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Records with Subject: Optimization
Showing records 1381 to 1405 of 1630. [First] Page: 1 53 54 55 56 57 58 59 60 61 Last
An Intelligent Optimized Route-Discovery Model for IoT-Based VANETs
Dinesh Karunanidy, Rajakumar Ramalingam, Ankur Dumka, Rajesh Singh, Ibrahim Alsukayti, Divya Anand, Habib Hamam, Muhammad Ibrahim
February 22, 2023 (v1)
Subject: Optimization
Keywords: autonomous vehicle, Energy Efficiency, intelligent route discovery, IoT-based VANET, java macaque algorithm
Intelligent Transportation system are becoming an interesting research area, after Internet of Things (IoT)-based sensors have been effectively incorporated in vehicular ad hoc networks (VANETs). The optimal route discovery in a VANET plays a vital role in establishing reliable communication in uplink and downlink direction. Thus, efficient optimal path discovery without a loop-free route makes network communication more efficient. Therefore, this challenge is addressed by nature-inspired optimization algorithms because of their simplicity and flexibility for solving different kinds of optimization problems. NIOAs are copied from natural phenomena and fall under the category of metaheuristic search algorithms. Optimization problems in route discovery are intriguing because the primary objective is to find an optimal arrangement, ordering, or selection process. Therefore, many researchers have proposed different kinds of optimization algorithm to maintain the balance between intensifica... [more]
Power Consumption Analysis and Experimental Study on the Kneading and Cutting Process of Licorice Stem in Horizontal Total Mixed Ration Mixer
Wentao Li, Baoqin Wen, Pengxiang Song, Yameng Shi, Jie Zhang, Jingbin Li, Junpeng Liang, Tianyang Li, Beichuan Qu
February 22, 2023 (v1)
Subject: Optimization
Keywords: experimental study, kneading power consumption, licorice stem, standard straw length rate
Aiming at the problems of high-power consumption and insufficient kneading and cutting of roughage in the total mixed ration mixer. In this paper, licorice stems were taken as experimental objects, the horizontal twin-shaft TMR mixer was used to carry out the experimental study. It should be as brief as possible and concise. Through the kneading and cutting process power analysis, determine the influencing factors of kneading and cutting power consumption. The auger speed, processing time and blade type were taken as experimental factors, with standard straw length rate and power consumption as indicators, Box−Behnken test with three factors and three levels was carried out, analysis of variance was performed on the test results, the results show that the significant effect of each factor on the standard grass length is processing time, blade type and auger speed in descending order. The significance of the influence on power consumption from large to small is auger speed, processing t... [more]
Thermodynamic Selection of the Optimal Working Fluid for Organic Rankine Cycles
Attila R. Imre, Réka Kustán, Axel Groniewsky
February 22, 2023 (v1)
Subject: Optimization
Keywords: adiabatic expansion, isentropic expansion, Optimization, T-s diagram, working fluid classification
A novel method proposed to choose the optimal working fluid—solely from the point of view of expansion route—for a given heat source and heat sink (characterized by a maximum and minimum temperature). The basis of this method is the novel classification of working fluids using the sequences of their characteristic points on temperature-entropy space. The most suitable existing working fluid can be selected, where an ideal adiabatic (isentropic) expansion step between a given upper and lower temperature is possible in a way, that the initial and final states are both saturated vapour states and the ideal (isentropic) expansion line runs in the superheated (dry) vapour region all along the expansion. Problems related to the presence of droplets or superheated dry steam in the final expansion state can be avoided or minimized by using the working fluid chosen with this method. Results obtained with real materials are compared with those gained with model (van der Waals) fluids; based on t... [more]
Quantitative Evaluation of the “Non-Enclosed” Microseismic Array: A Case Study in a Deeply Buried Twin-Tube Tunnel
Hang Zhang, Chunchi Ma, Tianbin Li
February 22, 2023 (v1)
Subject: Optimization
Keywords: microseismic monitoring, non-enclosed array, source location accuracy, twin-tube tunnel
