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.

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.

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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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.

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.

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.

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.

With an accelerated inclusion of renewable energy generators in the power system, the inertia support traditionally provided by conventionally powered synchronous generators is lagging, and power system stability is reducing. This grid-supporting behavior will now have to be provided by the power converters of renewable energy sources with the help of power electronics. Grid forming control refers to the idea of the converter’s ability to set its frequency and voltage by means of emulating similar characteristics as that of conventional synchronous generators. Most of the protection and control studies on grid forming control for wind turbines have been done using a simple power system model containing the generator and an infinite AC bus and very less insight is available for grid forming generators in a realistic power system. This study aimed to apply the grid forming control strategy on DFIG (Type-3) and full converter wind turbines (Type-4). For this, the MIGRATE benchmark models in RSCAD/RTDS were used for the comparison of the key power indicators for both grid forming and grid following controlled modes. This was followed by the development and validation of the grid forming controller as a black-box model using IntervalZero and RTDS software in the loop setup (SIL).

Integrating renewable offshore wind generation into global power grids is a critical issue in the energy industry. Modular Multilevel Converter (MMC)-based High Voltage Direct Current (HVDC) grids are the most effective and promising technical solution for the new offshore wind energy power system connections. These grids offer scalability, controllability, and reliability advantages, but their stable and compliant operation requires implementing MMC control strategies and controllers. This thesis investigates the intricacies of HVDC technologies, focusing on MMC control strategies and controllers. The research explores grid following and grid forming converter control strategies, essential for ensuring stable and compliant operation of MMC-based HVDC grids.
The research elaborates on the Model Predictive Control (MPC), which is a promising control strategy for MMC-based HVDC grids. The MPC controller makes the control strategies respond faster, emphasizing constraints
and cost functions. Furthermore, a comparative analysis of Proportional Integral (PI)-based and MPC-based
controllers is conducted across various scenarios, highlighting the advantages of MPC-based controllers over
PI-based controllers regarding response time and stability.
Lastly, a large stability analysis is conducted using the direct Lyapunov method to evaluate the effectiveness of the control strategies and controllers during transient events. This analysis provides insights into the stability and performance of MMC-based HVDC grids under different operating conditions and disturbances.
This thesis illustrates the capabilities of grid-forming control strategy through Model Predictive controllers for
FPGA-based MMC-MTDC networks on RSCAD/RTDS®. The outcomes of this thesis contribute to advancing
HVDC technologies and control strategies, with implications for enhancing the stability and efficiency of MMC-based HVDC grids. The findings of this thesis have significant potential in the energy industry, particularly in integrating renewable offshore wind generation into global power grids.

This thesis investigates and compares the performance of HVDC protection algorithms in terms of their sensitivity, selectivity, speed, and robustness. The threshold determination process for each algorithm has been described in detail as well. Each algorithm is tested under various fault resistances, and fault distances to test the sensitivity of the algorithm. The trip time for each case in each algorithm is monitored to analyze the speed of the algorithm. Various external faults have been simulated to test the selectivity of the algorithm. Lastly, the resilience of each algorithm against white noise has been tested. Furthermore, the effect of varying the sampling frequency and the inductance of the current limiting inductors on each algorithm is investigated. The HVDC protection algorithms discussed are - current differential deviation-based protection, ROCOV-based protection, ROCOC-based protection, and DC reactor voltage change rate-based protection. All protection algorithms have been implemented in the PSCAD environment. The noise resilience analysis for each algorithm has been performed in MATLAB.

