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Number of results: 17
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Abstract

In this paper, the applications of the multivariate data analysis and optimization on vibration signals from compressors have been tested on the assembly line to identify nonconforming products. The multivariate analysis has wide applicability in the optimization of weather forecasting, agricultural experiments, or, as in this case study, in quality control. The techniques of discriminant analysis and linear program were used to solve the problem. The acceleration and velocity signals used in this work were measured in twenty-five rotating compressors, of which eleven were classified as good baseline compressors and fourteen with manufacturing defects by the specialists in the final acoustic test of the production line. The results obtained with the discriminant analysis separated the conforming and nonconforming groups with a significance level of 0.01, which validated the proposed methodology.
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Abstract

This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
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Abstract

A transformer is an important part of power transmission and transformation equipment. Once a fault occurs, it may cause a large-scale power outage. The safety of the transformer is related to the safe and stable operation of the power system. Aiming at the problem that the diagnosis result of transformer fault diagnosis method is not ideal and the model is unstable, a transformer fault diagnosis model based on improved particle swarm optimization online sequence extreme learning machine (IPSO-OS-ELM) algorithm is proposed. The improved particle swarmoptimization algorithm is applied to the transformer fault diagnosis model based on the OS-ELM, and the problems of randomly selecting parameters in the hidden layer of the OS-ELM and its network output not stable enough, are solved by optimization. Finally, the effectiveness of the improved fault diagnosis model in improving the accuracy is verified by simulation experiments.
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Abstract

In the last decade, Poland has become one of the most active markets for unconventional hydrocarbon deposits exploration. At present, there are twenty concessions for the exploration and/or discovery of reserves, including shale gas. The area covered by exploration concessions constitutes ca. 7.5% of the country’s area. Four main stages can be distinguished In the shale gas development and exploitation project: the selection and preparation of the place of development of the wells, hydraulic drilling and fracturing, exploitation (production) and marketing, exploitation suppression and land reclamation. In the paper, the concept of cost analysis of an investment project related to the exploration and development of a shale gas field/area was presented. The first two stages related to the preparatory work, carried out on the selected site, as well as drilling and hydraulic fracturing were analyzed. For economic reasons, the only rational way to make shale gas reserves available is to use horizontal drilling, either singly or in groups. The number of drilling pads covering the concession area is a fundamental determinant of the development cost of the deposit. In the paper, the results of the cost analysis of various types of reaming method with an area of 25,000,000 m2 were presented. Cost estimates were prepared for two variants: group drilling for three types of drilling pads: with three, five and seven wells and for single wells. The results show that, as the number of horizontal wells increases, the total cost of the development of the deposit is reduced. For tree-wells pad, these costs are 7% lower than in the second variant, for five-well pads they are 11% lower, and for seven-well pads they are 11.5% smaller than in the second variant. Authors, using applied methodology, indicate the direction of further research that will enable the optimization of shale gas drilling operations.
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Abstract

This article considers designing of a renewable electrical power generation system for self-contained homes away from conventional grids. A model based on a technique for the analysis and evaluation of two solar and wind energy sources, electrochemical storage and charging of a housing area is introduced into a simulation and calculation program that aims to decide, based on the optimized results, on electrical energy production system coupled or separated from the two sources mentioned above that must be able to ensure a continuous energy balance at any time of the day. Such system is the most cost-effective among the systems found. The wind system adopted in the study is of the low starting speed that meets the criteria of low winds in the selected region under study unlike the adequate solar resource, which will lead to an examination of its feasibility and profitability to compensate for the inactivity of photovoltaic panels in periods of no sunlight. That is a system with fewer photovoltaic panels and storage batteries whereby these should return a full day of autonomy. Two configurations are selected and discussed. The first is composed of photovoltaic panels and storage batteries and the other includes the addition of a wind system in combination with the photovoltaic system with storage but at a higher investment cost than the first. Consequently, this result proves that is preferable to opt for a purely photovoltaic system supported by the storage in this type of site and invalidates the interest of adding micro wind turbines adapted to sites with low wind resources.
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Abstract

The locally resonant sonic material (LRSM) is an artificial metamaterial that can block underwater sound. The low-frequency insulation performance of LRSM can be enhanced by coupling local resonance and Bragg scattering effects. However, such method is hard to be experimentally proven as the best optimizing method. Hence, this paper proposes a statistical optimization method, which first finds a group of optimal solutions of an object function by utilizing genetic algorithm multiple times, and then analyzes the distribution of the fitness and the Euclidean distance of the obtained solutions, in order to verify whether the result is the global optimum. By using this method, we obtain the global optimal solution of the low-frequency insulation of LRSM. By varying parameters of the optimum, it can be found that the optimized insulation performance of the LRSM is contributed by the coupling of local resonance with Bragg scattering effect, as well as a distinct impedance mismatch between the matrix of LRSM and the surrounding water. This indicates coupling different effects with impedance mismatches is the best method to enhance the low-frequency insulation performance of LRSM.
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Abstract

