Search results for: Distributed generation

Authors: Zhoucheng Bao, Haiyan Zhu, Tingting Pang, Zuling Wang

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This paper presents a multi population Differential Evolution (DE) with adaptive mutation and local search for global optimization, named AMMADE in order to better coordinate the cooperation between the populations and the rational use of resources. In AMMADE, the population is divided based on the Euclidean distance sorting method at each generation to appropriately coordinate the cooperation between subpopulations and the usage of resources, such that the best-performed subpopulation will get more computing resources in the next generation. Further, an adaptive local search strategy is employed on the best-performed subpopulation to achieve a balanced search. The proposed algorithm has been tested by solving optimization problems taken from CEC2014 benchmark problems. Experimental results show that our algorithm can achieve a competitive or better result than related methods. The results also confirm the significance of devised strategies in the proposed algorithm.

Keywords: Differential evolution, multi-mutation strategies, memetic algorithm, adaptive local search.

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

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Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Paula Ferreira, Filipa Vieira

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The use of wind energy for electricity generation is growing rapidly across the world and in Portugal. However, the geographical characteristics of the country along with the average wind regime and with the environmental restrictions imposed to these projects create limitations to the exploit of the onshore wind resource. The best onshore wind spots are already committed and the possibility of offshore wind farms in the Portuguese cost is now being considered. This paper aims to make a contribution to the evaluation of offshore wind power projects in Portugal. The technical restrictions are addressed and the strategic, environmental and financial interest of the project is analysed from the private company and public points of view. The results suggest that additional support schemes are required to ensure private investors interest for these projects. Assuming an approach of direct substitution of energy sources for electricity generation, the avoided CO2 equivalent emissions for an offshore wind power project were quantified. Based on the conclusions, future research is proposed to address the environmental and social impacts of these projects.

Keywords: Feed-in tariff, offshore wind power, project evaluation.

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Authors: Adi A. Maaita, Hamza A. A. Al_Sewadi

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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced, or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfill Shannon’s principle of “confusion and diffusion”. ASCII code characters were utilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.

Keywords: Cryptosystems, Information Security agreement, Key distribution, Random numbers.

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to prevent deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network. 

Keywords: Accident risks estimation, artificial neural network, deep learning, K-mean, road safety.

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

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Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: Combat effectiveness, emerging technologies, human factors, systems safety analysis.

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Authors: Muhammad Muhsin, Abhishek Mishra, Shreyansh Vishwakarma, K. Dasaratha Babu, Anudevi Samuel

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In an interconnected power system, any sudden small load perturbation in any of the interconnected areas causes the deviation of the area frequencies, the tie line power and voltage deviation at the generator terminals. This paper deals with the study of performance of intelligent Fuzzy Logic controllers coupled with Conventional Controllers (PI and PID) for Load Frequency Control. For analysis, an isolated single area and interconnected two area thermal power systems with and without generation rate constraints (GRC) have been considered. The studies have been performed with conventional PI and PID controllers and their performance has been compared with intelligent fuzzy controllers. It can be demonstrated that these controllers can successfully bring back the excursions in area frequencies and tie line powers within acceptable limits in smaller time periods and with lesser transients as compared to the performance of conventional controllers under same load disturbance conditions. The simulations in MATLAB have been used for comparative studies.

Keywords: Area Control Error, Fuzzy Logic, Generation rate constraint, Load Frequency, Tie line Power.

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Authors: Zhen Cheng, Xinyu Dai, Shujian Huang, Jiajun Chen

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Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable.

Keywords: Natural Language Inference, explanation generation, variational auto-encoder, generative model.

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Authors: Jihad S. Daba, J. P. Dubois

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Fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper utilized a Poisson modulated-weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multidiversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.

Keywords: Cellular communication, femto- and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process.

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Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo

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Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.

Keywords: Power quality, remote monitoring, distributed automation system, economic evaluation, LV network.

