Physics-based modeling of power system components for the evaluation of low-frequency radiated electromagnetic fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system's EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter's components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

Physical dynamic simulation of shipboard power system components in a distributed computational environment

Shipboard power systems have different characteristics than the utility power systems. In the Shipboard power system it is crucial that the systems and equipment work at their peak performance levels. One of the most demanding aspects for simulations of the Shipboard Power Systems is to connect the device under test to a real-time simulated dynamic equivalent and in an environment with actual hardware in the Loop (HIL). The real time simulations can be achieved by using multi-distributed modeling concept, in which the global system model is distributed over several processors through a communication link. The advantage of this approach is that it permits the gradual change from pure simulation to actual application. In order to perform system studies in such an environment physical phase variable models of different components of the shipboard power system were developed using operational parameters obtained from finite element (FE) analysis. These models were developed for two types of studies low and high frequency studies. Low frequency studies are used to examine the shipboard power systems behavior under load switching, and faults. High-frequency studies were used to predict abnormal conditions due to overvoltage, and components harmonic behavior. Different experiments were conducted to validate the developed models. The Simulation and experiment results show excellent agreement. The shipboard power systems components behavior under internal faults was investigated using FE analysis. This developed technique is very curial in the Shipboard power systems faults detection due to the lack of comprehensive fault test databases. A wavelet based methodology for feature extraction of the shipboard power systems current signals was developed for harmonic and fault diagnosis studies. This modeling methodology can be utilized to evaluate and predicate the NPS components future behavior in the design stage which will reduce the development cycles, cut overall cost, prevent failures, and test each subsystem exhaustively before integrating it into the system.

Distributed Power balance and damping control for high power multiport LCL DC hub

This project is funded by European Research Council in FP7; grant no 259328, 2010 and EPSRC grant no EP/K006428/1, 2013.

Distributed Power balance and damping control for high power multiport LCL DC hub

This project is funded by European Research Council in FP7; grant no 259328, 2010 and EPSRC grant no EP/K006428/1, 2013.

Performance study of the Galway Bay wave energy test site floating power system

The Galway Bay wave energy test site promises to be a vital resource for wave energy researchers and developers. As part of the development of this site, a floating power system is being developed to provide power and data acquisition capabilities, including its function as a local grid connection, allowing for the connection of up to three wave energy converter devices. This work shows results from scaled physical model testing and numerical modelling of the floating power system and an oscillating water column connected with an umbilical. Results from this study will be used to influence further scaled testing as well as the full scale design and build of the floating power system in Galway Bay.

THE DESIGN OF A POWER SYSTEM FOR A WIRELESS SENSOR NETWORK FOR LONG-TERM OPERATION

Wireless sensor networks (WSNs) have shown wide applicability to many fields including monitoring of environmental, civil, and industrial settings. WSNs however are resource constrained by many competing factors that span their hardware, software, and networking. One of the central resource constrains is the charge consumption of WSN nodes. With finite energy supplies, low charge consumption is needed to ensure long lifetimes and success of WSNs. This thesis details the design of a power system to support long-term operation of WSNs. The power system’s development occurs in parallel with a custom WSN from the Queen’s MEMS Lab (QML-WSN), with the goal of supporting a 1+ year lifetime without sacrificing functionality. The final power system design utilizes a TPS62740 DC-DC converter with AA alkaline batteries to efficiently supply the nodes while providing battery monitoring functionality and an expansion slot for future development. Testing tools for measuring current draw and charge consumption were created along with analysis and processing software. Through their use charge consumption of the power system was drastically lowered and issues in QML-WSN were identified and resolved including the proper shutdown of accelerometers, and incorrect microcontroller unit (MCU) power pin connection. Controlled current profiling revealed unexpected behaviour of nodes and detailed current-voltage relationships. These relationships were utilized with a lifetime projection model to estimate a lifetime between 521-551 days, depending on the mode of operation. The power system and QML-WSN were tested over a long term trial lasting 272+ days in an industrial testbed to monitor an air compressor pump. Environmental factors were found to influence the behaviour of nodes leading to increased charge consumption, while a node in an office setting was still operating at the conclusion of the trail. This agrees with the lifetime projection and gives a strong indication that a 1+ year lifetime is achievable. Additionally, a light-weight charge consumption model was developed which allows charge consumption information of nodes in a distributed WSN to be monitored. This model was tested in a laboratory setting demonstrating +95% accuracy for high packet reception rate WSNs across varying data rates, battery supply capacities, and runtimes up to full battery depletion.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