The high-stress hazards of underground engineering have stimulated the exploration of microseismic monitoring and early warning methods. To achieve a good monitoring effect, the monitoring object is usually enclosed by a microseismic array (sensor array) (e.g., slope engineering, etc.). However, some characteristics of a buried tunnel, including “linear”, “deep-buried”, and “long”, make it difficult to deploy a reasonable microseismic array, which leads to the microseismic array being non-enclosed for the monitoring object. Application of the non-enclosed microseismic array yields decreases the accuracy of the source location. To solve the problem wisely, this paper deals with the feasibility of non-enclosed microseismic arrays (axial-extended, lateral-extended, and twin-tube arrays) by introducing a quantitative method. To this end, an optimized microseismic array with the best source location accuracy for a twin-tube expressway tunnel is proposed. The obtained results reveal that the... [more]
Spectrum Analysis and Optimization of the Axial Magnetic Gear with Halbach Permanent Magnet Arrays
Fang Hu, Yilan Zhou, Hesong Cui, Xiao Liu
February 22, 2023 (v1)
Subject: Optimization
Keywords: axial magnetic gear, Halbach, Optimization, parametric analysis
In order to study the contribution of each harmonic to the output torque and axial torque of the axial magnetic gear with Halbach permanent magnet arrays (HAMG), torque and axial force calculation formulas of the HAMG are proposed based on the air-gap flux density distribution of the HAMG. Because of the difference of the air-gap flux densities at different radii, two simplified torque and axial force calculation formulas are proposed and compared. To improve the torque capability of the HAMG, parametric analysis of eight dimensional parameters is firstly conducted. By parametric analysis, six parameters such as the inner radius have been found to have obvious impact on the output torque and output torque density of the HAMG. The optimization using Maxwell software is then executed for maximizing the output torque density of the HAMG. The output torque density of the optimized HAMG is improved from 78.1 kNm/m3 to 93.3 kNm/m3 with an increase of 19%. Furthermore, spectrum analysis is al... [more]
A Data-Driven Workflow Approach to Optimization of Fracture Spacing in Multi-Fractured Shale Oil Wells
Xu Yang, Boyun Guo
February 22, 2023 (v1)
Subject: Optimization
Keywords: fracturing, Optimization, shale oil, unconventional, well
A data-driven workflow approach is presented in this study for optimizing fracture spacing of multifractured horizontal wells (MFHW) in shale oil reservoirs. The workflow employs a simple well productivity model for the initial design of hydraulic fracturing well completions. This provides a transparent approach to the identification of key fracturing parameters affecting well productivity. The workflow uses transient pressure or production data to identify fracture interference. This offers a reliable and cost-effective means for assessment of well production potential in terms of optimization of fracture spacing in the MFHW. Result of a field case study indicated that three wells were drilled in an area with dense natural fractures, and the fracture spacing of MFHW in this area was short enough to effectively drain the stimulated reservoir volume (SRV), while the other three wells were drilled in an area with less natural fractures, and the fracture spacing of MFHW in this area could... [more]
Investigation on Optimization Design of Offshore Wind Turbine Blades based on Particle Swarm Optimization
Yong Ma, Aiming Zhang, Lele Yang, Chao Hu, Yue Bai
February 22, 2023 (v1)
Subject: Optimization
Keywords: blade optimization, FAST, PSO algorithm, time-domain coupled model, wind turbine
Offshore wind power has become an important trend in global renewable energy development. Based on a particle swarm optimization (PSO) algorithm and FAST program, a time-domain coupled calculation model for a floating wind turbine is established, and a combined optimization design method for the wind turbine’s blade is developed in this paper. The influence of waves on the power of the floating wind turbine is studied in this paper. The results show that, with the increase of wave height, the power fluctuation of the wind turbine increases and the average power of the wind turbine decreases. With the increase of wave period, the power oscillation amplitude of the wind turbine increases, and the power of the wind turbine at equilibrium position decreases. The optimal design of the offshore floating wind turbine blade under different wind speeds is carried out. The results show that the optimum effect of the blades is more obvious at low and mid-low wind speeds than at rated wind speeds.... [more]