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Authors: Lucy Patricia Onundo, Wilfred Njoroge Mwema

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The rapidly diminishing fossil fuel reserves, their exorbitant cost and the increasingly apparent negative effect of fossil fuels to climate changes is a wake-up call to explore renewable energy. Wind, bio-fuel and solar power have already become staples of Kenyan electricity mix. The potential of electric power generation from marine tidal currents is enormous, with oceans covering more than 70% of the earth. However, attempts to harness marine tidal energy in Kenya, has yet to be studied thoroughly due to its promising, cyclic, reliable and predictable nature and the vast energy contained within it. The high load factors resulting from the fluid properties and the predictable resource characteristics make marine currents particularly attractive for power generation and advantageous when compared to others. Global-level resource assessments and oceanographic literature and data have been compiled in an analysis of the technology-specific requirements for tidal energy technologies and the physical resources. Temporal variations in resource intensity as well as the differences between small-scale applications are considered.

Keywords: Energy data assessment, environmental legislation, renewable energy, tidal-in-stream turbines.

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Authors: M. Moslehpour, S. Khorsandi

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As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: NDP, SEND, CGA, modifier, malicious node.

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Authors: Salma Parvin, M. A. Alim

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The convective and radiative heat transfer performance and entropy generation on forced convection through a direct absorption solar collector (DASC) is investigated numerically. Four different fluids, including Cu-water nanofluid, Al₂O₃-waternanofluid, TiO₂-waternanofluid, and pure water are used as the working fluid. Entropy production has been taken into account in addition to the collector efficiency and heat transfer enhancement. Penalty finite element method with Galerkin’s weighted residual technique is used to solve the governing non-linear partial differential equations. Numerical simulations are performed for the variation of mass flow rate. The outcomes are presented in the form of isotherms, average output temperature, the average Nusselt number, collector efficiency, average entropy generation, and Bejan number. The results present that the rate of heat transfer and collector efficiency enhance significantly for raising the values of m up to a certain range.

Keywords: DASC, forced convection, mass flow rate, nanofluid.

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Authors: Sudeshna Bhattacharya, Pratyush Pandey, Pradeep Kumar K

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We propose a decoy-pulse protocol for frequency-coded implementation of B92 quantum key distribution protocol. A direct extension of decoy-pulse method to frequency-coding scheme results in security loss as an eavesdropper can distinguish between signal and decoy pulses by measuring the carrier photon number without affecting other statistics. We overcome this problem by optimizing the ratio of carrier photon number of decoy-to-signal pulse to be as close to unity as possible. In our method the switching between signal and decoy pulses is achieved by changing the amplitude of RF signal as opposed to modulating the intensity of optical signal thus reducing system cost. We find an improvement by a factor of 100 approximately in the key generation rate using decoy-state protocol. We also study the effect of source fluctuation on key rate. Our simulation results show a key generation rate of 1.5×10-4/pulse for link lengths up to 70km. Finally, we discuss the optimum value of average photon number of signal pulse for a given key rate while also optimizing the carrier ratio.

Keywords: B92, decoy-pulse, frequency-coding, quantum key distribution.

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Authors: Ben Richard Hughes, Hassam Nasarullah Chaudhry

Abstract:

The main aim of this work is to establish the capabilities of new green buildings to ascertain off-grid electricity generation based on the integration of wind turbines in the conceptual model of a rotating tower [2] in Dubai. An in depth performance analysis of the WinWind 3.0MW [3] wind turbine is performed. Data based on the Dubai Meteorological Services is collected and analyzed in conjunction with the performance analysis of this wind turbine. The mathematical model is compared with Computational Fluid Dynamics (CFD) results based on a conceptual rotating tower design model. The comparison results are further validated and verified for accuracy by conducting experiments on a scaled prototype of the tower design. The study concluded that integrating wind turbines inside a rotating tower can generate enough electricity to meet the required power consumption of the building, which equates to a wind farm containing 9 horizontal axis wind turbines located at an approximate area of 3,237,485 m2 [14].

Keywords: computational fluid dynamics, green building, horizontal axis wind turbine, rotating tower, velocity gradient.

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Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj Biswas, Frank Ferrese

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This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star Topology, Fault Tolerance, Conditional Diagnosability, Multi-Agent System, Automated Power System.

