Search results for: optimization wind power plant

Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

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This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

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Authors: Weng Jiantao, Wu Yiqun

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The efficiency of natural ventilation, wind pressure distribution on building surface, wind comfort for pedestrians and buildings’ wind tolerance in traditional settlements are closely related to the pattern of terrain. On the basis of field research on the typical island terrain in China, the physical and mathematical models are established by using CFD software, and then the simulation results of the wind field are exported. We discuss the relationship between wind direction and wind field results. Furthermore simulation results are imported into ArcGIS platform. The evaluation model of island site selection is established with considering slope factor. We realize the visual model of site selection on complex island terrain. The multi-plans of certain residential are discussed based on wind simulation; at last the optimal project is selected. Results can provide the theory guidance for settlement planning and construction in China's traditional island.

Keywords: CFD, island terrain, site selection, construction mechanism

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Authors: Ramin Rezaei, Terry Ng, Abdollah Afjeh

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Near wake development of a wind turbine affects the aerodynamic loads on the tower and the wind turbine. Design considerations of both isolated wind turbines and wind farms must include unsteady wake flow conditions under which the turbines must operate. The consequent aerodynamic loads could lead to over design of wind turbines and adversely affect the cost of wind turbines and, in turn, the cost of energy produced by wind turbines. Reducing the weight of turbine rotors is particularly desirable since larger wind turbine rotors can be utilized without significantly increasing the cost of the supporting structure. Larger rotor diameters produce larger swept areas and consequently greater energy production from the wind thereby reducing the levelized cost of wind energy. To understand the development and structure of the near tower wake of a wind turbine, an experimental study was conducted to describe the flow field of the near wake for both upwind and downwind turbines. The study was conducted under controlled environment of a wind tunnel using a scaled model of a turbine. The NREL 5 MW reference wind turbine was used as a baseline design and was modified as necessary to design and build upwind and downwind scaled wind turbine models. This paper presents the results of the wind tunnel study using turbine models to quantify the near wake of upwind and downwind wind turbine configurations for various lengths of tower-to-turbine spacing. The variations of mean velocity and turbulence are measured using a computer-controlled, traversing hot wire probe. Additionally, smoke flow visualizations were conducted to qualitatively study the wake. The results show a more rapid dissipation of the near wake for an upwind configuration. The results can readily be incorporated into low fidelity system level turbine simulation tools to more accurately account for the wake on the aerodynamic loads of a upwind and downwind turbines.

Keywords: hot wire anemometry, near wake, upwind and downwind turbine. Hot wire anemometry, near wake, upwind and downwind turbine

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Authors: Imane El Karaoui, Mohammed Maaroufi, Hamid Chaikhy

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Doubly Fed Induction Generator (DFIG) is one of the most reliable wind generator. Major problem in wind power generation is to generate Sinusoidal signal with very low THD on variable speed caused by inverter two levels used. This paper presents a multi-level inverter whose objective is to reduce the THD and the dimensions of the output filter. This work proposes a three-level NPC-type inverter, the results simulation are presented demonstrating the efficiency of the proposed inverter.

Keywords: DFIG, multilevel inverter, NPC inverter, THD, induction machine

Procedia PDF Downloads 235

Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

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Authors: Takeshi Takemoto, Naoya Suzuki, Naohisa Takagaki, Satoru Komori, Masako Terui, George Truscott

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Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place.

Keywords: air-sea interaction, drag coefficient, air-sea momentum flux, CFD (Computational Fluid Dynamics)

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Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

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Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

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Authors: S. W. Chen, W. K. Lin, J. R. Wang, C. Shih, H. T. Lin, H. C. Chang, W. Y. Li

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Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the over pressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study.

Keywords: TRACE, safety analysis, BWR/6, FRAPTRA

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

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Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Ioana Neamtu

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This paper investigates the potential for demand-side management for the system price in the Nordic electricity market and the price effects of introducing wind-power into the system. The model proposed accounts for the micro-structure of the Nordic electricity market by modeling each hour individually, while still accounting for the relationship between the hours within a day. This flexibility allows us to explore the differences between peak and shoulder demand hours. Preliminary results show potential for demand response management, as indicated by the price elasticity of demand as well as a small but statistically significant decrease in price, given by the wind power penetration. Moreover, our study shows that these effects are stronger during day-time and peak hours,compared to night-time and shoulder hours.