Biogas Production and Heat Transfer Performance of a Multiphase Flow Digester
Pei Guo, Jiri Zhou, Rongjiang Ma, Nanyang Yu, Yanping Yuan
February 22, 2023 (v1)
Subject: Optimization
Keywords: anaerobic digestion, biogas production, experiment, multiphase flow, optimization analysis
Traditional static anaerobic digestion technology presents the disadvantages of a low gas production rate and long digestion cycle, which is not conducive to the treatment of livestock manure. A 12 m3 multiphase flow anaerobic digester (MFD) was developed in this study to improve the biogas production rate and maintain constant temperature digestion during winters. Full-scale field experiments were conducted on the biogas production rate at different temperatures, the dynamic digestion effects, and the dynamic heating digestion effects of the system at Sichuan, China. A comparison of the dynamic and static digestion results of 50 days indicated that the biogas production for the dynamic digestion (DD) group was 115.22 m3 or 127.1% higher than that of the static digestion (SD) group with the same digestion temperature. The results of the heat transfer performance experiment revealed that the heat transfer rate of the system increased significantly, and the temperature of the biogas slur... [more]
Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets
Arthur H.A. Melani, Carlos A. Murad, Adherbal Caminada Netto, Gilberto F.M. Souza, Silvio I. Nabeta
February 22, 2023 (v1)
Subject: Optimization
Keywords: availability, cooling tower, generalized stochastic Petri net, GSPN, maintenance, reliability
Determining the ideal size of maintenance staff is a daunting task, especially in the operation of large and complex mechanical systems such as thermal power plants. On the one hand, a significant investment in maintenance is necessary to maintain the availability of the system. On the other hand, it can significantly affect the profit of the plant. Several mathematical modeling techniques have been used in many different ways to predict and improve the availability and reliability of such systems. This work uses a modeling tool called generalized stochastic Petri net (GSPN) in a new way, aiming to determine the effect that the number of maintenance teams has on the availability and performance of a coal-fired power plant cooling tower. The results obtained through the model are confronted with a thermodynamic analysis of the cooling tower that shows the influence of this system’s performance on the efficiency of the power plant. Thus, it is possible to determine the optimal size of th... [more]
Optimization of an Organic Rankine Cycle System for an LNG-Powered Ship
Jamin Koo, Soung-Ryong Oh, Yeo-Ul Choi, Jae-Hoon Jung, Kyungtae Park
February 22, 2023 (v1)
Subject: Optimization
Keywords: cold energy, lng fuel supply system, LNG-powered ship, Optimization, organic Rankine cycle, Particle Swarm Optimization
Recovering energy from waste energy sources is an important issue as environmental pollution and the energy crisis become serious. In the same context, recovering liquefied natural gas (LNG) cold energy from an LNG-powered ship is also important in terms of energy savings. To this end, this study investigated a novel solution for a LNG-powered ship to recover LNG cold energy. Six different organic Rankine cycle (ORC) systems (three for high-pressure dual-fuel engines and three for medium-pressure dual-fuel engines) were proposed and optimized; nine different working fluids were investigated; annualized costs for installing proposed ORC systems were estimated based on the optimization results. In addition, a sensitivity analysis was performed to identify the effect of uncertainties on the performance of the ORC systems. As a result, the ORC system for the medium-pressure engines with direct expansion, multi-condensation levels, and a high evaporation temperature exhibited the best perfo... [more]
Research and Application of a Novel Combined Model Based on Multiobjective Optimization for Multistep-Ahead Electric Load Forecasting
Yechi Zhang, Jianzhou Wang, Haiyan Lu
February 22, 2023 (v1)
Subject: Optimization
Keywords: combined model, data preprocessing technique, electric load forecasting, multiobjective optimization algorithm