The Power of the Synthetic Control Method

The synthetic control method (SCM) is a new, popular method developed for the purpose of estimating the effect of an intervention when only one single unit has been exposed. Other similar, unexposed units are combined into a synthetic control unit intended to mimic the evolution in the exposed unit, had it not been subject to exposure. As the inference relies on only a single observational unit, the statistical inferential issue is a challenge. In this paper, we examine the statistical properties of the estimator, study a number of features potentially yielding uncertainty in the estimator, discuss the rationale for statistical inference in relation to SCM, and provide a Web-app for researchers to aid in their decision of whether SCM is powerful for a specific case study. We conclude that SCM is powerful with a limited number of controls in the donor pool and a fairly short pre-intervention time period. This holds as long as the parameter of interest is a parametric specification of the intervention effect, and the duration of post-intervention period is reasonably long, and the fit of the synthetic control unit to the exposed unit in the pre-intervention period is good.

Kulmastabiilisuuden mallinnus

Työn tavoitteena oli kartoittaa vaihtoehtoisia menetelmiä perinteiselle aikatasossa tapahtuvalle kulmastabiilisuuden mallinnukselle käyttövarmuustarkastelussa. Vaihtoehtoisiin menetelmiin tutustuttiin kirjallisuuden avulla ja valittiin menetelmä testattavaksi pohjoismaisessa yhteiskäyttöjärjestelmässä. Vaihtoehtoisen menetelmän ominaisuusvaatimuksiin kuului nopeampi laskenta, luotettava stabiilien ja epästabiilien tilanteiden seulontakyky ja menetelmän antama indeksi stabiilisuus-/epästabiilisuusasteesta. Pääasiassa menetelmät, joihin tutustuttiin, arvioivat vain transienttia stabiilisuutta. SIME-menetelmä soveltui myös dynaamisen stabiilisuuden arviointiin. Suomessa voi dynaamisella stabiilisuudella olla tulevaisuudessa merkittävä rooli käyttövarmuustarkasteluissa. SIME-menetelmän toimivuutta testattiin osin yksinkertaistetulla Nordel-verkkomallilla, ja saadut tulokset olivat lupaavia. Menetelmä täytti uudelle menetelmälle asetetut vaatimukset, vaikka ongelmiakin esiintyi. Testauksessa käytetyn menetelmän edelleen kehittäminen ja menetelmän testaaminen täydellisellä verkkomallilla on suositeltavaa.

Otimização de controladores utilizando algoritmos genéticos para melhoria da capacidade de sobrevivência a afundamentos de tensão de aerogeradores de indução duplamente excitados

Na presente tese propõe-se uma metodologia de ajuste ótimo dos controladores do conversor interligado ao rotor de aerogeradores de indução duplamente excitados (DFIG), utilizando algoritmos genéticos (AG), com o objetivo de melhorar a segurança e a robustez do sistema elétrico de potência, permitindo que os aerogeradores DFIG participem da gestão técnica do sistema. Para garantir este objetivo, é utilizada uma estratégia de proteção do tipo “crow-bar” durante a falta, mantendo o conversor interligado ao rotor conectado à máquina. Imediatamente após a eliminação da falta, o “crow-bar” é desativado, e simultaneamente os controladores ótimos do conversor interligado ao rotor são acionados, previamente ajustados pelo AG, a fim de melhorar a capacidade de sobrevivência a afundamentos de tensão “ridethrough capability” e a margem de estabilidade global do sistema elétrico. Para validação da metodologia ótima desenvolvida foram realizadas simulações computacionais utilizando uma rede elétrica real, em três condições operacionais distintas.

A comparative study of the damping oscillation function of TCSC and UPFC

The main objective of this work is to analyze the ability of FACTS devices like TCSC and UPFC to damp low frequency oscillations and a POD controller is also included. A comparative study of damping effect of those devices IS carried out. The Power Sensitivity Model (PSM) is used to the representation of the electric power system. Sensibility analysis using the residue method shows the best place for the installation of FACTS and the procedure to determine POD parameters. ©2008 IEEE.

O modelo de injeção de potência do TCSC e sua aplicação no estudo da estabilidade a pequenas perturbações

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)