, especially within Europe’s ambitious energy targets and the phased decommissioning of nuclear power plants, underscores the pressing need for advanced control systems and real-time simulation models to navigate the complexities of these next-generation energy highways... ... Read more

The MMC-based MTDC systems are considered a promising solution for long-distance power transmission, integration of renewable energy sources, and interconnection of power grids. Nowadays, MMC-based MTDC systems have been successfully developed in various projects worldwide and are expected to play a significant role in future electrical power transmission systems.

Despite the benefits provided by the MMC-based MTDC system, various technical problems emerge. For example, in case of a DC fault on HVDC transmission lines, the DC voltage suffers a deep sag, and the fault current increases to the peak value after several milliseconds, the system stability is seriously affected. The fault currents will easily damage the power electronics and may lead to a collapse of the entire system if the faults are not cleared promptly. Thus, it is crucial to implement a fast, selective, and reliableDC fault protection technology in the system for fault detection. Once the fault is cleared, it is important to know the exact fault location to repair the faulty sections and to restore the system. Hence, an accurate DC fault location technique is of utmost importance for the MTDC system, which would significantly minimize electricity loss and expedite the system restoration process in the event of power outages. In addition, there is a lack of standardization in MMC control, and the majority of HVDC projects are constructed in a vendor-specific manner. As of today, it is unclear how MMC converters from different manufacturers will interoperate with each other. These pose new challenges to the performance of HVDC protection and MMC control and need to be addressed to manage, safeguard, and accelerate the practical feasibility of this system.

The research in this thesis aims to address the shortcomings that have not been addressed in the state of the art, mainly related to the challenges arising when DC faults occur in the MMC MTDC systems and, as such, could provide promising solutions for future practicalMTDCapplications. The main topics areMMC control&interoperability, Protection, and Fault location for the MMC-based MTDC system. The thesis deals with designing a robust protection scheme, a fault location method, and an investigation of the interoperableMMC controllers...
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LVDC Distribution systems are becoming popular due to the avenue of integrating renewable energy sources on a large scale. Predominant DC based power system architecture has been predicted to serve the needs of a sustainable society that holds the capability to self-generate, share, and trade power produced from renewable energy sources. Bottom - up approach beginning from development of products that run on DC till microgrids and integration of rural communities using LVDC distribution presents as a promising avenue for adoption of DC grids worldwide. Many areas in DC distribution system are yet to undergo rigorous study both theoretically and practically. Touch protection is one such area which is largely unexplored. Residual current devices (RCD) are traditionally implemented at the load side to trip at specific residual current levels ranging from few to hundreds of milli amperes. Current trip thresholds and time within which the fault must be isolated are different for DC. There is dearth of standards for DC RCD. In this thesis project we attempt to design a compact, reliable, and cost-effective RCD. The designed and developed prototype is tested at DC Low Voltage levels for various residual current magnitudes to determine important parameters like reaction time and accuracy. ... Read more

Submodules are the building blocks for MMC-type HVDC converters and therefore of utmost importance for converter reliability. In order to unlock smarter maintenance strategies for submodule semiconductors, the technical condition of the semiconductors needs to be estimated to form a health index. Besides the non-project-specific traditional health index methods, a complete practical implementable data-driven lifetime estimation approach for individual converters is needed to determine the exact remaining useful lifetime of all submodule semiconductors. The methodologies should finally explore a new research direction in the optimization of the converter lifetime considering maintenance intervals. This thesis presents a health index methodology applicable to submodule semiconductors in modern MMC-type HVDC converters. The ON-state collector-emitter voltage is used as a condition indicator and external influences are neglected with electrical and thermal models. These models are needed to estimate the junction temperature in the submodule semiconductors due to the temperature-dependent ON-state collector-emitter voltage. A novel lifetime optimization methodology is presented that determines the submodule that is near its end-of-lifetime and should be replaced in the next maintenance interval. In order to optimize the converter lifetime, the selected submodule is switched more frequently based on a selection window generated from the submodule insertion vector. Switching this submodule more frequently can ensure that it fails exactly at a determined time instant and allows other submodules to be switched less frequently extending their remaining useful lifetime. Finally, a complete data-driven lifetime estimation methodology has been described that uses available measurements in existing MMC-type HVDC converters. Based on the converter load profile and the semiconductor specifications, estimations are made on the submodule semiconductors’ lifetime. Simulations show the significant influence of the DC-pole current based on different voltage class semiconductors and their limitations considering the minimum required lifetime. ... Read more