Busbars are one of the most crucial components in the electricity grid and, as such, must always be protected against all types of faults.
The busbar differential protection is a protection scheme typically utilized to protect the busbar system in high-voltage substations. Nevertheless, due to the vast number of substations in the distribution level and the high cost of differential busbar protection, DSOs try to implement more cost-effective protection schemes for the busbars. This includes using various communication-based protection schemes, such as the reverse-blocking scheme that Stedin implements. However, due to impedance grounding, the single-phase-to-ground short circuit current can reach small values in magnitude in medium voltage distribution grids, making detecting it more challenging for these protection schemes. That is the problem that Stedin experiences in its network.
In this thesis, a novel communication-based protection scheme is proposed as a solution to this problem. The protection scheme utilizes the IEC 61850 standard and the currently available infrastructure Stedin owns. The scheme can be considered a distributed protection scheme. The grid is modeled in RTDS, and a HiL simulation is carried out to test the protection scheme. The extensive simulations show that this scheme can detect single-phase-to-ground busbar faults in impedance earthed networks. Some limitations of the proposed scheme are also seen in the simulation results. Furthermore, a centralized approach for busbar protection is discussed. Two algorithms are developed based on GOOSE and SV messages, respectively. HiL simulations are carried out for these centralized algorithms too. The advantages and the considerations for implementing centralized protection are discussed. These findings can serve as a basis for further research for Stedin in the domain of centralized protection.

With the replacements of coal and nuclear plants with renewable energy sources such as Type-3 and Type-4 wind turbines and photovoltaic system, the fault current levels of the electrical power system become lower. This leads to a weakened ability of the commercial distance relays to detect fault currents. Therefore, new fault detection algorithms have been developed based on different approaches with the intention of raising the ability to detect faults under different circumstances. Among them, Stockwell Transform has been proved to be a useful tool to determine the occurrence of faults. This thesis presents an FPGA implementation of one of the newly developed S-Transform-based fault detection system on Zynq device. The conceptual methods of building an IEC communication interface to connect the system to an RTDS are investigated.
The algorithm on hardware is implemented in fixed-point representation, fully parameterized, and fully pipelined with the operation frequency at 100MHz. The final implementation is able to provide the result within 570ns. The hardware implementation of the S-Transform-based fault detection system is tested with simulations proving it can perform identically with the MATLAB model of itself.

The growing demand for electricity and the importance of decarbonization have forced to transition from fossil fuels to sustainable sources of energy like wind and solar. Currently, the universal power mix remains dominated by fossil fuels but plans are in motion to achieve the target set for the upcoming years. It involves grid expansion and the addition of new elements in the form of Distributed Energy Resources(DERs). This has an influence on the performance of the complete power system. To allow an increasing penetration level of
DG(Distributed Generations) without causing protection problems or unacceptable power flows and fault levels, the impact of DG has to be researched for a secured future grid.
The protection system of the power system is an aspect that will be significantly affected by the continuous integration of Distributed generation sources. For this reason, it is crucial to develop and validate smart protection solutions for future power systems in order to avoid catastrophic blackouts. In order to overcome the shortcomings, Synchrophasor systems can be used for real-time wide area protection and control. The real-time implementation reflects a smart protection scheme, using smart hardware such as a Phasor measurement Unit (PMU). By developing a suitable algorithm that can be used for decision-making
in case of an event on the transmission lines. It coherently helps in faster restoration of the transmission lines operation. Smart protection solutions will help in strengthening the protection system and will allow more flexibility in the coming years.

As a power system evolves in size and complexity due to energy transition, the focus on the stability of the power system becomes more imperative than ever. Power system stability is tested when the system is subjected to large disturbances. Consequently, a conventional protection scheme is always deployed to take quick and automatic actions based on localized measurements, to restore the power system to a steady operating state. However, in many cases, further remedial actions by the system operator are necessary to avoid cascading failures and eventual instability problems. The introduction of phasor measurement units in the form of WAMS has led to improved awareness and
hence, better, capability to take remedial actions. In particular, the vast amount of data provided by the PMUs have led to the development of data-driven machine learning applications to aid the system operator in maintaining stability. One such application is power system event classification. In general, event classification is achieved using supervised and unsupervised methods. A review of pioneering literature reveals that offline models trained using both these methods can achieve a high order of classification accuracy. However, in a realistic, online setting with streaming PMU data, there is a possibility
of new, unknown events appearing in the data stream. In such a case, Offline
models which are trained on a limited number of known classes are unable to adapt to new class data. Therefore, there is a necessity for event learning applications that are capable of incrementally identifying new classes that appear in the PMU data stream. Hence, this thesis proposes the event clustering algorithm which performs in two stages – label correction stage and new class labeling stage. In the first stage, the algorithm corrects the class labels predicted by a supervised model, and flags and collects new incoming event instances through a shape-based similarity measure, i.e. DTW measure. In the subsequent second stage, it incrementally clusters the collected new event instances using Time-Series k-means clustering, where the hyperparameter of the number of clusters is automatically determined using a silhouette score clustering metric. The results of this algorithm show successful detection of new power system events with high classification accuracy. Also, final improvements are suggested to overcome certain drawbacks of the algorithm listed in the thesis.