Keywords: structural model, GMM estimation, system of equations, electricity market

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Authors: Abdulrazak Jinadu Otaru, Ahmed Almulhim, Hassan Alhassan, Mohammed Sabri

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Saudi Arabia is host to a state-owned oil and gas corporation, known as Saudi ARAMCO, that is responsible for the highest emissions of carbon dioxide (CO₂) due to the heavy reliance on fossil fuels as an energy source for various sectors such as transportation, aerospace, manufacturing, and residential use. Unfortunately, the detrimental consequences of CO₂ emissions include escalating temperatures in the Middle East region, posing significant obstacles in terms of food security and water scarcity for the Kingdom of Saudi Arabia. As part of the Saudi Vision 2030 initiative, which aims to reduce the country's reliance on fossil fuels by 50 %, this study focuses on designing a plant that will produce approximately 100,000 metric tons per year (MTPY) of green hydrogen (H₂) using brine as the primary feedstock. The proposed facility incorporates a double electrolytic technology that first separates brine or sodium chloride (NaCl) into sodium hydroxide, hydrogen gas, and chlorine gas. The sodium hydroxide is then used as an electrolyte in the splitting of water molecules through the supply of electrical energy in a second-stage electrolyser to produce green hydrogen. The study encompasses a comprehensive analysis of process descriptions and flow diagrams, as well as materials and energy balances. It also includes equipment design and specification, cost analysis, and considerations for safety and environmental impact. The design capitalizes on the abundant brine supply, a byproduct of the world's largest desalination plant located in Al Jubail, Saudi Arabia. Additionally, the design incorporates the use of available renewable energy sources, such as solar and wind power, to power the proposed plant. This approach not only helps reduce carbon emissions but also aligns with Saudi Arabia's energy transition policy. Furthermore, it supports the United Nations Sustainable Development Goals on Sustainable Cities and Communities (Goal 11) and Climate Action (Goal 13), benefiting not only Saudi Arabia but also other countries in the Middle East.

Keywords: plant design, electrolysis, brine, sodium hydroxide, chlorine gas, green hydrogen

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Authors: Luis Lara-Valencia, Mateo Ramirez-Acevedo, Daniel Caicedo, Jose Brito, Yosef Farbiarz

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Controlling wind-induced vibrations as well as aerodynamic forces, is an essential part of the structural design of tall buildings in order to guarantee the serviceability limit state of the structure. This paper presents a numerical investigation on the optimal design parameters of a Tuned Inerter Damper (TID) based system for the control of wind-induced vibration in tall buildings. The control system is based on the conventional TID, with the main difference that its location is changed from the ground level to the last two story-levels of the structural system. The TID tuning procedure is based on an evolutionary cultural algorithm in which the optimum design variables defined as the frequency and damping ratios were searched according to the optimization criteria of minimizing the root mean square (RMS) response of displacements at the nth story of the structure. A Monte Carlo simulation was used to represent the dynamic action of the wind in the time domain in which a time-series derived from the Davenport spectrum using eleven harmonic functions with randomly chosen phase angles was reproduced. The above-mentioned methodology was applied on a case-study derived from a 37-story prestressed concrete building with 144 m height, in which the wind action overcomes the seismic action. The results showed that the optimally tuned TID is effective to reduce the RMS response of displacements up to 25%, which demonstrates the feasibility of the system for the control of wind-induced vibrations in tall buildings.

Keywords: evolutionary cultural algorithm, Monte Carlo simulation, tuned inerter damper, wind-induced vibrations

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Authors: Huiqiang Yang, Domingo Santana

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Reducing parasitic power consumption of concentrating solar power plants is the main challenge to increase the overall efficiency, particularly for molten salt tower technology. One of the most effective approaches to reduce the parasitic power consumption is to implement a natural draft dry cooling system instead of the standard utilized mechanical draft dry cooling system. In this paper, a thermo-economic analysis of a natural draft direct cooling system was performed based on a 100MWe commercial scale molten salt power plant. In this configuration with a natural draft direct cooling system, the exhaust steam from steam turbine flows directly to the heat exchanger bundles inside the natural draft dry cooling tower, which eliminates the power consumption of circulation pumps or fans, although the cooling tower shadows a portion of the heliostat field. The simulation results also show that compared to a mechanical draft cooling system the annual solar field efficiency is decreased by about 0.2% due to the shadow, which is equal to a reduction of approximately 13% of the solar field area. As a contrast, reducing the solar field size by 13% in purpose in a molten salt power plant with a natural draft drying cooling system actually will lead to a reduction of levelized cost of electricity (LCOE) by about 4.06% without interfering the power generated.

