Non-invasive identification of turbogenerator parameters from actual transient network data

Synchronous machines are the most widely used form of generators in electrical power systems. Identifying the parameters of these generators in a non-invasive way is very challenging because of the inherent non-linearity of power station performance. This study proposes a parameter identification method using a stochastic optimisation algorithm that is capable of identifying generator, exciter and turbine parameters using actual network data. An eighth order generator/turbine model is used in conjunction with the measured data to develop the objective function for optimisation. The effectiveness of the proposed method for the identification of turbo-generator parameters is demonstrated using data from a recorded network transient on a 178 MVA steam turbine generator connected to the UK's national grid

Обзор методов определения параметров моделей синхронных генераторов

A synchronous generator is one of the key elements of any power system, having a significant impact on the stability and reliability of consumers’ power supply. Nowadays, the power systems emergency and operational control issues are being solved using computational models, the parameters whereof are determined using the reference data, or the data obtained during testing. High dependence of the models’ parameters on various external factors leads to a significant decrease in the accuracy of solving the issues of emergency and operational control. Identification based on the traditional telemetry systems or synchrophasor measurements is used to improve the accuracy of parameters of the power systems’ computational models. The purpose of this research lies in a meta-analysis of the available studies aimed at developing a methodology for determining parameters of a synchronous generator on the basis of measurement data. Russian and foreign studies were analyzed and grouped to achieve this goal. After that, for each group, advantages, disadvantages, and the area of application were identified. As a result, it is shown that the existing methods for determining parameters of synchronous generators based on measurement data cannot adapt to the source dataset and also require significant computing power. As a way to overcome these shortcomings, an adaptive model of a synchronous machine is proposed.Синхронный генератор является одним из основных элементов электроэнергетической системы, оказывающих существенное влияние на устойчивость и надёжность электроснабжения потребителей. В настоящее время задачи противоаварийного и режимного управления энергосистемами решаются на основе математических моделей, параметры которых задаются с помощью паспортных данных или данных, полученных при испытаниях. Высокая зависимость значений параметров математических моделей от внешних факторов ведёт к значительному снижению точности анализируемых процессов. Для повышения точности параметров математических моделей энергосистем применяются идентификация на основе измерений, полученных с помощью традиционных систем телеметрии или векторных измерений. Целью данной статьи является проведение метаанализа существующих исследований, направленных на разработку методики определения параметров синхронного генератора по данным измерений. Для достижения поставленной цели были проанализированы и сгруппированы как российские, так и зарубежные исследования. Затем для каждой группы были выявлены достоинства, недостатки, а также область применения. В результате было показано, что существующие методики определения параметров синхронных генераторов по данным измерений не способны подстраиваться к набору исходных данных, а также требуют значительных вычислительных мощностей. В качестве способа преодоления указанных недостатков предлагается адаптивная модель синхронной машины

Wind Power

This book is the result of inspirations and contributions from many researchers of different fields. A wide verity of research results are merged together to make this book useful for students and researchers who will take contribution for further development of the existing technology. I hope you will enjoy the book, so that my effort to bringing it together for you will be successful. In my capacity, as the Editor of this book, I would like to thanks and appreciate the chapter authors, who ensured the quality of the material as well as submitting their best works. Most of the results presented in to the book have already been published on international journals and appreciated in many international conferences

In search of the optimal acoustic features for statistical parametric speech synthesis

