Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU

Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.

Grounding in a wind power application

The subject of this master’s thesis is to research grounding in a particular wind power application. The aim is to define how the grounding from different points effects to the function of the whole system. The investigated subjects are generator voltage spikes, ground currents and system fault situations. The first part of this thesis represents power electronics, which is commonly used in wind power systems. The second part concentrates more to the grounding, electrical safety demands and potential fault situations. The object of the simulations is to investigate voltage spikes and fault situations. Measurements will be made with small-scale setup and in the last part simulation and measurement results are compared to each other and to a full-scale system.

Overvoltage Mitigation Techniques in Wind Power Generators

Advancements in power electronic semiconductor switching devices have lead to significantly faster switching times. In motor and generator applications, the fast switching times of pulse width modulated (PWM) inverters lead to overvoltages caused by voltage reflections with shorter and shorter cables. These excessive overvoltages may lead to a failure of the electrical machine in a matter of months. In this thesis, the causes behind the overvoltage phenomenon as well as its different mitigation techniques are studied. The most suitable techniques for mitigating the overvoltage phenomenon in wind power generator applications are chosen based on both simulations and actual measurements performed on a prototype. An RC filter at the terminals of the electrical machine and an inverter output filter designed to reduce the rise and fall times of voltage pulses are presented as a solution to the overvoltage problem. The performance and losses of both filter types are analysed.

Business opportunities in power sector of Ukraine : focus small-scale hydro and wind power sectors

In the last few years, the Ukrainian investment market has constantly shown strong performance and significant growth. This is primarily due to the investment attractiveness of Ukraine. From the perspective of investments in energy sector, Ukraine can be described as a country providing significant number of opportunities to multiply invested funds. But there are numbers of risks which hamper large investments. The work objective was to discover opportunities in small-scale hydropower and wind power sectors of Ukraine and more importantly to prove economic expediency of such investments. Thesis covers major of issues, concerning entering the Ukrainian power market as a foreign investor. It provides basic information about the structure of power market, the state of renewables sector in Ukraine, development of power sector in the regions, functioning of Wholesale Electricity Market, formation of electricity prices, possibilities for implementing joint Implementation mechanism, while the most attention, nevertheless, is concentrated on the opportunities in small-scale hydro and wind power sectors. Theoretical part of the study disclosed that Crimea peninsula has perfect wind conditions and could be a prospective area for wind project development. Investment analysis revealed that project profits will be excellent if green tariff for renewable energy is adopted. By the moment uncertainties about green law adoption bring additional risk to the projects and complicate any investment decision.

Doubly fed induction generator versus direct drive permanent magnet synchronous generator in wind power applications

The objective of this master's thesis is to compare two different generator systems for wind turbines. It is the doubly fed induction generator system with three stage gearbox and the direct drive permanent magnet generator system. The comparison of generator systems is based on annual energy production for a given wind climate. For comparison a 3 MW, 15 rpm wind turbine is used. Modelling of a turbine rotor, gearbox and converters were done. Design of two generators was done and their performance was examined.

Design of a 1 kW 150 rpm permanent-magnet synchronous generator for stand-alone wind-power applications

A program for calculating low-speed low-power synchronous machine is presented. A permanent-magnet synchronous generator for 1 kW 150 rpm is designed. Optimization of magnet’s and coil’s dimensions was made.

Fast identification algorithms for Gaussian process model

A class identification algorithms is introduced for Gaussian process(GP)models.The fundamental approach is to propose a new kernel function which leads to a covariance matrix with low rank,a property that is consequently exploited for computational efficiency for both model parameter estimation and model predictions.The objective of either maximizing the marginal likelihood or the Kullback–Leibler (K–L) divergence between the estimated output probability density function(pdf)and the true pdf has been used as respective cost functions.For each cost function,an efficient coordinate descent algorithm is proposed to estimate the kernel parameters using a one dimensional derivative free search, and noise variance using a fast gradient descent algorithm. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

An aggregated wind power generation model based on MERRA reanalysis data: MATLAB model and example data for the April 2014 wind farm distribution of Great Britain.

The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

Estimation of Gaussian process regression model using probability distance measures

A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

WIND POWER SUITABILITY ANALYSIS FOR THE GULF OF MAINE

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WIND POWER IN MAINE: BALANCING CONSERVATION AND ENERGY PRODUCTION

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