Keywords: molten salt power tower, natural draft dry cooling, parasitic power consumption, commercial scale

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Authors: Kathy Mwende Kiema, Remember Samu, Murat Fahrioglu

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The potential of power generation from solar resources has been established as being robust in sub Saharan Africa. Consequently many governments in the region have encouraged the exploitation of this resource through, inter alia direct funding, subsidies and legislation (such as feed in tariffs). Through a case study of Kenya and Zimbabwe it is illustrated that a good deal of proposed grid connected solar power projects and related feed in tariffs have failed to take into account key economic and technical considerations in the selection of solar technologies to be implemented. This paper therefore presents a comparison between concentrated solar power (CSP) and solar photovoltaic (PV) to assess which technology is better suited to meet the energy demand for a given set of prevailing conditions. The evaluation criteria employed is levelized cost of electricity (LCOE), net present value (NPV) and plant capacity factor. The outcome is therefore a guide to aid policy makers and project developers in choosing between CSP and PV given certain solar irradiance values, planned nominal plant capacity, availability of water resource and a consideration of whether or not the power plant is intended to compete with existing technologies, primarily fossil fuel powered, in meeting the peak load.load.

Keywords: capacity factor, peak load, solar PV, solar CSP

Procedia PDF Downloads 278

Authors: Zakir Husain

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Main objective of a power transformer design optimization problem requires minimizing the total overall cost and/or mass of the winding and core material by satisfying all possible constraints obligatory by the standards and transformer user requirement. The constraints include appropriate limits on winding fill factor, temperature rise, efficiency, no-load current and voltage regulation. The design optimizations tasks are a constrained minimum cost and/or mass solution by optimally setting the parameters, geometry and require magnetic properties of the transformer. In this paper, present the above design problems have been formulated by using genetic algorithm (GA) and simulated annealing (SA) on the MATLAB platform. The importance of the presented approach is stems for two main features. First, proposed technique provides reliable and efficient solution for the problem of design optimization with several variables. Second, it guaranteed to obtained solution is global optimum. This paper includes a demonstration of the application of the genetic programming GP technique to transformer design.

Keywords: optimization, power transformer, genetic algorithm (GA), simulated annealing technique (SA)

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Authors: Poojan Vora, Hardik Pancholi, Sanket Tajane, Harsh Shah, Elias Keedy

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The global COVID-19 pandemic has affected the industry drastically in many ways. Even though the vaccine is being distributed quickly and despite the decreasing number of positive cases, testing is projected to remain a key aspect of the ‘new normal’. Improving existing plant layout and improving safety within the facility are of great importance in today’s industries because of the need to ensure productivity optimization and reduce safety risks. In practice, it is essential for any manufacturing plant to reduce nonvalue adding steps such as the movement of materials and rearrange similar processes. In the current pandemic situation, optimized layouts will not only increase safety measures but also decrease the fixed cost per unit manufactured. In our case study, we carefully studied the existing layout and the manufacturing steps of a new Texas start-up company that manufactures COVID testing kits. The effects of production rate are incorporated with the computerized relative allocation of facilities technique (CRAFT) algorithm to improve the plant layout and estimate the optimization parameters. Our work reduces the company’s material handling time and increases their daily production. Real data from the company are used in the case study to highlight the importance of colleges in fostering small business needs and improving the collaboration between college researchers and industries by using existing models to advance best practices.

