A Bayesian network incorporating observation error to predict phosphorus and chlorophyll a in Saginaw Bay

Empirical relationships between lake chlorophyll a and total phosphorus concentrations are widely used to develop predictive models. These models are often estimated using sample averages as implicit surrogates for unknown lake-wide means, a practice than can result in biased parameter estimation and inaccurate predictive uncertainty. We develop a Bayesian network model based on empirical chlorophyll-phosphorus relationships for Saginaw Bay, an embayment on Lake Huron. The model treats the means as unknown parameters, and includes structure to accommodate the observation error associated with estimating those means. Compared with results from an analogous simple model using sample averages, the observation error model has a lower predictive uncertainty and predicts lower chlorophyll and phosphorus concentrations under contemporary lake conditions. These models will be useful to guide pending decision-making pursuant to the 2012 Great Lakes Water Quality Agreement.     

Stochastic feature compensation methods for speaker verification in noisy environments

This paper explores the significance of stereo-based stochastic feature compensation (SFC) methods for robust speaker verification (SV) in mismatched training and test environments. Gaussian Mixture Model (GMM)-based SFC methods developed in past has been solely restricted for speech recognition tasks. Application of these algorithms in a SV framework for background noise compensation is proposed in this paper. A priori knowledge about the test environment and availability of stereo training data is assumed. During the training phase, Mel frequency cepstral coefficient (MFCC) features extracted from a speaker's noisy and clean speech utterance (stereo data) are used to build front end GMMs. During the evaluation phase, noisy test utterances are transformed on the basis of a minimum mean squared error (MMSE) or maximum likelihood (MLE) estimate, using the target speaker GMMs. Experiments conducted on the NIST-2003-SRE database with clean speech utterances artificially degraded with different types of additive noises reveal that the proposed SV systems strictly outperform baseline SV systems in mismatched conditions across all noisy background environments.     

Realizing energy infrastructure projects – A qualitative empirical analysis of local practices to address social acceptance

The federal state of Upper Austria, at a crossing point for European energy grids, provides large-scale resources for storage of natural gas and is among the top infrastructures in this regard in Europe. Considering the ambitious plans for enhancements of energy infrastructures in this region, the issue of social acceptance of energy infrastructure is crucial. To foster an understanding of the challenges inherent in this issue we present an analysis concentrating on the social acceptance of energy infrastructure projects in Upper Austria. This paper addresses the issues with realizing energy infrastructure projects and analyzes the problems and benefits based on an empirical–qualitative study comprising expert interviews, discussions with stakeholders, and a round table workshop integrating the disparate viewpoints. The aim of the process was to integrate different attitudes, perspectives and positions of relevant stakeholders, members of citizens’ initiatives, environmental organizations and of the national government and local authorities. The results presented are based on both the analysis of the empirical–qualitative data and the existing studies and literature on social acceptance. The qualitative research compares experiences and current practices with social acceptance issues (like frameworks, participation, communication strategies) in a set of considered energy infrastructure projects.     

PID controller for automatic voltage regulator using teaching–learning based optimization technique

The present work presents teaching–learning based optimization (TLBO) algorithm as an optimization technique in the area of tuning of the classical controller installed in automatic voltage regulator (AVR). The proposed TLBO algorithm is applied with an aim to find out the optimum value of proportional integral derivative (PID) controller gains with first order low pass filter installed in the AVR. The voltage response of the AVR system, as obtained by using the proposed TLBO based PID controller with first order low pass filter, is compared to those offered by the other algorithms reported in the recent state-of-the-art literatures. The advantage of using this control strategy may be noted by providing good dynamic responses over a wide range of system parametric variations. For on-line, off-nominal operating conditions, fast acting Sugeno fuzzy logic technique is applied to obtain the on-line dynamic responses of the studied model. Furthermore, robustness analysis is also carried out to check the performance of the designed TLBO based PID controller. An analysis, based on voltage response profile, has been investigated with the variations of the model parameters. The simulation results show that the proposed TLBO based PID controller is a significant optimization tool in the subject area of the AVR system. The essence of the present work signifies that the proposed TLBO technique maybe, successfully, applied for the AVR of power system.     

Knowledge domain states mapping concept for controller tuning in an interconnected power network

This paper presents novel power system stabilizers (PSS) tuning approach with particles swarm optimization (PSO) driven knowledge domain states mapping for multi area power system. Tuning of PSS parameters has been done by PSO technique offline at different operating conditions as load dynamics change. The objective function for PSS parameters tuning is integral time multiplied by absolute error (ITAE). The sets of tuned parameters at different operating conditions thus obtained are termed as knowledge domain. The process is viewed as knowledge domain mapping. The dynamical system response has been linked with states, and if there is any violation from desired limits, control action is initiated and thus retuned control parameters obtained straight away from the respective knowledge domain helps to provide quick response and precise damping of signals of interest. Proposed concept also demonstrates that if one controller (PSS) fails to stabilize the system at certain operating condition then another controller (UPFC) connected in the system acts as supplementary controller in automation which assists PSS functioning and thus entire system operation improves by way of modulating the signal dynamics at interface points which quickly damps oscillations. The system study has been performed on a sample six area power systems comprising of UPFC connected between area two and three and PSS to all areas. The proposed concept demonstrates auto tuning of PSS for quick oscillation damping as the operating conditions change and also under situations of PSS failure due to relatively larger perturbation, UPFC acts as supplementary controller by assisting the entire system PSS to recover ensuring stability.     

