Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Effective notch method assessment of misalignment for fatigue loaded welds

 The objective of this thesis work was to assess axial misalignment in fatigue loaded welds using the effective notch method. As a result, the fatigue behaviour of non-load carrying cruciform fillet welded joint under cyclic tensile loading has been studied. Various degrees of axial misalignment have been found in one series of non-load carrying cruciform fillet welded joints used in a laboratory investigation. As a result, it was important to carry out a comprehensive investigation since axial misalignment forms part of thequality of fatigue loaded structure and can reduce the fatigue strength. To extend the study, the correlation between fatigue strength and stress ratio, as well as stress concentration factor, were also studied. Moreover, a closer investigation of place of crack initiation and its dependence on weld sequence and imperfections of test specimen (angular distortion) was studied. For the fatigue class calculations, FEM (finite element method) and the effectivenotch approach are used. The addressed variable is the axial misalignment whichis introduce by modeling the entire joint. Fracture mechanics based calculations are also used and quantitatively compared with effective notch and experimental results.

Discription of a New Calculation Method for Determination of Stoichiometric Dissociation Constants of WeakAcid in Salt Solutions from Potentiometric Titration Data

A recently developed calculation method to determine stoichiometric dissociation constants of weak acids from potentiometric titration data is described. The titration data from three different weak acids in aqueous salt solutions at 25 °C were used as examples of the use of the method. The salt alone determined the ionic strength of the solutions considered in this study, and salt molalities up to 0,5 mol kg -1 were used.

Communicating Cost Information to Design Engineers using an Activity-based Costing Method

This paper analyzes the possibilities of integrating cost information and engineering design. Special emphasis is on finding the potential of using the activity-based costing (ABC) method when formulating cost information for the needs of design engineers. This paper suggests that ABC is more useful than the traditional job order costing, but the negative issue is the fact that ABC models become easily too complicated, i.e. expensive to build and maintain, and difficult to use. For engineering design the most suitable elements of ABC are recognizing activities of the company, constructing acitivity chains, identifying resources, activity and cost drivers, as wellas calculating accurate product costs. ABC systems including numerous cost drivers can become complex. Therefore, a comprehensive ABC based cost information system for the use of design engineers should be considered criticaly. Combining the suitable ideas of ABC with engineering oriented thinking could give competentresults.

Potentiometric titration as a method of determining the stoichiometric dissociation constants of weak acids from the thermodynamic dissociation constants of aqueous solutions at 298.15 K

The simple single-ion activity coefficient equation originating from the Debye-Hückel theory was used to determine the thermodynamic and stoichiometric dissociation constants of weak acids from data concerning galvanic cells. Electromotive force data from galvanic cells without liquid junctions, which was obtained from literature, was studied in conjuction with the potentiometric titration data relating to aqueous solutions at 298.15 K. The dissociation constants of weak acids could be determined by the presented techniques and almost all the experimental data studied could be interpreted within the range of experimental error. Potentiometric titration has been used here and the calculation methods were developed to obtain the thermodynamic and stoichiometric dissociation constants of some weak acids in aqueous solutions at 298.15 K. The ionic strength of titrated solutions were adjusted using an inert electrolyte, namely, sodium or potassium chloride. Salt content alonedetermines the ionic strength. The ionic strength of the solutions studied varied from 0.059 mol kg-1 to 0.37 mol kg-1, and in some cases up to 1.0 mol kg-1. The following substances were investigated using potentiometric titration: aceticacid, propionic acid, L-aspartic acid, L-glutamic acid and bis(2,2-dimethyl-3-oxopropanol) amine.

Radio Frequency Measurement Method for Detecting Bearing Currents in Induction Motors

Induction motors are widely used in industry, and they are generally considered very reliable. They often have a critical role in industrial processes, and their failure can lead to significant losses as a result of shutdown times. Typical failures of induction motors can be classified into stator, rotor, and bearing failures. One of the reasons for a bearing damage and eventually a bearing failure is bearing currents. Bearing currents in induction motors can be divided into two main categories; classical bearing currents and inverter-induced bearing currents. A bearing damage caused by bearing currents results, for instance, from electrical discharges that take place through the lubricant film between the raceways of the inner and the outer ring and the rolling elements of a bearing. This phenomenon can be considered similar to the one of electrical discharge machining, where material is removed by a series of rapidly recurring electrical arcing discharges between an electrode and a workpiece. This thesis concentrates on bearing currents with a special reference to bearing current detection in induction motors. A bearing current detection method based on radio frequency impulse reception and detection is studied. The thesis describes how a motor can work as a “spark gap” transmitter and discusses a discharge in a bearing as a source of radio frequency impulse. It is shown that a discharge, occurring due to bearing currents, can be detected at a distance of several meters from the motor. The issues of interference, detection, and location techniques are discussed. The applicability of the method is shown with a series of measurements with a specially constructed test motor and an unmodified frequency-converter-driven motor. The radio frequency method studied provides a nonintrusive method to detect harmful bearing currents in the drive system. If bearing current mitigation techniques are applied, their effectiveness can be immediately verified with the proposed method. The method also gives a tool to estimate the harmfulness of the bearing currents by making it possible to detect and locate individual discharges inside the bearings of electric motors.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Orthogonal function method in modelling paper web quality variation

This work is devoted to the analysis of signal variation of the Cross-Direction and Machine-Direction measurements from paper web. The data that we possess comes from the real paper machine. Goal of the work is to reconstruct the basis weight structure of the paper and to predict its behaviour to the future. The resulting synthetic data is needed for simulation of paper web. The main idea that we used for describing the basis weight variation in the Cross-Direction is Empirical Orthogonal Functions (EOF) algorithm, which is closely related to Principal Component Analysis (PCA) method. Signal forecasting in time is based on Time-Series analysis. Two principal mathematical procedures that we used in the work are Autoregressive-Moving Average (ARMA) modelling and Ornstein–Uhlenbeck (OU) process.

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

Parameter identification in time series models

Time series analysis can be categorized into three different approaches: classical, Box-Jenkins, and State space. Classical approach makes a basement for the analysis and Box-Jenkins approach is an improvement of the classical approach and deals with stationary time series. State space approach allows time variant factors and covers up a broader area of time series analysis. This thesis focuses on parameter identifiablity of different parameter estimation methods such as LSQ, Yule-Walker, MLE which are used in the above time series analysis approaches. Also the Kalman filter method and smoothing techniques are integrated with the state space approach and MLE method to estimate parameters allowing them to change over time. Parameter estimation is carried out by repeating estimation and integrating with MCMC and inspect how well different estimation methods can identify the optimal model parameters. Identification is performed in probabilistic and general senses and compare the results in order to study and represent identifiability more informative way.