Keywords: computerized relative allocation of facilities technique, facilities planning, optimization, start-up business

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Authors: Ali Ravangard, S. Mohammadi

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Shunt Capacitors have several uses in the electric power systems. They are utilized as sources of reactive power by connecting them in line-to-neutral. Electric utilities have also connected capacitors in series with long lines in order to reduce its impedance. This is particularly common in the transmission level, where the lines have length in several hundreds of kilometers. However, this post will generally discuss shunt capacitors. In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. For solving the problem, a new enhanced cuckoo optimization algorithm is presented.The proposed method is tested on distribution test system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: capacitor placement, power losses, voltage stability, radial distribution systems

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Authors: Samuel Abebe Ebebo

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Scale precipitation causes a major issue for geothermal power plants because it reduces the production rate of geothermal energy. Each geothermal power plant's different chemical and physical conditions can cause the scale to precipitate under a particular set of fluid-rock interactions. Depending on the mineral, it is possible to have scale in the production well, steam separators, heat exchangers, reinjection wells, and everywhere in between. The scale consists mainly of smectite and trace amounts of chlorite, magnetite, quartz, hematite, dolomite, aragonite, and amorphous silica. The smectite scale is one of the difficult scales at injection wells in geothermal power plants. X-ray diffraction and chemical composition identify this smectite as Stevensite. The characteristics and the scale of each injection well line are different depending on the fluid chemistry. The smectite scale has been widely distributed in pipelines and surface plants. Mineral water equilibrium showed that the main factors controlling the saturation indices of smectite increased pH and dissolved Mg concentration due to the precipitate on the equipment surface. This study aims to characterize the scales and geothermal fluids collected from the Onuma geothermal power plant in Akita Prefecture, Japan. Field tests were conducted on October 30–November 3, 2021, at Onuma to determine the pH control methods for preventing magnesium silicate scaling, and as exemplified, the formation of magnesium silicate hydrates (M-S-H) with MgO to SiO2 ratios of 1.0 and pH values of 10 for one day has been studied at 25 °C. As a result, M-S-H scale formation could be suppressed, and stevensite formation could also be suppressed when we can decrease the pH of the fluid by less than 8.1, 7.4, and 8 (at 97 °C) in the fluid from O-3Rb and O-6Rb, O-10Rg, and O-12R, respectively. In this context, the scales and fluids collected from injection wells at a geothermal power plant in Japan were analyzed and characterized to understand the formation conditions of Mg-silicate scales with on-site synthesis experiments. From the results of the characterizations and on-site synthesis experiments, the inhibition method of their scale formation is discussed based on geochemical modeling in this study.

Keywords: magnesium silicate, scaling, inhibitor, geothermal power plant

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Authors: Prateek Kishore, T. M. Muruganandam

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Supersonic wind tunnel nozzles are generally capable of producing a constant Mach number flow in the test section of the wind tunnel. As a result, most of the supersonic vehicles are widely designed using steady state flow characteristics which may have errors while facing unsteady situations. This study aims to explore the possibility of varying the Mach number of the flow during wind tunnel operation. The nozzle walls are restricted to be inflexible for cooling near the throat due to high stagnation temperature requirement of the flow to simulate the conditions as experienced by the vehicle. Two simple independent mechanisms, rotation and translation of nozzle walls have been analyzed and the nozzle ranges have been optimized to vary the Mach number from Mach 2 to Mach 5 using minimum number of nozzles in the wind tunnel.

Keywords: method of characteristics, nozzle, supersonic wind tunnel, variable mach number

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Authors: Saeed Kamarian, Mahmoud Shakeri

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Sandwich structures are used in a variety of engineering applications including aircraft, construction and transportation where strong, stiff and light structures are required. In this paper, frequency maximization of Functionally Graded Sandwich (FGS) beams resting on Pasternak foundations is investigated. A generalized power-law distribution with four parameters is considered for material distribution through the thicknesses of face layers. Since the search space is large, the optimization processes becomes so complicated and too much time consuming. Thus a novel meta–heuristic called Imperialist Competitive Algorithm (ICA) which is a socio-politically motivated global search strategy is implemented to improve the speed of optimization process. Results show the success of applying ICA for engineering problems especially for design optimization of FGM sandwich beams.