Induction motors have a significant role in every aspect of modern living. They are extensively used in every industry because of their robust construction, easy operation, controllable and adaptable features. Therefore, occurrence of faults in these machines are a major concern. The protection schemes implemented in a network plays an important role in the safe operation of the machine. The key component of common protection schemes is a relay that senses abnormalities in the network and separates the faulty section from the healthy network. Large faults such as phase faults, phase-to-phase faults are easily detected as they impact the whole network. However, commonly occurring faults such as stator winding faults, bearing faults, etc. are difficult to detect using the standardised protection schemes. Stator winding faults create localised heating that can rapidly incite phase faults. Thus, additional protection schemes are required to detect them in time. This thesis focuses on modelling and simulation of stator inter-turn faults in an induction motor using Electromagnetic Transient Program - Alternative Transients Program (EMTP-ATP) platform; dynamic testing of a chosen relay at various fault severities and fault resistances. Finally, optimised settings of the chosen relay are suggested for a given medium power induction motor and the results are discussed.

Overhead power lines play a key role in the transmission and distribution of electrical power. Traditionally, the operating limits of these overhead lines are fixed and determined through static line rating. These limits are designed under conservative conditions such as high loads and extreme weather scenarios. However, the global energy demand is expected to increase substantially in a few decades. Furthermore, there will be higher levels of penetration of intermittent renewable generation in the power system due to energy transition in the future. In this thesis, a Dynamic Line Rating (DLR) method is developed to enable the determination of the varying operating limits of the overhead lines. It is realized by calculating the maximum allowable current for the line considering the real-time monitored electrical and weather quantities while meeting the requirements for the design and security criteria of the line. This is a more economical and feasible solution to improve the existing power system compared to constructing additional infrastructure. This thesis aims to develop a real-time dynamic line monitoring system by utilizing Phasor Measurement Unit (PMU) data for a 50kV distribution grid. The Real-Time Digital Simulator(RTDS) is used with an interface to MATLAB to realize the DLR model at computational speeds equivalent to real-time operations. A parametric sensitivity analysis is conducted to understand the influence of each parameter in the DLR model and its working. Case studies are conducted by using the DLR model on the 50kVdistribution grid, which showed an increase of 20% on the line ampacity. Lastly, a comparative analysis of the DLR model and the P341 MiCOM DLR relay results are performed by applying RTDS Hardware-in-the-loop (HIL) testing. The results of the DLR model are found to be in accordance with those obtained by the relay which also validates the model. Finally, recommendations and future work are proposed such as DLR implementation for cables using PMU data.

State estimation (SE) is a crucial tool for power system state monitoring since the control center requires a process to deal with a large number of imprecise measurements. Several SE methods have been applied and developed for the electric power system in the transmission level in the past several decades. Meanwhile, SE for the distribution level remained in the background for a long time since the distribution networks were mainly radial with uni-directional power flows, making classical monitoring and control functions sufficient. Recently, due to the liberalization of the energy market, growing penetration of distributed generation, mainly renewable energy sources, and distributed energy resources such as electric vehicles, the distribution system has been gradually changing from passive into active grids. This requires more sophisticated monitoring and control of the distribution network via a distribution management system (DMS) to ensure optimal integration and maximize the grid hosting capacity. Since one of the key functions of DMS for real-time operation is the SE procedure, this calls for the following: (i) development of SE techniques for the distribution level, so-called distribution system state estimation (DSSE); (ii) more deployment of time-synchronized devices like phasor measurement units (PMU) that can directly measure and acquire accurate and time-aligned phasors with typical refresh rates up to 20-60 times per second.

