As modern power systems operate closer to the limits due to load growth and financial imperatives, voltage stability becomes a more important issue and there have been more incidents caused by voltage collapse. For example, there have been 11 outages affecting more than 4000MW between 1984 and 2000 in North America [1]. In power systems, load voltages decrease as the supplied loads increase until the maximum power transfer point is reached. The voltage will collapse if the load is increased above this limit. Therefore, it is important to monitor the loadability of a system to avoid voltage collapse. The loadability of a system can be calculated when the Thevenin impedance is available as the maximum power transfer occurs when the Thevenin impedance and the load impedance are the same in magnitude. This thesis suggests a method to estimate the Thevenin impedance of a system. ABB corporation suggests the Voltage Stability Predictor (VIP) method to estimate the Thevenin impedance, but there are problems with this method and it is not gaining popularity in industry. In this thesis, a method is suggested to estimate the Thevenin impedance by taking advantage of the existance of negative sequence components in the system. The concept of this method has been proved mathematically. Simulations were performed on simple systems and on the modified IEEE 13 bus power flow test case to verify the feasibility of the method and the results are promising. Then, the method was verified with field measurements for a 25kV substation. The voltages and currents were analyzed to estimate the Thevenin equivalent impedance of the power system and the results were compared with the design Thevenin equivalent impedance. The result confirms the viability of the method as the estimated Thevenin impedance matched the design value.

As modern power systems operate closer to the limits due to load growth and financial imperatives, voltage stability becomes a more important issue and there have been more incidents caused by voltage collapse. For example, there have been 11 outages affecting more than 4000MW between 1984 and 2000 in North America [1]. In power systems, load voltages decrease as the supplied loads increase until the maximum power transfer point is reached. The voltage will collapse if the load is increased above this limit. Therefore, it is important to monitor the loadability of a system to avoid voltage collapse. The loadability of a system can be calculated when the Thevenin impedance is available as the maximum power transfer occurs when the Thevenin impedance and the load impedance are the same in magnitude. This thesis suggests a method to estimate the Thevenin impedance of a system. ABB corporation suggests the Voltage Stability Predictor (VIP) method to estimate the Thevenin impedance, but there are problems with this method and it is not gaining popularity in industry. In this thesis, a method is suggested to estimate the Thevenin impedance by taking advantage of the existance of negative sequence components in the system. The concept of this method has been proved mathematically. Simulations were performed on simple systems and on the modified IEEE 13 bus power flow test case to verify the feasibility of the method and the results are promising. Then, the method was verified with field measurements for a 25kV substation. The voltages and currents were analyzed to estimate the Thevenin equivalent impedance of the power system and the results were compared with the design Thevenin equivalent impedance. The result confirms the viability of the method as the estimated Thevenin impedance matched the design value.