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Authors: Amir Alani, Mojtaba Mahmoodian, Anna Romanova, Asaad Faramarzi

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Pipelines are extensively used engineering structures which convey fluid from one place to another. Most of the time, pipelines are placed underground and are encumbered by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on concrete pipes in sewage systems (concrete sewers). This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of this type of pipe. Then three probabilistic time dependent reliability analysis methods including the first passage probability theory, the gamma distributed degradation model and the Monte Carlo simulation technique are discussed and developed. Sensitivity analysis indexes which can be used to identify the most important parameters that affect pipe failure are also discussed. The reliability analysis methods developed in this paper contribute as rational tools for decision makers with regard to the strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the sewer system.

Keywords: Reliability analysis, service life prediction, Monte Carlo simulation method, first passage probability theory, gamma distributed degradation model.

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Authors: Elysia Barker, Jian Guo Zhou, Ling Qian, Steve Decent

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A method of modelling topography used in the simulation of riverbeds is proposed in this paper which removes the need for datapoints and measurements of a physical terrain. While complex scans of the contours of a surface can be achieved with other methods, this requires specialised tools which the proposed method overcomes by using fractional Brownian motion (FBM) as a basis to estimate the real surface within a 15% margin of error while attempting to optimise algorithmic efficiency. This removes the need for complex, expensive equipment and reduces resources spent modelling bed topography. This method also accounts for the change in topography over time due to erosion, sediment transport, and other external factors which could affect the topography of the ground by updating its parameters and generating a new bed. The lattice Boltzmann method (LBM) is used to simulate both stationary and steady flow cases in a side-by-side comparison over the generated bed topography using the proposed method, and a test case taken from an external source. The method, if successful, will be incorporated into the current LBM program used in the testing phase, which will allow an automatic generation of topography for the given situation in future research, removing the need for bed data to be specified.

Keywords: Bed topography, FBM, LBM, shallow water, simulations.

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Authors: A. Salsabili, M.Aghajani Mir, S.Saheri, Noor Ezlin Ahmad Basri

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The main aims in this research are to study the solid waste generation in the Faculty of Engineering and Built Environment in the UKM and at the same time to determine composition and some of the waste characteristics likewise: moisture content, density, pH and C/N ratio. For this purpose multiple campaigns were conducted to collect the wastes produced in all hostels, faculties, offices and so on, during 24th of February till 2nd of March 2009, measure and investigate them with regard to both physical and chemical characteristics leading to highlight the necessary management policies. Research locations are Faculty of Engineering and the Canteen nearby that. From the result gained, the most suitable solid waste management solution will be proposed to UKM. The average solid waste generation rate in UKM is 203.38 kg/day. The composition of solid waste generated are glass, plastic, metal, aluminum, organic and inorganic waste and others waste. From the laboratory result, the average moisture content, density, pH and C/N ratio values from the solid waste generated are 49.74%, 165.1 kg/m3, 5.3, and 7:1 respectively. Since, the food waste (organic waste) were the most dominant component, around 62% from the total waste generated hence, the most suitable solid waste management solution is composting.

Keywords: Solid Waste, Waste Management, Characterizationand Composition

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Authors: Indar Chaerah Gunadin, Adi Soeprijanto, Ontoseno Penangsang

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This paper will discuss about an active power generator scheduling method in order to increase the limit level of steady state systems. Some power generator optimization methods such as Langrange, PLN (Indonesian electricity company) Operation, and the proposed Z-Thevenin-based method will be studied and compared in respect of their steady state aspects. A method proposed in this paper is built upon the thevenin equivalent impedance values between each load respected to each generator. The steady state stability index obtained with the REI DIMO method. This research will review the 500kV-Jawa-Bali interconnection system. The simulation results show that the proposed method has the highest limit level of steady state stability compared to other optimization techniques such as Lagrange, and PLN operation. Thus, the proposed method can be used to create the steady state stability limit of the system especially in the peak load condition.