Two types of DSSE algorithms were developed and implemented on the real-life 50 kV ring distribution grid composed of PMU devices by using the real-time simulation platform. The first is a static approach. The problem is formulated as a WLS problem to be solved based on the iterative Newton method, known as static state estimation (SSE). The second is a dynamic approach, which is more advanced, known as the forecasting-aided state estimation (FASE). It is one of the particular applications of the dynamic state estimation (DSE) concept based on the quasi-steady-state operating conditions. The dynamic formulation is solved using the extended Kalman filter (EKF) technique. This research aims to implement distribution system state estimation (DSSE) algorithms coupled with the auxiliary function, the so-called anomaly detection discrimination and identification (ADDI), into the distribution network. Both normal and abnormal operation scenarios of the power system are simulated to validate the algorithms.

The results reveal that the FASE is superior to the SSE algorithm in terms of estimation accuracy and computational time under normal operating conditions. However, under abnormal conditions, if there is no ADDI module, the performances of both algorithms are degraded significantly due to erroneous measurements. The FASE algorithm loses the system states' trajectory when sudden load change occurs. These issues point out the necessity of using the ADDI module against possible disturbances in real-life networks. In the end, the results show that the proposed FASE algorithm coupled with the ADDI module can accurately estimate the states under both normal and abnormal operations. One significant contribution is that the proposed algorithm can perform adequately fast so that it can process every high-speed measurement from PMU devices.

Intelligent Electronic Devices (IEDs) serve as the foundation of substation automation system. Many testing cases have discussed the performance of implementing IEC 61850 in IEDs manufactured by different vendors. However, the procedures of configuring an IED and mapping it with the power network model are not summarized. This project aims to provide the configuring procedures of a distance relay using IEC 61850 protocols, and test if the relay can correctly operate a circuit breaker modelled in Real Time Digital Simulator (RTDS). The communication between relay and circuit breaker is realized by GOOSE, SV and MMS services embedded in the GTNET card. Two testing cases are performed to illustrate that the closed-loop testing using IEC61850-configured relay is feasible in RTDS environment. The thesis is developed as guidelines for future lab work and teaching materials.

Today, 60% of the European mainline railway network is electrified with 80% of total traffic. It will further increase driven by The Trans-European Transport Network (TEN-T) and sustainability initiatives. As electricity consumption by railway networks increases, quantification of rail transport’s actual energy consumption is essential. Currently, railways’ energy consumption is measured at the supply side, i.e., the grid, which includes the network’s losses. This measurement does not give actual energy consumption. The European Union demanded an on-board energy measurement system for railways from 2019 onward.

The existing energy measurement systems designed for transmission and distribution networks are not suitable for railway applications due to the harsh conditions. The voltage and current signals are highly distorted and need a more sophisticated measurement system. The energy measurement can be divided into current measurement, voltage measurement, and energy calculation. This thesis project is part of the ongoing research in the current measurement for the on-board energy measurement system focusing on the DC current measurement.

The primary objective is to measure the energy dissipated during braking of the train. Therefore, we need to measure the current flowing through the braking rheostat during the braking of the train. This current measurement is difficult due to the fast switching of high current (in order of 500 A-600 A) termed as chopped current.

VSL has developed a test setup to measure the chopped current flowing through the braking rheostat. The test setup is modified to eliminate distortions and achieve the project requirement of 600 A current measurement. Intermediate tests are performed during the modification to analyze the components’ performance. Finally, the modified setup is tested up to load current of 600 A, and uncertainty calculation performed on the measurement results.