Accurate forecasting of electric loads has a great impact on actual power generation, power distribution, and tariff pricing. Therefore, in recent years, scholars all over the world have been proposing more forecasting models aimed at improving forecasting performance; however, many of them are conventional forecasting models which do not take the limitations of individual predicting models or data preprocessing into account, leading to poor forecasting accuracy. In this study, to overcome these drawbacks, a novel model combining a data preprocessing technique, forecasting algorithms and an advanced optimization algorithm is developed. Thirty-minute electrical load data from power stations in New South Wales and Queensland, Australia, are used as the testing data to estimate our proposed model’s effectiveness. From experimental results, our proposed combined model shows absolute superiority in both forecasting accuracy and forecasting stability compared with other conventional forecast... [more]
Research on Location and Capacity Optimization Method for Electric Vehicle Charging Stations Considering User’s Comprehensive Satisfaction
Tao Yi, Xiao-bin Cheng, Hao Zheng, Jin-peng Liu
February 22, 2023 (v1)
Subject: Optimization
Keywords: electric vehicle charging station, fuzzy membership degree, immune algorithm, location and capacity optimization, user satisfaction
The development of electric vehicles has significant value for the sustainable utilization of energy resources. However, the unreasonable construction of charging stations causes problems such as low user satisfaction, waste of land resources, unstable power systems, and so on. Reasonable planning of the location and capacity of charging stations is of great significance to users, investors and power grids. This paper synthetically considers three indicators of user satisfaction: charging convenience, charging cost and charging time. Considering the load and charging requirements, the model of electric vehicle charging station location and volume is established, and the model based on artificial immune algorithm is used to optimize the solution. An empirical analysis was conducted based on a typical regional survey. The research results show that increasing the density of charging stations, lowering the charging price and shortening the charging time can effectively improve user satisf... [more]
Coordinated Voltage Regulation by On-Load Tap Changer Operation and Demand Response Based on Voltage Ranking Search Algorithm
Qiangqiang Xie, Xiangrong Shentu, Xusheng Wu, Yi Ding, Yongzhu Hua, Jiadong Cui
February 22, 2023 (v1)
Subject: Optimization
Keywords: demand response, power distribution system, real-time optimization, smart grid, voltage regulation
The growing penetration of photovoltaic (PV) systems may cause an over-voltage problem in power distribution systems. Meanwhile, charging of massive electric vehicles may cause an under-voltage problem. The over- and under-voltage problems make the voltage regulation become more challenging in future power distribution systems. Due to the development of smart grid and demand response, flexible resources such as PV inverters and controllable loads can be utilized for voltage regulation in distribution systems. However, the voltage regulation needs to calculate the nonlinear power flow; as a result, utilizing flexible resources for voltage regulation is a nonlinear scheduling problem requiring heavy computational resources. This study proposes an intelligent search algorithm called voltage ranking search algorithm (VRSA) to solve the optimization of flexible resource scheduling for voltage regulation. The VRSA is built based on the features of radial power distribution systems. A numeric... [more]
Impact of a Periodic Power Source on a RES Microgrid
Angelos Angelopoulos, Aphrodite Ktena, Christos Manasis, Stamatis Voliotis
February 22, 2023 (v1)
Subject: Optimization
Keywords: hill climbing optimization, load factor, photovoltaics, storage, tidal energy
The aim of this article is to highlight the impact of a periodic power source, such as a tidal turbine, on the operation and sizing of an autonomous hybrid microgrid with photovoltaic panels and storage. The technique of hill climbing (repeated local search) is used to find the optimum combination of Renewable Energy Sources (RES) and storage units with respect to the required capital cost for various load curves and weather conditions. To model the operation of the microgrid devices, analytical and phenomenological models, have been used, which take into account the specifications of actual commercial devices. Six different case studies are presented, with and without a tidal generator, which are based on six different sets of electrical consumption data corresponding to the Euripus campus of the National & Kapodistrian University of Athens (NKUA) in Psachna, Evia, Greece, and respective meteorological and tidal current data from the region. The results show that tidal energy may be u... [more]
A Modified Wireless Power Transfer System for Medical Implants
Yosra Ben Fadhel, Sana Ktata, Khaled Sedraoui, Salem Rahmani, Kamal Al-Haddad