Keywords: generation scheduling, steady-state stability limit, REI Dimo, margin stability

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Authors: Sachin Vrajlal Rajani, Vivek Pandya, Ankit Suvariya

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Green and renewable energy is getting extraordinary consideration today, because of ecological concerns made by blazing of fossil powers. Photovoltaic and wind power generation are the basic decisions for delivering power in this respects. Producing power by the sun based photovoltaic systems is known to the world, yet control makers may get confounded to pick between on-grid and off-grid systems. In this exploration work, an endeavor is made to compare the off-grid (stand-alone) and on-grid (grid-connected) frameworks. The work presents relative examination, between two distinctive PV frameworks situated at V.V.P. Engineering College, Rajkot. The first framework is 100 kW remain solitary and the second is 60 kW network joined. The real-time parameters compared are; output voltage, load current, power in-flow, power output, performance ratio, yield factor, and capacity factor. The voltage changes and the power variances in both frameworks are given exceptional consideration and the examination is made between the two frameworks to judge the focal points and confinements of both the frameworks.

Keywords: Standalone PV systems, grid connected PV systems, comparison, real time data analysis.

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Authors: R. Moradifar, M. Masahebfard, M. Zahir

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In this article the investigation about installation heat recovery steam generation (HRSG) on the exhaust of turbo generators of phases 2&3 at South Pars Gas Complex is presented. The temperature of exhaust gas is approximately 665 degree centigrade, Installation of heat recovery boiler was simulated in ThermoFlow 17.0.2 software, based on test operation data and the equipments site operation conditions in Pars exclusive economical energy area, the affect of installation HRSG package on the available gas turbine and its operation parameters, ambient temperature, the exhaust temperatures steam flow rate were investigated. Base on the results recommended HRSG package should have the capacity for 98 ton per hour high pressure steam generation this refinery, by use of exhaust of three gas turbines for each package in operation condition of each refinery at 30 degree centigrade. Besides saving energy this project will be an Environment-Friendly project. The Payback Period is estimated approximately 1.8 year, with considering Clean Development Mechanism.

Keywords: HRSG, South pars Gas complex, ThermoFlow 17.0.2 software, energy, turbo generators.

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Authors: Dagnija Blumberga, Toms Prodanuks, Ivars Veidenbergs, Andra Blumberga

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Gas condensing units with inner tubes heat exchangers represent third generation technology and differ from second generation heat and mass transfer units, which are fulfilled by passive filling material layer. The first one improves heat and mass transfer by increasing cooled contact surface of gas and condensate drops and film formed in inner tubes heat exchanger. This paper presents a selection of significant factors which influence the heat and mass transfer. Experimental planning is based on the research and analysis of main three independent variables; velocity of water and gas as well as density of spraying. Empirical mathematical models show that the coefficient of heat transfer is used as dependent parameter which depends on two independent variables; water and gas velocity. Empirical model is proved by the use of experimental data of two independent gas condensing units in Lithuania and Russia. Experimental data are processed by the use of heat transfer criteria-Kirpichov number. Results allow drawing the graphical nomogram for the calculation of heat and mass transfer conditions in the innovative and energy efficient gas cooling unit.

Keywords: Gas condensing unit, filling, inner heat exchanger, package, spraying, tunes.

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Authors: A. Badri

Abstract:

Restructured electricity markets may provide opportunities for producers to exercise market power maintaining prices in excess of competitive levels. In this paper an oligopolistic market is presented that all Generation Companies (GenCos) bid in a Cournot model. Genetic algorithm (GA) is applied to obtain generation scheduling of each GenCo as well as hourly market clearing prices (MCP). In order to consider network constraints a multiperiod framework is presented to simulate market clearing mechanism in which the behaviors of market participants are modelled through piecewise block curves. A mixed integer linear programming (MILP) is employed to solve the problem. Impacts of market clearing process on participants- characteristic and final market prices are presented. Consequently, a novel multi-objective model is addressed for security constrained optimal bidding strategy of GenCos. The capability of price-maker GenCos to alter MCP is evaluated through introducing an effective-supply curve. In addition, the impact of exercising market power on the variation of market characteristics as well as GenCos scheduling is studied.