Zero emission fuels and reducing emissions are important topics in all transport sectors and hybrid systems play a key role in the transition towards full decarbonization. This thesis studies the components that are found in hybrid maritime electrical power systems and their influence on power quality, short-circuit currents and protection & coordination. In order to help system integrators such as Alewijnse in the design of these hybrid systems, two typical models of actual vessels are created in simulation software ETAP. Both systems are low-voltage, high-power systems, based on either an AC or DC busbar.

Rules and standards related to power quality and short-circuit currents are studied as well as practical protection strategies. For the AC model, various studies have been successfully simulated including a load flow study, transient stability study including peak shaving and virtual generator simulations for the battery, a protection & coordination study and a harmonic study. Some challenges with ETAP regarding DC grid simulations are discussed, but is also demonstrated how to use the formulas and standard approximation function from the IEC 61660 to calculate short-circuit currents and I2t values and how to use these results in the protection & coordination study. ... Read more

As the electricity sector transitions towards a low-carbon future, an increasing proportion of synchronous generation in the power system is replaced with inverter-based resources (IBRs). The result is a reduction in the available rotational inertia in the grid, depleting its ability to withstand and arrest frequency changes following disturbances. Consequently, disturbances such as a loss of generation or load have an increasingly larger impact on the system, resulting in higher frequency deviations and increased rate of change of frequency (RoCoF).

On two occasions in 2021, the Continental Europe Synchronous Area (CESA) experienced system splitting events caused by cascading trips of several transmission system elements. In both cases, system defence plans were activated in order to preserve the integrity of the overall system. The amount of disconnected load was limited on both occasions, however, should similar events occur in the future with even lower rotational inertia in the grid, the impact could be more severe. This raises the question of whether the existing defence measures are sufficient to maintain system integrity and stable system operation.

Currently in CESA, containment of system frequency excursions following a severe loss of generation is achieved through low-frequency demand disconnection (LFDD) at a frequency below 49Hz. Due to the reduction in traditional synchronous generation and system inertia, the frequency stability of the system is expected to deteriorate, leading to an elevated impact of major disturbances, a rising probability of forced disconnections at frequencies below 49 Hz, and the potential for cascading loss of generation and blackout events.

The objective of this research is to explore the potential impact of reduced system inertia and increased penetration of renewable generation on the performance of the traditional LFDD scheme. In conjunction, additional proactive measures are proposed and investigated with the aim to reduce the probability of LFDD disconnections, by taking actions at frequency thresholds between 50 and 49Hz, as well as to improve the performance of the LFDD scheme in the event that disconnections are required. As a test case, the LFDD scheme as currently applied by one of the distribution system operators in the Netherlands is considered.

This project is therefore categorised in two primary research directions: (i) improving selection criteria for LFDD load shedding locations, and (ii) improving LFDD performance using alternative load shedding schemes.

Key topics explored in this research include: (i) the use of system strength and real-time DER generation as input parameters to load bus selection criteria for LFDD, and (ii) proactive RoCoF-based disconnection of pre-determined consumers above 49Hz. The findings of this study indicate that adapting the current LFDD implementation based on the local system strength and the level of active DER generation at LFDD buses can improve frequency response and reduce instability following LFDD switching operations. Furthermore, proactive RoCoF-based demand side load management techniques above 49Hz prove effective in reducing frequency deviation during the most severe events while avoiding LFDD over-shedding for smaller contingencies.
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