February 22, 2023 (v1)
Subject: Optimization
Keywords: active implant, coil, DC/AC converter, form factor, power transfer efficiency, resonant inductive coupling, wireless power transfer
Wireless Power Transfer (WPT) is a promising technique, yet still an experimental solution, to replace batteries in existing implants and overcome the related health complications. However, not all techniques are adequate to meet the safety requirements of medical implants for patients. Ensuring a compromise between a small form factor and a high Power Transfer Efficiency (PTE) for transcutaneous applications still remains a challenge. In this work, we have used a resonant inductive coupling for WPT and a coil geometry optimization approach to address constraints related to maintaining a small form factor and the efficiency of power transfer. Thus, we propose a WPT system for medical implants operating at 13.56 MHz using high-efficiency Complementary Metal Oxide-Semiconductor (CMOS) components and an optimized Printed Circuit Coil (PCC). It is divided into two main circuits, a transmitter circuit located outside the human body and a receiver circuit implanted inside the body. The trans... [more]
Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation
Longda Wang, Xingcheng Wang, Kaiwei Liu, Zhao Sheng
February 22, 2023 (v1)
Subject: Optimization
Keywords: automatic train operation, comprehensive learning strategy, fusion distance, multi-objective hybrid optimization algorithm, Particle Swarm Optimization, whale optimization algorithm
Aiming at the problem of easy-to-fall-into local convergence for automatic train operation (ATO) velocity ideal trajectory profile optimization algorithms, an improved multi-objective hybrid optimization algorithm using a comprehensive learning strategy (ICLHOA) is proposed. Firstly, an improved particle swarm optimization algorithm which adopts multiple particle optimization models is proposed, to avoid the destruction of population diversity caused by single optimization model. Secondly, to avoid the problem of random and blind searching in iterative computation process, the chaotic mapping and the reverse learning mechanism are introduced into the improved whale optimization algorithm. Thirdly, the improved archive mechanism is used to store the non-dominated solutions in the optimization process, and fusion distance is used to maintain the diversity of elite set. Fourthly, a dual-population evolutionary mechanism using archive as an information communication medium is designed to e... [more]
A Dual-Objective Substation Energy Consumption Optimization Problem in Subway Systems
Hongjie Liu, Tao Tang, Jidong Lv, Ming Chai
February 22, 2023 (v1)
Subject: Optimization
Keywords: energy storage system, improved artificial bee colony, regenerative energy, timetable optimization, ϵ-constraint method
Maximizing regenerative energy utilization is an important way to reduce substation energy consumption in subway systems. Timetable optimization and energy storage systems are two main ways to improve improve regenerative energy utilization, but they were studied separately in the past. To further improve energy conservation while maintaining a low cost, this paper presents a strategy to improve regenerative energy utilization by an integration of them, which determines the capacity of each Wayside Energy Storage System (WESS) and correspondingly optimizes the timetable at the same time. We first propose a dual-objective optimization problem to simultaneously minimize substation energy consumption and the total cost of WESS. Then, a mathematical model is formulated with the decision variables as the configuration of WESS and timetable. Afterwards, we design an ϵ -constraint method to transform the dual-objective optimization problem into several single-objective optimization probl... [more]
The Voltage Control Strategy of a DC-Link Bus Integrated Photovoltaic Charging Module in a Unified Power Quality Conditioner
Fuyin Ni, Zhengming Li, Qi Wang
February 22, 2023 (v1)
Subject: Optimization
Keywords: chaos particle swarm optimization based on multi-agent system algorithm, current harmonics, micro-grid, power quality, unified power quality conditioner