Keywords: Optimal bidding strategy, Cournot equilibrium, market power, network constraints, market auction mechanism

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Authors: Shang-Lin Hsieh, Lung-Yao Hsu, I-Ju Tsai

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This paper proposes a copyright protection scheme for color images using secret sharing and wavelet transform. The scheme contains two phases: the share image generation phase and the watermark retrieval phase. In the generation phase, the proposed scheme first converts the image into the YCbCr color space and creates a special sampling plane from the color space. Next, the scheme extracts the features from the sampling plane using the discrete wavelet transform. Then, the scheme employs the features and the watermark to generate a principal share image. In the retrieval phase, an expanded watermark is first reconstructed using the features of the suspect image and the principal share image. Next, the scheme reduces the additional noise to obtain the recovered watermark, which is then verified against the original watermark to examine the copyright. The experimental results show that the proposed scheme can resist several attacks such as JPEG compression, blurring, sharpening, noise addition, and cropping. The accuracy rates are all higher than 97%.

Keywords: Color image, copyright protection, discrete wavelet transform, secret sharing, watermarking.

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Authors: Damian Ramajo, Santiago Corzo, Norberto Nigro

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A Multi-dimensional computational fluid dynamics (CFD) two-phase model was developed with the aim to simulate the in-core coolant circuit of a pressurized heavy water reactor (PHWR) of a commercial nuclear power plant (NPP). Due to the fact that this PHWR is a Reactor Pressure Vessel type (RPV), three-dimensional (3D) detailed modelling of the large reservoirs of the RPV (the upper and lower plenums and the downcomer) were coupled with an in-house finite volume one-dimensional (1D) code in order to model the 451 coolant channels housing the nuclear fuel. Regarding the 1D code, suitable empirical correlations for taking into account the in-channel distributed (friction losses) and concentrated (spacer grids, inlet and outlet throttles) pressure losses were used. A local power distribution at each one of the coolant channels was also taken into account. The heat transfer between the coolant and the surrounding moderator was accurately calculated using a two-dimensional theoretical model. The implementation of subcooled boiling and condensation models in the 1D code along with the use of functions for representing the thermal and dynamic properties of the coolant and moderator (heavy water) allow to have estimations of the in-core steam generation under nominal flow conditions for a generic fission power distribution. The in-core mass flow distribution results for steady state nominal conditions are in agreement with the expected from design, thus getting a first assessment of the coupled 1/3D model. Results for nominal condition were compared with those obtained with a previous 1/3D single-phase model getting more realistic temperature patterns, also allowing visualize low values of void fraction inside the upper plenum. It must be mentioned that the current results were obtained by imposing prescribed fission power functions from literature. Therefore, results are showed with the aim of point out the potentiality of the developed model.

Keywords: CFD, PHWR, Thermo-hydraulic, Two-phase flow.

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Authors: Min Ye Koo, Ji Ho Ahn, Byung Il You, Gyo Woo Lee

Abstract:

Everything that is attached to the outside of the vehicle to improve the driving performance of the vehicle by changing the flow characteristics of the surrounding air or to pursue the external personality is called a tuning part. Typical tuning components include front or rear air dam, also known as spoilers, splitter, and side air dam. Particularly, the front air dam prevents the airflow flowing into the lower portion of the vehicle and increases the amount of air flow to the side and front of the vehicle body, thereby reducing lift force generation that lifts the vehicle body, and thus, improving the steering and driving performance of the vehicle. The purpose of this study was to investigate the role of anterior air dam in the flow around a sedan passenger car using computational fluid dynamics. The effects of flow velocity, trajectory of fluid particles on static pressure distribution and pressure distribution on body surface were investigated by varying flow velocity and size of air dam. As a result, it has been confirmed that the front air dam improves the flow characteristics, thereby reducing the generation of lift force of the vehicle, so it helps in steering and driving characteristics.

Keywords: Numerical study, computational fluid dynamics, air dam, tuning parts, drag, lift force.