Keywords: sandwich beam, functionally graded materials, optimization, imperialist competitive algorithm

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Authors: Rishikesh Dingari, Sai Kiran Dornala

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In this paper, a simple method of achieving maximum power by mechanical energy transmission device (METD) with integration to induction generator is proposed. METD functioning is explained and dynamic response of system to step input is plotted. Induction generator is being operated at self-excited mode with excitation capacitor at stator. Voltage and current are observed when linked to METD.

Keywords: mechanical energy transmitting device(METD), self-excited induction generator, wind turbine, hydraulic actuators

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Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: Abdalla Mohamed Eblabla

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Due to the high increase and demand for a wide assortment of applications that require low-cost, high-efficiency, and compact systems, RF power amplifiers are considered the most critical design blocks and power consuming components in wireless communication, TV transmission, radar, and RF heating. Therefore, much research has been carried out in order to improve the performance of power amplifiers. Classes-A, B, C, D, E, and F are the main techniques for realizing power amplifiers. An implementation of high efficiency class-F power amplifier with Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) was realized in this paper. The simulation and optimization of the class-F power amplifier circuit model was undertaken using Agilent’s Advanced Design system (ADS). The circuit was designed using lumped elements.

Keywords: Power Amplifier (PA), gallium nitride (GaN), Agilent’s Advanced Design System (ADS), lumped elements

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Authors: S. P. Koko, K. Kusakana, H. J. Vermaak

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Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).

Keywords: economic analysis, micro-hydrokinetic, rural-electrification, cost of energy (COE), net present cost (NPC)

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Authors: F. Hafdhi, T. Khir, A. Ben Yahia, A. Ben Brahim

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An Energetic and exergetic analysis is conducted on a Steam Turbine Power Plant of an existing Phosphoric Acid Factory. The heat recovery systems used in different parts of the plant are also considered in the analysis. Mass, thermal and exergy balances are established on the main compounds of the factory. A numerical code is established using EES software to perform the calculations required for the thermal and exergy plant analysis. The effects of the key operating parameters such as steam pressure and temperature, mass flow rate as well as seawater temperature, on the cycle performances are investigated. A maximum Exergy Loss Rate of about 72% is obtained for the melters, followed by the condensers, heat exchangers and the pumps. The heat exchangers used in the phosphoric acid unit present exergetic efficiencies around 33% while 60% to 72% are obtained for steam turbines and blower. For the explored ranges of HP steam temperature and pressure, the exergy efficiencies of steam turbine generators STGI and STGII increase of about 2.5% and 5.4% respectively. In the same way, optimum HP steam flow rate values, leading to the maximum exergy efficiencies are defined.

Keywords: steam turbine generator, energy efficiency, exergy efficiency, phosphoric acid plant

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Authors: J. R. Wang, H. T. Lin, H. C. Chen, C. Shih, S. W. Chen, S. C. Chiang, C. C. Liu

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In this research, TRACE model of Chinshan BWR/4 Nuclear Power Plant (NPP) has been developed for the simulation and analysis of Ultimate Response Guideline (URG). The main actions of URG are the depressurization and low pressure water injection of reactor and containment venting. This research focuses to verify the URG efficiency under Fukushima-like conditions. Trace analysis results show that the URG can keep the PCT below the criteria 1088.7 K under Fukushima-like conditions. It indicated that Chinshan NPP was safe.

Keywords: BWR, trace, safety analysis, URG

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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The simulation in wind tunnel is used thoroughly to model real situations of drainages of air. Besides the automotive industry, a great number of applications can be numbered: dispersion of pollutant, studies of pedestrians comfort and dispersion of particles. This work had the objective of visualizing the characteristics aerodynamics of two automobiles in different ways. To accomplish that drainage of air a fan that generated a speed exists (measured with anemometer of hot thread) of 4,1m/s and 4,95m/s. To visualize the path of the air through the cars, in the wind tunnel, smoke was used, obtained with it burns of vegetable oil. For “to do smoke” vegetable oil was used, that was burned for a tension of 20 V generated by a thread of 2,5 mm. The cars were placed inside of the wind tunnel with the drainage of “air-smoke” and photographed, registering like this the path lines around them, in the 3 different speeds.

Keywords: aerodynamics, vehicle drag, vegetable oil, wind tunnel

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Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

Abstract:

The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

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