In order to improve the functionality and efficiency of a unified power quality conditioner (UPQC), a DC-link bus integrated photovoltaic charging module is proposed in a UPQC. It can generate power for essential loads apart from providing energy to a DC-link bus. A conventional proportional integral (PI) controller fails to run smoothly in dynamic conditions of the micro-grid, since it has poor capabilities in determining suitable values of proportional gain and integral gain. So, the optimization algorithm for a PI controller based on chaos particle swarm optimization based on a multi-agent system (CPSO-MAS) algorithm was developed in this paper to overcome properties such as intermittent instability in the micro-grid. Through verification by simulation and experiment of UPQC harmonic compensation, it showed that the proposed DC link bus voltage control strategy can be effectively applied to UPQC towards various conditions related to voltage and current distortion. In addition, it pr... [more]
Design Optimization of a Permanent-Magnet Saturated-Core Fault-Current Limiter
John Linden, Yasha Nikulshin, Alex Friedman, Yosef Yeshurun, Shuki Wolfus
February 22, 2023 (v1)
Subject: Optimization
Keywords: Fault Current Limiters, permanent magnets, saturated core, variable inductance
Designs of saturated-cores fault current limiters (FCLs) usually implement conducting or superconducting DC coils serving to saturate the magnetic cores during nominal grid performance. The use of coils adds significantly to the operational cost of the system, consuming energy, and requiring maintenance. A derivative of the saturated-cores FCL is a design implementing permanent magnets as an alternative to the DC coils, eliminating practically all maintenance due to its entirely passive components. There are, however, various challenges such as the need to reach deep saturation with the currently available permanent magnets as well as the complications involved in the assembly process due to very powerful magnetic forces between the magnets and the cores. This paper presents several concepts, achieved by extensive magnetic simulations and verified experimentally, that help in maximizing the core saturation of the PMFCL (Permanent Magnet FCL), including optimization of the permanent mag... [more]
Gear Ratio Optimization of a Multi-Speed Transmission for Electric Dump Truck Operating on the Structure Route
Senqi Tan, Jue Yang, Xinxin Zhao, Tingting Hai, Wenming Zhang
February 22, 2023 (v1)
Subject: Optimization
Keywords: electric dump truck, Energy Efficiency, gear ratio optimization, performance analysis, structure route
Research demonstrated that the application of a multi-speed transmission could improve the dynamic and economic performance of electric vehicles. This paper deals with a novel multi-speed transmission for the electric dump truck (EDT) operating on the structure route (SR), which has a definite starting point and end point without complex traffic conditions. To optimize the gear ratio and shift schedule to reduce energy consumption in such conditions, the mathematical model of the transmission and the dynamic model of the EDT are initially required. Following this, the shift schedule is presented according to the motor efficiency map. After that, the gear ratio optimization is carried out by a particle swarm optimization (PSO) algorithm. Moreover, the proposed EDT is compared with an EDT with a single-speed transmission. The simulation results show that the energy consumption is reduced by 6.1%.
Smart Hybrid Micro-Grid Integration for Optimal Power Sharing-Based Water Cycle Optimization Technique
Peter Makeen, R. A. Swief, T. S. Abdel-Salam, Noha H. El-Amary
February 22, 2023 (v1)
Subject: Optimization
Keywords: coupled micro-grid, decision-making, Distributed Generators (DG), Genetic Algorithm (GA), islanded micro-grid, overloaded micro-grid, Water Cycle Optimization Technique (WCOT)
Micro-Grid (MG) with hybrid power resources can supply electric loads independently. In case of surplus power, the neighborhood micro-grids can be integrated together in order to supply the overloaded micro-grid. The challenge is to select the most suitable, optimal and preferable micro-grid within a distributed network, which consists of islanded MGs, to form that integration. This paper presents an intelligent decision-making criteria based on the Weighted Arithmetic Mean (WAM) of different technical indices, for optimal selection of micro-grids integration in case of overloaded event due to either unusual increase in consumed power or any deficiency in power generation. In addition, overloading is expected due to excess increase or decrease in weather temperature. This may lead to extreme increase of load due to increase of air conditioning or heating loads respectively. The proposed arithmetic mean determination based on six multi-objective indices, which are voltage deviation, fre... [more]
Electricity Purchase Optimization Decision Based on Data Mining and Bayesian Game
Yajing Gao, Xiaojie Zhou, Jiafeng Ren, Zheng Zhao, Fushen Xue
February 22, 2023 (v1)
