Transformers are essential components facilitating transmission and distribution of electric power. Energisation of transformers, however, can cause core operating at deep saturation region and thereby induce transient inrush currents of high magnitude and with rich harmonics. This can lead to undesirable effects including potential damage to the transformer itself, relay mal-operation, harmonic resonant overvoltages, and reduced power quality in the system (mainly in the form of voltage dips). This thesis investigates voltage dips caused by energising generator step-up (GSU) transformers and two types of generation connection are studied: one is a combine cycle gas turbine (CCGT) plant connected to a 400 kV transmission grid and the other is a large offshore wind farm connected to a 132 kV distribution grid. To carry out the investigation, detailed network models were developed in alternative transients program/electromagnetic transients program (ATP/EMTP) and validated with the help of field measurements. For the connection of generation in the transmission grid, deterministic assessment was conducted to comparatively analyse voltage dips caused by energising large GSU transformers under different energisation conditions and different network conditions; special attention was paid to the energisation cases involving sympathetic inrush between transformers by addressing its prolonging effects on voltage dips, with sensitivity studies further carried out to identify the key influential parameters. In addition, stochastic assessment was conducted by applying Monte Carlo method, which helps identify the dip frequency pattern and the likelihood of reaching the dip magnitude resulted from the commonly agreed worst case energisation condition; their sensitivities to the variation of circuit breaker closing time span, transformer core residual flux, system condition and the number of transformers being energized together were also investigated. Furthermore, possible cost-effective operational approaches to mitigate the voltage dips were explored and compared. For the connection of large offshore wind farm, voltage dips caused by energising wind turbine transformers under different scenarios were assessed; in particular, sympathetic inrush between wind turbine transformers were studied, and the energisation sequence resulting in less sympathetic inrush was deterministically identified and stochastically validated. The simulation results of deterministic studies indicate that, when carrying out energisation of a large GSU transformer in the transmission grid under the commonly agreed worst case energisation condition, the dip magnitude can reach 9.6% and the duration 2.7 seconds; moreover, when coupled with sympathetic inrush, the duration can be prolonged by 136%, lasting for 6.4 seconds. The sensitivity studies show that transformer core saturation inductance is the key parameter determining dip magnitude and transformer copper losses is the key parameter determining dip duration. Stochastic assessment of voltage dips shows that, out of 1000 stochastic dip events, less than 0.5% of the dips can reach the worst case dip magnitude and about 80% are of magnitudes less than 0.6 pu of the worst case dip magnitude; the dip frequency pattern is found to be insensitive to the circuit breaker closing time variation but can be considerably influenced by the residual flux distribution. In terms of mitigation measures, it was proven that, by adjusting tap changer position, applying static var compensator and even opening coupler circuit breaker in the substation, the degree of voltage dip especially the dip duration can be significantly reduced. Contrasting to those observed in the transmission grid, voltage dips resulted from energising wind turbine transformers in large offshore wind farms are of less concern; dip magnitudes are no more than 1% in the case of energising a stand-alone wind turbine transformer. However, sympathetic inrush between wind turbine transformers within one feeder was found to be significant and the energisation sequence resulting in less sympathetic inrush is to separately energise the wind turbine transformer from the one closest to the offshore platform to the one farthest away from the platform.

Nesta pesquisa, apresentam-se os principais eventos relacionados com a proteção de transformadores e sua correlação com os distúrbios de qualidade da energia elétrica (QEE). Neste sentido, foi desenvolvido um algoritmo que utiliza a transformada Wavelet (TW) e a lógica Fuzzy (LF) para classificar os eventos transitórios associados à proteção de transformadores. Estes eventos foram observados em um sistema elétrico de potência (SEP) simulado com a utilização do software Alternative Transients Program (ATP). Importa ressaltar que o sistema modelado apresenta transformadores ligados em paralelo, possibilitando o estudo de eventos decorrentes desta situação, como a energização solidária (Sympathetic Inrush). Por este SEP, modelado sobre parâmetros reais, foram simuladas várias situações transitórias, que provocam o aparecimento de correntes diferenciais, sendo estas direcionadas para análise do algoritmo desenvolvido. Afirma-se que, nos testes realizados, o algoritmo proposto apresentou um desempenho satisfatório perante as mais variadas situações a que foi submetido, identificando as causas das correntes diferenciais, sejam proporcionadas por defeitos ou por outras condições de operação aplicadas. / In this research, the main events related to the transformer protection and its correlation with the power quality disturbances (PQ) are presented. In this context, an algorithm based on Wavelet transform (WT) and Fuzzy logic (FL) was developed to classify the transient events associated with the transformer protection. These events were observed in an electrical power system (EPS) simulated using the Alternative Transients Program (ATP) software. It should be emphasized that the modeled system presents transformers connected in parallel, allowing the study of events of this situation, such as sympathetic inrush. For the simulated EPS, modeled based on real parameters, various transients situationswere simulated, causing the appearance of differentials currents which were directed to the analysis. The proposed algorithm showed a satisfactory performance tomany situations, identifying the causes of the differentials currents, either provided by faults or other operation conditions.