Hybrid Renewable Energy Systems connected to the traditional power suppliers are an interesting technological solution in the field of energy engineering and the integration of renewable systems with other energy systems can significantly increase in energy reliability. In this paper, an analysis and optimization of the hybrid energy system, which uses photovoltaic modules and wind turbines components connected to the grid, is presented. The system components are optimized using two objectives criteria: economic and environmental. The optimization has been performed based on the experimental data acquired for the whole year. Results showed the optimal configuration for the hybrid system based on economical objective, that presents the best compromise between the number of components and total efficiency. This achieved the lowest cost of energy but with relatively high CO2 emissions, while environmental objective results with lower CO2 emissions and higher cost of energy and presents the best compromise between the number of components and system net present cost. It has been shown that a hybrid system can be optimized in such a way that CO2 emission is maximally reduced and – separately – in terms of reducing the cost. However, the study shows that these two criteria cannot be optimized at the same time. Reducing the system cost increase CO2 emission and enhancing ecological effect makes the system cost larger. However, depends on strategies, a balance between different optimization criteria can be found. Regardless of the strategy used economic criteria – which also indirect takes environmental aspects as a cost of penalties – should be considered as a major criterion of optimization while the other objectives including environmental objectives are less important.
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Abstract

The problem of optimally controlling a Wiener process until it leaves an interval (a; b) for the first time is considered in the case when the infinitesimal parameters of the process are random. When a = ��1, the exact optimal control is derived by solving the appropriate system of differential equations, whereas a very precise approximate solution in the form of a polynomial is obtained in the two-barrier case.
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Abstract

The article deals with the patterns of segmental adaptation of Polish voiceless affricates in initial and fi nal CC (consonant + consonant) clusters by native speakers of English. The data have been collected in an online loanword adaptation experiment in which 30 native speakers of Southern British English reproduced Polish words containing such sequences. The major problem posed by the data is the divergent adaptation of the post-alveolar /͡tʂ/ vs. the pre-palatal /͡tɕ/, with the former substituted mainly with the coronal plosive [t] and the latter realised as the palato-alveolar affricate [͡tʃ]. It is argued that these patterns of nativisation are due to the highlyranked IDENT-IO[dist] constraint, which militates against the modifi cation in the value of the feature [distributed]. Furthermore, it is demonstrated that the experimental results provide evidence in favour of the fundamental assumptions underlying the phonological approach to loan assimilation, namely the phonological input view as well as the faithful perception view.
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Abstract

Transport is one of the factors influencing the development of metropolitan areas. However, for its efficient work, numerous optimizations are required. Main tasks are shortening travel time, improving service quality and increasing the number of passengers served. The author has presented current studies on the field in optimization of public transport, mainly ways to optimize the transport network construction, based on large data sets about the population and their communication behaviour. Methods of combining various types of public transport with each other are presented. In the paper also are presents authors studies on the communication accessibility within the city of Cracow. Estimated distances from buildings to various types of public transport stops. The results were presented in aggregated form. Calculated communication speed of three types of public transport functioning in Cracow has also been discussed.
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Abstract

This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS-PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.
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Abstract

In this paper, a modified sound quality evaluation (SQE) model is developed based on combination of an optimized artificial neural network (ANN) and the wavelet packet transform (WPT). The presented SQE model is a signal processing technique, which can be implemented in current microphones for predicting the sound quality. The proposed method extracts objective psychoacoustic metrics including loudness, sharpness, roughness, and tonality from sound samples, by using a special selection of multi-level nodes of the WPT combined with a trained ANN. The model is optimized using the particle swarm optimization (PSO) and the back propagation (BP) algorithms. The obtained results reveal that the proposed model shows the lowest mean square error and the highest correlation with human perception while it has the lowest computational cost compared to those of the other models and software.
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Abstract