Subject: Optimization
Keywords: Bayesian game, fuzzy clustering, load forecasting, power retailer, price forecasting
The openness of the electricity retail market results in the power retailers facing fierce competition in the market. This article aims to analyze the electricity purchase optimization decision-making of each power retailer with the background of the big data era. First, in order to guide the power retailer to make a purchase of electricity, this paper considers the users’ historical electricity consumption data and a comprehensive consideration of multiple factors, then uses the wavelet neural network (WNN) model based on “meteorological similarity day (MSD)„ to forecast the user load demand. Second, in order to guide the quotation of the power retailer, this paper considers the multiple factors affecting the electricity price to cluster the sample set, and establishes a Genetic algorithm- back propagation (GA-BP) neural network model based on fuzzy clustering (FC) to predict the short-term market clearing price (MCP). Thirdly, based on Sealed-bid Auction (SA) in game theory, a Bayesi... [more]
Optimization of Synthetic Inertial Response from Wind Power Plants
Müfit Altin, Jan Christian Kuhlmann, Kaushik Das, Anca Daniela Hansen
February 22, 2023 (v1)
Subject: Optimization
Keywords: Genetic Algorithm, heuristic optimization, synthetic inertial response, wind energy integration, wind power plants
In this paper the emphasis is on the optimization of synthetic inertial response of wind power plants (WPPs) for power systems with high wind power penetration levels, considering different wind speed operating conditions. The synthetic inertial response of wind power plants can play an important role in the resilience of future power systems with low inertia during large frequency disturbances. In order to investigate this role, a generic optimization methodology employing the genetic algorithm is proposed, taking into consideration the frequency nadir, second frequency dip, and time to reach the quasi⁻steady-state frequency. This optimization methodology comprehends the inertial response capability of WPPs and the frequency control dynamics of the power system. Accordingly, offline parameter tuning of synthetic inertial response is performed at the power system level with the proposed methodology. Based on the optimization results, the relevant aspects to be considered by transmissio... [more]
Optimal Design of an Axial-Flux Permanent-Magnet Motor for an Electric Vehicle Based on Driving Scenarios
Yee Pien Yang, Guan Yu Shih
February 22, 2023 (v1)
Subject: Optimization
Keywords: axial-flux permanent-magnet (AFPM) motor, driving scenario, electric vehicle, Optimization
This paper proposes a driving-scenario oriented optimal design of an axial-flux permanent-magnet (AFPM) motor for an electric vehicle. The target torque and speed (TN) curve is defined as three operation zones-constant torque, maximum direct current, and maximum voltage—based on the driving scenario. The AFPM motor is designed to minimize energy consumption based on the motor weight and the frequent operating points of a driving cycle. The final result shows that the electric vehicle driven by the proposed AFPM motor consumes about 15% less energy than motors designed using traditional methods.
Analysis and Optimization of Three-Resonator Wireless Power Transfer System for Predetermined-Goals Wireless Power Transmission
Jin Zhang, Chonghu Cheng
February 22, 2023 (v1)
Subject: Optimization
Keywords: frequency splitting phenomenon, predetermined-goals, three-resonator system, wireless power transfer (WPT)
Three-resonator wireless power transfer (WPT) systems have been proposed to improve the power transfer efficiency (PTE) and power delivered to the load (PDL) in recent years. However, analysis formulas of a three-resonator WPT system are complicated, and the parameters for clarifying the transfer characteristics of this system are difficult to extract. In this paper, concise formulas for analyzing PTE and PDL of the three-resonator system are derived by introducing three factors. Diagram discriminance based on the derived formulas is proposed to obtain the frequency splitting criterions of PTE and PDL in this system. Further, at the transfer distances, where the PTE and PDL are low at original frequency due to frequency splitting phenomenon, the two predetermined-goals of maximizing PTE and PDL are achieved by optimizing coupling strength between the three resonators. The third predetermined-goal of obtaining a constant amount of PDL transfer at maximum PTE is also implemented based on... [more]
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