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Authors: Mustafa Engin Başoğlu, Bekir Çakir

Abstract:

Since large part of electricity is generated by using fossil based resources, energy is an important agenda for countries. In this context, renewable energy sources are alternative to conventional sources due to the depletion of fossil resources, increasing awareness of climate change and global warming concerns. Solar, wind and hydropower energy are the main renewable energy sources. Among of them, since installed capacity of wind power has increased approximately eight times between 2008 - November of 2014, wind energy is a promising source for Turkey. Furthermore, signing of Kyoto Protocol can be accepted as a milestone for Turkey's energy policy. Turkish Government has announced Vision 2023 (energy targets by 2023) in 2010-2014 Strategic Plan prepared by Ministry of Energy and Natural Resources (MENR). Energy targets in this plan can be summarized as follows: Share of renewable energy sources in electricity generation is 30% of total electricity generation by 2023. Installed capacity of wind energy will be 20 GW by 2023. Other renewable energy sources such as solar, hydropower and geothermal are encouraged with new incentive mechanisms. Dependence on foreign energy is reduced for sustainability and energy security. On the other hand, since Turkey is surrounded by three coastal areas, wind energy potential is convenient for wind power application. As of November of 2014, total installed capacity of wind power plants is 3.51 GW and a lot of wind power plants are under construction with capacity 1.16 GW. Turkish government also encourages the locally manufactured equipments. In this context, one of the projects funded by private sector, universities and TUBİTAK names as MILRES is an important project aimed to promote the use wind energy in electricity generation. Within this project, wind turbine with 500 kW power has been produced and will be installed at the beginning of the 2015. After that, by using the experience obtained from the first phase of the project, a wind turbine with 2.5 MW power will be manufactured in an industrial scale.

Keywords: Wind energy, wind speed, Vision 2023, MILRES (national wind energy system), wind energy potential, Turkey.

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Authors: Suma. V., T. R. Gopalakrishnan Nair

Abstract:

Defect prevention is the most vital but habitually neglected facet of software quality assurance in any project. If functional at all stages of software development, it can condense the time, overheads and wherewithal entailed to engineer a high quality product. The key challenge of an IT industry is to engineer a software product with minimum post deployment defects. This effort is an analysis based on data obtained for five selected projects from leading software companies of varying software production competence. The main aim of this paper is to provide information on various methods and practices supporting defect detection and prevention leading to thriving software generation. The defect prevention technique unearths 99% of defects. Inspection is found to be an essential technique in generating ideal software generation in factories through enhanced methodologies of abetted and unaided inspection schedules. On an average 13 % to 15% of inspection and 25% - 30% of testing out of whole project effort time is required for 99% - 99.75% of defect elimination. A comparison of the end results for the five selected projects between the companies is also brought about throwing light on the possibility of a particular company to position itself with an appropriate complementary ratio of inspection testing.

Keywords: Defect Detection and Prevention, Inspections, Software Engineering, Software Process, Testing.

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Authors: María Jesús Luengo-Valderrey, Mónica Moso-Díez

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In the knowledge-based economy, innovation is considered essential in order to achieve survival and growth in organizations. On the other hand, knowledge management is currently understood as one of the keys to innovation process. Both factors are generally admitted as generators of competitive advantage in organizations. Specifically, activities on R&D&I and those that generate internal knowledge have a positive influence in innovation results. This paper examines this effect and if it is similar or not is what we aimed to quantify in this paper. We focus on the impact that proportion of knowledge workers, the R&D&I investment, the amounts destined for ICTs and training for innovation have on the variation of tangible and intangibles returns for the sector of high and medium technology in Spain. To do this, we have performed an empirical analysis on the results of questionnaires about innovation in enterprises in Spain, collected by the National Statistics Institute. First, using clusters methodology, the behavior of these enterprises regarding knowledge management is identified. Then, using SEM methodology, we performed, for each cluster, the study about cause-effect relationships among constructs defined through variables, setting its type and quantification. The cluster analysis results in four groups in which cluster number 1 and 3 presents the best performance in innovation with differentiating nuances among them, while clusters 2 and 4 obtained divergent results to a similar innovative effort. However, the results of SEM analysis for each cluster show that, in all cases, knowledge workers are those that affect innovation performance most, regardless of the level of investment, and that there is a strong correlation between knowledge workers and investment in knowledge generation. The main findings reached is that Spanish high and medium technology companies improve their innovation performance investing in internal knowledge generation measures, specially, in terms of R&D activities, and underinvest in external ones. This, and the strong correlation between knowledge workers and the set of activities that promote the knowledge generation, should be taken into account by managers of companies, when making decisions about their investments for innovation, since they are key for improving their opportunities in the global market.

Keywords: High and medium technology sector, innovation, knowledge management, Spanish companies.

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