This paper researches the application of grey system theory in cost forecasting of the coal mine. The grey model (GM(1.1)) is widely used in forecasting in business and industrial systems with advantages of minimal data, a short time and little fluctuation. Also, the model fits exponentially with increasing data more precisely than other prediction techniques. However, the traditional GM(1.1) model suffers from the poor anti-interference ability. Aimed at the flaws of the conventional GM(1.1) model, this paper proposes a novel dynamic forecasting model with the theory of background value optimization and Fourier-series residual error correction based on the traditional GM(1.1) model. The new model applies the golden segmentation optimization method to optimize the background value and Fourier-series theory to extract periodic information in the grey forecasting model for correcting the residual error. In the proposed dynamic model, the newest data is gradually added while the oldest is removed from the original data sequence. To test the new model’s forecasting performance, it was applied to the prediction of unit costs in coal mining, and the results show that the prediction accuracy is improved compared with other grey forecasting models. The new model gives a MAPE & C value of 0.14% and 0.02, respectively, compared to 1.75% and 0.37 respectively for the traditional GM(1.1) model. Thus, the new GM(1.1) model proposed in this paper, with advantages of practical application and high accuracy, provides a new method for cost forecasting in coal mining, and then help decision makers to make more scientific decisions for the mining operation.
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Abstract

Mining ventilation should ensure in the excavations required amount of air on the basis of determined regulations and to mitigate various hazards. These excavations are mainly: longwalls, function chambers and headings. Considering the financial aspect, the costs of air distribution should be as low as possible and due to mentioned above issues the optimal air distribution should be taken into account including the workers safety and minimization of the total output power of main ventilation fans. The optimal air distribution is when the airflow rate in the mining areas and functional chambers are suitable to the existing hazards, and the total output power of the main fans is at a minimal but sufficient rate. Restructuring of mining sector in Poland is usually connected with the connection of different mines. Hence, dependent air streams (dependent air stream flows through a branch which links two intake air streams or two return air streams) exist in ventilation networks of connected mines. The zones of intake air and return air include these air streams. There are also particular air streams in the networks which connect subnetworks of main ventilation fans. They enable to direct return air to specified fans and to obtain different airflows in return zone. The new method of decreasing the costs of ventilation is presented in the article. The method allows to determine the optimal parameters of main ventilation fans (fan pressure and air quantity) and optimal air distribution can be achieved as a result. Then the total output power of the fans is the lowest which makes the reduction of costs of mine ventilation. The new method was applied for selected ventilation network. For positive regulation (by means of the stoppings) the optimal air distribution was achieved when the total output power of the fans was 253.311 kW and for most energy-intensive air distribution it was 409.893 kW. The difference between these cases showed the difference in annual energy consumption which was 1 714 MWh what was related to annual costs of fan work equaled 245 102 Euro. Similar values for negative regulation (by means of auxiliary fans) were: the total output power of the fans 203.359 kW (optimal condition) and 362.405 kW (most energy-intensive condition). The difference of annual energy consumption was 1 742 MWh and annual difference of costs was 249 106 Euro. The differences between optimal airflows considering positive and negative regulations were: the total output power of fans 49.952 kW, annual energy consumption 547 MWh, annual costs 78 217 Euro.
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Abstract

High distribution system power-losses are predominantly due to lack of investments in R&D for improving the efficiency of the system and improper planning during installation. Outcomes of this are un-designed extensions of the distributing power lines, the burden on the system components like transformers and overhead (OH) lines/conductors and deficient reactive power supply leading to drop in a system voltage. Distributed generation affects the line power flow and voltage levels on the system equipment. These impacts of distributed generation (DG) may be to improve system efficiency or reduce it depending on the operating environment/conditions of the distribution system and allocation of capacitors. For this purpose, allocating of distributed generation optimally for a given radial distribution system can be useful for the system outlining and improve efficiency. In this paper, a new method is used for optimally allocating the DG units in the radial distribution system to curtail distribution system losses and improve voltage profile. Also, the variation in active power load in the system is considered for effective utilization of DG units. To evidence the effectiveness of the proposed algorithm, computer simulations are carried out in MATLAB software on the IEEE-33 bus system and Vastare practical 116 bus system.
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Abstract

In this paper a scaling approach for the solution of 2D FE models of electric machines is proposed. This allows a geometrical and stator and rotor resistance scaling as well as a rewinding of a squirrel cage induction machine enabling an efficient numerical optimization. The 2D FEM solutions of a reference machine are calculated by a model based hybrid numeric induction machine simulation approach. In contrast to already known scaling procedures for synchronous machines the FEM solutions of the induction machine are scaled in the stator-current-rotor-frequency-plane and then transformed to the torque- speed-map. This gives the possibility to use a new time scaling factor that is necessary to keep a constant field distribution. The scaling procedure is validated by the finite element method and used in a numerical optimization process for the sizing of an electric vehicle traction drive considering the gear ratio. The results show that the scaling procedure is very accurate, computational very efficient and suitable for the use in machine design optimization.
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