In the Statistical Parametric Speech Synthesis (SPSS) paradigm, speech is generally represented as acoustic features and the waveform is generated by a vocoder. A comprehensive summary of state-of-the-art vocoding techniques is presented, highlighting their characteristics, advantages, and drawbacks, primarily when used in SPSS. We conclude that state-of-the-art vocoding methods are suboptimal and are a cause of significant loss of quality, even though numerous vocoders have been proposed in the last decade. In fact, it seems that the most complicated methods perform worse than simpler ones based on more robust analysis/synthesis algorithms. Typical methods, based on the source-filter or sinusoidal models, rely on excessive simplifying assumptions. They perform what we call an "extreme decomposition" of speech (e.g., source+filter or sinusoids+ noise), which we believe to be a major drawback. Problems include: difficulties in the estimation of components; modelling of complex non-linear mechanisms; a lack of ground truth. In addition, the statistical dependence that exists between stochastic and deterministic components of speech is not modelled. We start by improving just the waveform generation stage of SPSS, using standard acoustic features. We propose a new method of waveform generation tailored for SPSS, based on neither source-filter separation nor sinusoidal modelling. The proposed waveform generator avoids unnecessary assumptions and decompositions as far as possible, and uses only the fundamental frequency and spectral envelope as acoustic features. A very small speech database is used as a source of base speech signals which are subsequently \reshaped" to match the specifications output by the acoustic model in the SPSS framework. All of this is done without any decomposition, such as source+filter or harmonics+noise. A comprehensive description of the waveform generation process is presented, along with implementation issues. Two SPSS voices, a female and a male, were built to test the proposed method by using a standard TTS toolkit, Merlin. In a subjective evaluation, listeners preferred the proposed waveform generator over a state-of-the-art vocoder, STRAIGHT. Even though the proposed \waveform reshaping" generator generates higher speech quality than STRAIGHT, the improvement is not large enough. Consequently, we propose a new acoustic representation, whose implementation involves feature extraction and waveform generation, i.e., a complete vocoder. The new representation encodes the complex spectrum derived from the Fourier Transform in a way explicitly designed for SPSS, rather than for speech coding or copy-synthesis. The feature set comprises four feature streams describing magnitude spectrum, phase spectrum, and fundamental frequency; all of these are represented by real numbers. It avoids heuristics or unstable methods for phase unwrapping. The new feature extraction does not attempt to decompose the speech structure and thus the "phasiness" and "buzziness" found in a typical vocoder, such as STRAIGHT, is dramatically reduced. Our method works at a lower frame rate than a typical vocoder. To demonstrate the proposed method, two DNN-based voices, a male and a female, were built using the Merlin toolkit. Subjective comparisons were performed with a state-of-the-art baseline. The proposed vocoder substantially outperformed the baseline for both voices and under all configurations tested. Furthermore, several enhancements were made over the original design, which are beneficial for either sound quality or compatibility with other tools. In addition to its use in SPSS, the proposed vocoder is also demonstrated being used for join smoothing in unit selection-based systems, and can be used for voice conversion or automatic speech recognition

Початкова ідентифікація електричних параметрів синхронних явнополюсних двигунів з постійними магнітами

Дипломний проект містить: 87 сторінок, 18 рисунків, 1 додаток та 4 листа А1 графічної частини. Метою роботи є синтез нового алгоритму початкової ідентифікації електричних та механічних параметрів явнополюсних синхронних двигунів з постійними магнітами. Синтезовано алгоритми векторного керування кутовою швидкістю/положенням явнополюсних синхронних двигунів, який забезпечує глобальне асимптотичне відпрацювання заданої траєкторії кутової швидкості/положення та прямої компоненти струму статора по осі d, а також розв’язку керування електричними та механічними координатами. Розроблені алгоритми дозволяють покращити енергетичну ефективність машини, не впливаючи на процеси регулювання механічних координат. В роботі виконано синтез алгоритму початкової ідентифікації електричних та механічних параметрів явнополюсних синхронних двигунів, який дозволяє ідентифікувати шість невідомих параметрів двигуна та момент навантаження та не вимагає попередньої інформації про будь-який параметр машини.The diploma project comprises: pages 87, figures 18, appendix 1 and the 4 pages A1 of graphical part. The purpose of the diploma project is to synthesize a novel algorithm of self commissioning function for electrical parameters initialization of the interior permanent magnets synchronous motor. The algorithm of indirect vector control of the speed (angular position) of the interior permanent magnets synchronous motor was synthesized, which provided the synchronous motor control system with such properties as global exponential processing of the given speed (angular position) and direct component of stator current along d-axis and also reached solvability in control of electrical and mechanical coordinates. Synthesized algorithm allow improve energetic efficiency of the machine without affecting on the control processes of mechanical coordinates. In this thesis project the algorithm of self-commissioning function for electrical and mechanical parameters initialization of the interior permanent magnets synchronous motor was synthesized, which provide initialization of six unknown motor parameters and torque perturbation and does not required preliminarily information about any of the machine parameters

Dynamics of Macrosystems; Proceedings of a Workshop, September 3-7, 1984

There is an increasing awareness of the important and persuasive role that instability and random, chaotic motion play in the dynamics of macrosystems. Further research in the field should aim at providing useful tools, and therefore the motivation should come from important questions arising in specific macrosystems. Such systems include biochemical networks, genetic mechanisms, biological communities, neutral networks, cognitive processes and economic structures. This list may seem heterogeneous, but there are similarities between evolution in the different fields. It is not surprising that mathematical methods devised in one field can also be used to describe the dynamics of another. IIASA is attempting to make progress in this direction. With this aim in view this workshop was held at Laxenburg over the period 3-7 September 1984. These Proceedings cover a broad canvas, ranging from specific biological and economic problems to general aspects of dynamical systems and evolutionary theory