Nesta pesquisa, apresentam-se os principais eventos relacionados com a proteção de transformadores e sua correlação com os distúrbios de qualidade da energia elétrica (QEE). Neste sentido, foi desenvolvido um algoritmo que utiliza a transformada Wavelet (TW) e a lógica Fuzzy (LF) para classificar os eventos transitórios associados à proteção de transformadores. Estes eventos foram observados em um sistema elétrico de potência (SEP) simulado com a utilização do software Alternative Transients Program (ATP). Importa ressaltar que o sistema modelado apresenta transformadores ligados em paralelo, possibilitando o estudo de eventos decorrentes desta situação, como a energização solidária (Sympathetic Inrush). Por este SEP, modelado sobre parâmetros reais, foram simuladas várias situações transitórias, que provocam o aparecimento de correntes diferenciais, sendo estas direcionadas para análise do algoritmo desenvolvido. Afirma-se que, nos testes realizados, o algoritmo proposto apresentou um desempenho satisfatório perante as mais variadas situações a que foi submetido, identificando as causas das correntes diferenciais, sejam proporcionadas por defeitos ou por outras condições de operação aplicadas. / In this research, the main events related to the transformer protection and its correlation with the power quality disturbances (PQ) are presented. In this context, an algorithm based on Wavelet transform (WT) and Fuzzy logic (FL) was developed to classify the transient events associated with the transformer protection. These events were observed in an electrical power system (EPS) simulated using the Alternative Transients Program (ATP) software. It should be emphasized that the modeled system presents transformers connected in parallel, allowing the study of events of this situation, such as sympathetic inrush. For the simulated EPS, modeled based on real parameters, various transients situationswere simulated, causing the appearance of differentials currents which were directed to the analysis. The proposed algorithm showed a satisfactory performance tomany situations, identifying the causes of the differentials currents, either provided by faults or other operation conditions.

This thesis investigates the impact of resonant overvoltages and their origin. Series and parallel resonances are present in any electrical grid. The frequency of which this resonance occurs is called resonance frequency. For parallel resonance, which is mainly being studied in this thesis, a high impedance peak can be found at the resonance frequency. This impedance peak in conjunction with a harmonic rich current cause a kind of temporary overvoltages called resonant overvoltages. The harmonic content of the current is high following a fault clearing in the grid, due to transformer saturation. The resonance frequency is heavily dependent on the amount of reactance present in the grid, which entail that a change in reactance causes a change in the resonance frequency. The electromagnetic transient tool PSCAD has been used to investigate resonant overvoltages following transformer energization caused by faults and switching in Stockholm. Secondly, a model was created of a grid connecting off-shore wind power to the mainland via long AC submarine transmission cables. These cables, having a high capacitance, lower the resonance frequency. Faults in this model were simulated to investigate the phenomenon of resonant overvoltages in such a grid. This was especially interesting due to Swedens planned expansion of wind power in the Baltic sea. While resonant overvoltages were found in Stockholm they were not deemed significant due to their low magnitude and longevity. However, severe resonant overvoltages were found in the off-shore wind farm model. The worst resonant overvoltages had a maximum amplitude of the 2nd order harmonic voltage of 130 kV which, while eventually damped, were significant for up to 50 periods. Lastly, the phenomenon of an increased resonance frequency during the saturation of a transformer was studied. The most severe resonant overvoltages occured in a model where the frequency scans showed a resonance frequency of 98 Hz. Indicating, caution needs to be had during EMT-studies of resonant overvoltages while choosing what resonance frequency to study.