Basic Study on Islanding Detection Method for PV Systems by Harmonic Impedance Detection in Case of Including Induction Motor in Load System

It is important that photovoltaic (PV) systems detect islanding caused by power system faults to ensure electrical safety. Thus we propose a novel islanding detection method which detects the harmonic impedance by injecting harmonic currents synchronized with the exciting current harmonics of the pole transformer. For the case in which an induction motor load is included in the load system, basic experiments on islanding detection and simulation analysis are conducted to verify the effectiveness of the proposed method.     

Cooperative Control by System Voltage Control Equipments in Consideration of Reducing Capacity of STATCOM

In recent years, the number of renewable energy sources (RESs) such as photovoltaic generation systems and wind power generation systems connected to the grid has been increasing as a way of reducing negative effects on the environment. The outputs of these RESs vary rapidly because of the influence of the weather and the conditions of the location. Therefore, there are concerns that the point voltages in a distribution system may vary drastically and that the voltages may deviate from the appropriate voltage range as a result of the influence of the RES connected to the distribution system or to the diversification of loads. Furthermore, there are concerns about adverse effects on electric power quality, such as voltage imbalances and harmonics. In this paper, we propose a cooperative voltage control method for a distribution system using system voltage control equipment in order to reduce the capacity of the static synchronous compensator. Numerical calculations were performed in order to verify the validity of the proposed method.     

Detection of Damaged Distribution Surge Arresters Using an Impulse Generator

Distribution surge arresters with an internal series gap have been installed on Japanese distribution lines at high density to reduce lightning‐related overvoltages. In contrast, surge arresters are sometimes damaged by direct lightning strokes, particularly in winter. Measurement of the insulation resistance between the terminals of the surge arrester and measurement of the dc discharge voltage of the surge arrester are generally adopted to detect damaged arresters. However, if metal‐oxide (MO) varistors are damaged and the internal series gap is not damaged, it is difficult to detect damaged arresters by the two conventional methods. Therefore, this paper presents a proposed detection method that can accurately detect damaged arresters. In the proposed method, first, the voltage between the terminals of the surge arrester is measured when the output of an impulse generator is applied to the surge arrester. Second, the damaged arrester is detected by comparison between its voltage waveform and the voltage waveform of the nondamaged arrester. The detection rate of damaged arresters by the proposed method is markedly higher than the rates of detection by the two conventional methods.     

A joint method for the maximum inscribed circle and minimum circumscribed circle

A joint method based on the relative diameter is introduced for evaluating the minimum circumscribed circle and maximum inscribed circle in this article. The definition and calculation of the relative diameter is given in detail. The proposed method is an approximate method based on the least square circle solution, and just for the minimum circumscribed circle and maximum inscribed circle criteria. Several examples from the literatures have been carried out to validate the effectiveness of the proposed algorithm.     

An approach to the evaluation of multivariate data during ball end milling free-form surface fragments

We present a method for investigating the process of ball end milling, a technology widely used in tool making and moulding. We analyse the main features of free-form surfaces used in this technology, and propose a sequence of steps to identify the most suitable milling strategy. The basic idea of such a sequence lies in the definition of the tangible fragments of free-form surfaces applicable to tool making. Tangible fragments represent the parts of tooling and signed radii that can distinguish both the active and transitional surfaces of tooling. Free-form surface fragments were selected since they are capable of securing definiteness in measurement of roughness parameters and surface errors. We investigated the operation capability of solid ball end milling cutters in terms of cutting tool edge micro-geometry. Cutting edge radius (r_n) and roughness parameters of the tool edge were measured to determine the relationship between new and worn tool edges. Roughness parameters were measured at different parts of the machined surfaces, which take on typical features of dies and moulds, such as inclined wall, ridge lines, valley lines, as well as, the active surfaces defined by signed radii. Surface error such as scallop height, gouging, tolerances and actual signed radii were measured at transitive surfaces. The traditional approach of evaluating roughness parameters was used to determine the suitability of factors such as milling operation, milling strategy and direction of milling. In addition, traditional approaches such as relationships, distributions and histograms were also used. We applied Khattree–Naik’s plot, which proves its suitability to visualise all the data being measured in the same units: microns and millimetres. Characteristic features of the ball end milling process, such as tool edge micro-geometry, geometry of the machined surface, and unit length of the transitive surface were applied in Khattree–Naik’s plots. We found that this plot was capable of processing multivariate data to distinguish specific markers of the quality of machined surfaces, which are produced in ball end milling.