As modern power systems operate closer to the limits due to load growth and financial imperatives, voltage stability becomes a more important issue and there have been more incidents caused by voltage collapse. For example, there have been 11 outages affecting more than 4000MW between 1984 and 2000 in North America [1]. In power systems, load voltages decrease as the supplied loads increase until the maximum power transfer point is reached. The voltage will collapse if the load is increased above this limit. Therefore, it is important to monitor the loadability of a system to avoid voltage collapse. The loadability of a system can be calculated when the Thevenin impedance is available as the maximum power transfer occurs when the Thevenin impedance and the load impedance are the same in magnitude. This thesis suggests a method to estimate the Thevenin impedance of a system. ABB corporation suggests the Voltage Stability Predictor (VIP) method to estimate the Thevenin impedance, but there are problems with this method and it is not gaining popularity in industry. In this thesis, a method is suggested to estimate the Thevenin impedance by taking advantage of the existance of negative sequence components in the system. The concept of this method has been proved mathematically. Simulations were performed on simple systems and on the modified IEEE 13 bus power flow test case to verify the feasibility of the method and the results are promising. Then, the method was verified with field measurements for a 25kV substation. The voltages and currents were analyzed to estimate the Thevenin equivalent impedance of the power system and the results were compared with the design Thevenin equivalent impedance. The result confirms the viability of the method as the estimated Thevenin impedance matched the design value. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-07-12T11:34:57Z No. of bitstreams: 1 henriqueluismoreiramonteiro.pdf: 6497394 bytes, checksum: e4ba6289e2d5a09f203b42d5461ff1b1 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-07-17T11:53:38Z (GMT) No. of bitstreams: 1 henriqueluismoreiramonteiro.pdf: 6497394 bytes, checksum: e4ba6289e2d5a09f203b42d5461ff1b1 (MD5) / Made available in DSpace on 2018-07-17T11:53:38Z (GMT). No. of bitstreams: 1 henriqueluismoreiramonteiro.pdf: 6497394 bytes, checksum: e4ba6289e2d5a09f203b42d5461ff1b1 (MD5) Previous issue date: 2018-04-04 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Neste trabalho é proposto um método para estimar a impedância de maneira invasiva, utilizando uma estrutura com controle de distúrbio, filtro para eliminar os componentes harmônicos contidos na rede e um interpolador em caso de variação de frequência. A impedância é um parâmetro importante para a análise da estabilidade de uma rede elétrica, pois através de sua estimação pode-se verificar, por exemplo, se há a presença de ressonância. Para provocar os distúrbios nos sinais de tensão e corrente utiliza-se o Sinal da Gaussiana Modulada (SGM), que pode ter seu decaimento controlado pelos parâmetros da função. Em relação à presença dos componentes harmônicos de fundo, que influenciam na estimação da impedância, é proposta uma versão do filtro Sliding Window Recursive Discrete Fourier Transform (SWRDFT), para estimar e eli-minar esses componentes, com o objetivo de permanecer somente o sinal de distúrbio. Sobre o desvio de frequência, outra questão que compromete a estimação da impedância, é proposta uma estrutura de interpolação, utilizando o método de Lagrange. A função da interpolação é estabelecer a sincronização dos sinais de corrente e tensão antes de serem processados para determinar o valor da impedância. Para validar os resultados, são realizados testes em redes no Simulink, RTDS, dSPACE e utilizando em um circuito experimental. Para os resultados são considerados Sistemas Elétricos com ressonância, com presença de componentes harmônicos de fundo e com variação de frequência. Para todos os casos a estimação obteve resultados satisfatórios. / This work proposes a method to estimate the power grid impedance in an invasive form, using a disturbance control structure, a filter to eliminate the harmonic components contained in the power grid and an interpolator in case of frequency variation. The impedance is an important parameter for the power grid stability analysis because through its estimation it can be verified, for example, if there is the presence of resonance. To insert the disturbances in the voltage and current signals, the Gaussian Modulated Signal (GMS) is used, which may have its decay controlled by the function parameters. Regarding the presence of the harmonic components, which influence the estimation of impedance, a version of the Sliding Window Recursive Discrete Fourier Transform (SWRDFT) is proposed to estimate and eliminate these components in order to remain only the disturbance signal. Regarding the frequency deviation, another issue that affects the impedance estimation, an interpolation structure is proposed, using the Lagrange method. The function of the interpolation is to establish the synchronization of the current and voltage signals before being processed to determine the impedance value. To validate the results, tests with grids on Simulink, RTDS, dSpace and using an experimental circuit are performed. Results consider Electrical Systems with resonance, with the presence of background harmonic components and frequency variation. For all cases, the estimation results were satisfactory.

Modern digital energy meters are installed between the distribution network and customers. Network operators and customers can use those meters to monitor electrical parameters, i.e., voltages and currents and to calculate statistics such as RMS value, fundamental Fourier component, etc. Observation of distribution network impedance can reveal problems in the system, such as broken neutral conductors. This project proposes a loop-theory method using variables from smart meters to estimate the network impedance, therefore giving the possibility of conductor fault detection. Specifically, loop theory uses the distribution network terminal’s voltage and current measured by smart meters and selects cases where the load appears to have varied significantly, so that there is a change of current together with a resulting change of voltage. For selected cases, the methods calculate different loop impedance and finally address single conductor impedance by the least-squares method. The project validates the proposed method by simulation, and with recorded data from a real house with varied known neutral-conductor impedance. Based on that, this method’s limitation and possible improvement are discussed for further study. / Moderna digitala energimätare används mellan distributionsnätet och kunderna. Sådana mätare kan användas för att övervaka elektriska parametrar, dvs. spänningar och strömmar och beräkna statistik som RMS-värde, grundläggande Fourier-komponent etc. Observation av distributionsnätets impedans kan avslöja problem i systemet, såsom neutrala ledare med brott eller hög impedans (’nollfel’). Detta projekt föreslår en loopteorimetod med hjälp av variabler från smarta mätare för att uppskatta nätverksimpedansen, vilket ger möjlighet till detektering av ledningsfel. Specifikt använder loopteorin spänning och ström mätt med genom smarta mätare, och väljer fall där belastningen verkar ha varierat avsevärt så att det sker en förändring av strömmen tillsammans med en resulterande spänningsförändring. För valda fall beräknar metoderna impedanser i olika slingor av nätets ledare, och slutligen gör en estimering av impedansen hos enskilda ledare genom minstakvadratmetoden. Projektet validerar den föreslagna metoden genom simulering, och med inspelade data från ett riktigt hus med varierad känd neutral ledare impedans. Baserat på detta diskuteras denna metods begränsning och möjliga förbättring för vidare studier.

