The loss of power and voltage can affect distribution networks that have a significant number of distributed power resources and electric vehicles. The present study focuses on a hybrid method to model multi-objective coordination optimisation problems for dis- tributed power generation and charging and discharging of electric vehicles in a distribution system. An improved simulated annealing based particle swarm optimisation (SAPSO) algorithm is employed to solve the proposed multi-objective optimisation problem with two objective functions including the minimal power loss index and minimal voltage deviation index. The proposed method is simulated on IEEE 33-node distribution systems and IEEE-118 nodes large scale distribution systems to demonstrate the performance and effectiveness of the technique. The simulation results indicate that the power loss and node voltage deviation are significantly reduced via the coordination optimisation of the power of distributed generations and charging and discharging power of electric vehicles.With the methodology supposed in this paper, thousands of EVs can be accessed to the distribution network in a slow charging mode.
This article contains information concerning of the analysis the possibility of defining refinery qualities of the slag based thermophysical and thermodynamical data. The paper presents a model of slag refining processes and a method of determining the reduction capability of slag solutions. Slag was analysed with the use of the DTA methods for the brass melting conductions. The study of computer program including the satisfactory number of data there are used in to the design a modern device rotating head used for gas-slag refining. It was achieved that the refining gas and fluxes were distributed ever by the rotating head. High effectiveness of the gas-slag refining processes was proved for the brass.
The predicted annual growth of energy consumption in ICT by 4% towards 2020, despite improvements and efficiency gains in technology, is challenging our ability to claim that ICT is providing overall gains in energy efficiency and Carbon Imprint as computers and networks are increasingly used in all sectors of activity. Thus we must find means to limit this increase and preserve quality of service (QoS) in computer systems and networks. Since the energy consumed in ICT is related to system load, ]this paper discusses the choice of system load that offers the best trade-off between energy consumption and QoS. We use both simple queueing models and measurements to develop and illustrate the results. A discussion is also provided regarding future research directions.
Production processes at KGHM are complex and require from customers products of constantly higher quality at relatively lowest prices. Such situation results in an increase of the importance of optimisation of processes. As products and technologies change rapidly, technologists at the plant in Głogów have less time to achieve optimisation basing on own experiences. Analysing a particular process, we can e.g. detect occurring disturbances, find factors having an influence on quality problems, select optimal settings or compare various production procedures. Analysis of the course of production process is the basis of process optimisation. One optimisation in case of the process of decopperisation of flash slag can be a change of a technological additive to a less energy-consuming one, and its final result can be an improvement of the productivity index, a change of the relation between final effects and born expenditures, as well as optimisation of production costs.
Evolutionary computing and algorithms are well known tools of optimisation that are utilized for various areas of analogue electronic circuits design and diagnosis. This paper presents the possibility of using two evolutionary algorithms - genetic algorithm and evolutionary strategies - for the purpose of analogue circuits yield and cost optimisation. Terms: technologic and parametric yield are defined. Procedures of parametric yield optimisation, such as a design centring, a design tolerancing, a design centring with tolerancing, are introduced. Basics of genetic algorithm and evolutionary strategies are presented, differences between these two algorithms are highlighted, certain aspects of implementation are discussed. Effectiveness of both algorithms in parametric yield optimisation has been tested on several examples and results have been presented. A share of evolutionary algorithms computation cost in a total optimisation cost is analyzed.
Micro perforated panel (MPP) absorber is a new form of acoustic absorbing material in comparison with porous ones. These absorbers are considered as next generation ones and the best alternative for traditional porous materials like foams. MPP combined with a uniform air gap constructs an absorber which has high absorption but in a narrow bandwidth of frequency. This characteristic makes MPPAs insufficient for practical purposes in comparison with porous materials. In this study instead of using a uniform air gap behind the MPP, the cavity is divided into several partitions with different depth arrangement which have parallel faces. This method improves the absorption bandwidth to reach the looked for goal. To achieve theoretical absorption of this absorber, equivalent electro-acoustic circuit and Maa’s theory (Maa, 1998) are employed. Maa suggested formulas to calculate MPP’s impedance which show good match with experimental results carried out in previous studies. Electro-acoustic analogy is used to combine MPP’s impedance with acoustic impedances of complex partitioned cavity. To verify the theoretical analyses, constructed samples are experimentally tested via impedance tube. To establish the test, a multi-depth setup facing a MPP is inserted into impedance tube and the absorption coefficient is examined in the 63–1600 Hz frequency range. Theoretical results show good agreement compared to measured data, by which a conclusion can be made that partitioning the cavity behind MPP into different depths will improve absorption bandwidth and the electro-acoustic analogy is an appropriate theoretical method for absorption enhancement research, although an optimisation process is needed to achieve best results to prove the capability of this absorber. The optimisation process provides maximum possible absorption in a desired frequency range for a specified cavity configuration by giving the proper cavity depths. In this article numerical optimisation has been done to find cavity depths for a unique MPP.
Most researchers have explored noise reduction effects based on the transfer matrix method and the boundary element method. However, maximum noise reduction of a plenum within a constrained space, which frequently occurs in engineering problems, has been neglected. Therefore, the optimum design of multi-chamber plenums becomes essential. In this paper, two kinds of multi-chamber plenums (Case I: a two-chamber plenum that is partitioned with a centre-opening baffle; Case II: a three-chamber plenum that is partitioned with two centre-opening baffles) within a fixed space are assessed. In order to speed up the assessment of optimal plenums hybridized with multiple partitioned baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fit with a series of real data – input design data (baffle dimensions) and output data approximated by BEM data in advance. To assess optimal plenums, a genetic algorithm (GA) is applied. The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.