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-03-27T15:28:12Z No. of bitstreams: 1 ramonreissiqueiradeoliveira.pdf: 4744081 bytes, checksum: dbce2e20c42a3bc456ad52a2096349ec (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-03-27T17:52:51Z (GMT) No. of bitstreams: 1 ramonreissiqueiradeoliveira.pdf: 4744081 bytes, checksum: dbce2e20c42a3bc456ad52a2096349ec (MD5) / Made available in DSpace on 2018-03-27T17:52:51Z (GMT). No. of bitstreams: 1 ramonreissiqueiradeoliveira.pdf: 4744081 bytes, checksum: dbce2e20c42a3bc456ad52a2096349ec (MD5) Previous issue date: 2017-12-18 / Uma rede com vários geradores distribuídos conectados pode melhorar a eficiência energética e reduzir o impacto negativo na rede elétrica. Um problema que surge é quando o fornecimento de energia principal é desconectado do sistema, diz-se então que ocorreu um ilhamento. Essa situação é indesejada, pois pode provocar problemas em termos de qualidade de energia, segurança, tensão e estabilidade de frequência. Esse trabalho tem por finalidade identificar o ilhamento pela variação da impedância do sistema, utilizando um método proposto que utiliza uma técnica de estimação de impedância através da injeção de um pequeno sinal na tensão de saída do gerador distribuído. Os testes realizados mostraram que quanto maior for a contribuição do inversor na potência fornecida para a carga, melhores são os valores estimados de impedância e na presença de dois inversores, os sinais injetados por cada um deles devem estar em frequências harmônicas o mais distante possível, para melhores resultados na estimação da impedância. Além disso, quando o fluxo de potência da rede para a carga é próximo de zero, o método foi capaz de identificar o ilhamento mesmo cosem atuação dos relés de tensão e frequência. O ilhamento é possível de ser identificado em aproximadamente 0,5 s em todos os casos testados, estando dessa forma dentro do tempo máximo estabelecido nas normas. / A grid with multiple distributed generators can improve energy efficiency and reduce the negative impact on itself. One problem that occurs is when the main power supply is disconnected from the system, this is called islanding. This is undesirable because it can cause problems in terms of power quality, safety, voltage and frequency stability. This work aims to identify the islanding by the system impedance variation, using a proposed method that uses an impedance estimation technique, injecting a small signal into the output voltage of the distributed generator. The tests performed showed as higher the contribution of the inverter to the power supplied to the load as better the estimated impedance values. In the presence of two inverters, the signals injected by each of them must be in harmonic frequencies, for better impedance estimation results. In addition, when the utility energy flow to the load is close to zero, the method was able to identify the same island as the voltage and frequency relays. The island can be identified in approximately 0.5 s in all cases tested, thus being within the maximum time limit set in the standards.

No description available.

蓄電池は携帯機器，電気自動車をはじめ，自然エネルギー有効利用に至るまで広範囲に利用され，その重要性はますます高まっている。これら機器の使用時間や特性は蓄電池の特性に大きく依存することから，電池自体の特性改善に加え，劣化を診断してより効率的に電池を運用することが求められている。本論文は，非線形情報処理を得意とする人工知能を用いた2次電池の劣化診断法を開発し，エネルギーの有効利用に資する技術を確立した。機器動作時の電池電圧・電流波形と電池劣化特性との関連性を，人工知能を用い学習することにより，機器稼働時に電池の劣化を診断することができる。なお，この関連性は非線形で複雑であるが，非線形分析を得意とする人工知能は劣化診断に適している。学習には時間を要するものの，診断は短時間になし得ることから，提案法は稼働時劣化診断に適している。本論文では，この特徴を生かし，電池の等価回路（ECM）を導出し，充電率（SOC），容量維持率（SOH）を推定している。また，本論文では現在産業応用分野で用いられている，リチウムイオン電池，ニッケル水素電池，鉛蓄電池を対象とし，提案法はあらゆる電池使用機器に応用可能である。また，提案法を電池状態監視装置（BMU）や，マイコンなどを用いた組み込みシステムに応用可能とし，実証している。以上のことから，本論文は，新たな蓄電池の劣化診断法の確立し，その有効性を確認している。 / The importance of rechargeable batteries nowadays is increasing from the portable electronic devices and solar energy industry up to the development of new EV models. The rechargeable batteries have a crucial role in the storage system, mostly in mobile applications and transportation, because the period of its usage and the flexibility of the function are determined by the battery. Due to the black box approach of the ANN it is possible to connect the complex physical phenomenon with a specific physical meaning expressed with a nonlinear logic between inputs and output. Using specific input data to relate with the desired output, makes possible to create a pattern connection with input and output. This ability helps to estimate in real time the desired outputs, behaviors, phenomes and at the same time it can be used as a real time diagnosis method. / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University

One of the main challenges in wireless power transfer (WPT) devices is performance degradation when the receiver’s position and characteristics vary. The variations in the system parameters such as load impedance and coupling strength in WPT devices affect performance characteristics such as output voltage and power. When the system parameters are different from the optimal operating conditions, the performances are degraded. Therefore, the load impedance and coupling strength must be monitored to do the necessary optimization and control. However, such control approaches require additional sensing circuits and a data communication link between transmitter- and receiver-sides. This study proposes a new machine learning (ML) assisted WPT system that predicts the power delivered to the receiver by only using measurements at the transmitter-side. In addition, a method is also proposed to estimate load impedance and coupling coefficient using machine learning approach. We study what parameters measurable at the transmitter-side can be used to predict the output power delivered to receivers at variable load impedance and coupling strengths. In the proposed method, the output power of an inductor-capacitor-capacitor (LCC)-Series tuned WPT system is successfully predicted only using the measured root-mean-square (RMS) of the input current. Random forest algorithm has shown best accuracy to estimate the output power based on transmitter-side parameters only. The proposed approach is experimentally validated using a laboratory prototype. Harmonic components of the input current are used to assess the load impedance and coupling coefficient successfully. Multi-output regression has the highest accuracy for estimating the load impedance and coupling coefficient. The proposed ML algorithm is also used to classify the turn-on and -off regimes to ensure high-efficient operation. / En av de viktigaste utmaningarna med trådlösa kraftöverföring enheter är degraderingen av prestandan när mottagarens position och egenskaper varierar. Variationerna av systemets parametrar, såsom belastningsmotstånd och kopplings styrka i WPT-anordning, påverkar prestanda egenskaperna såsom spänning och effekt. När system parametrarna skiljer sig från de optimala drifts förhållandena, försämras prestandan. Därför måste luftmotståndet och kopplings styrkan övervakas, för att göra nödvändig optimering och kontroll. Sådana styrmetoder kräver emellertid ytterligare avkännings kretsar, och en data kommunikationslänk mellan sändar- och mottagarsidan. Denna studie föreslår ett nytt maskininlärning assisterat WPT-system, som förutsäger kraften som levereras till mottagaren genom att endast använda mätningar på sändarsidan. Dessutom föreslås en metod för att detektera belastningsimpedans och kopplings koefficient med användning av maskin inlärningsmetoder. Vi studerar vilka parametrar som är mätbara på sändarsidan och som kan användas för att förutsäga utgången effekten som levereras till mottagare vid varierande belastningsmotstånd och kopplings nivåer. I den föreslagna metoden förutses framgångs effekten för ett induktor-kondensator-kondensator LCCserie avstämt WPT-system endast framgångsrikt med hjälp av det uppmätta effektivvärdet för ingångs strömmen. Slumpmässig skogsalgoritm har visat exceptionell noggrannhet för att uppskatta uteffekten endast baserat på sändarsidans parametrar. Den föreslagna metoden valideras experimentellt med användning av en laboratorium prototyp. Harmoniska komponenter i ingångs strömmen används för att framgångsrikt bedöma last motståndet och kopplings koefficienten. Multi-utgångsregression har verkat vara mycket exakt för att uppskatta belastningsimpedans och kopplingskoefficient. Den föreslagna maskininlärning algoritmen används också för att klassificera start-och-off-regimer för att säkerställa hög effektiv drift.