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A modeling method for photovoltaic cells using explicit equations and optimization algorithm

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 59卷 23-28页

作者： Xu, Yonghai Kong, Xiangyu Zeng, Yawen Tao, Shun Xiao, Xiangning North China Power Elect Univ Dept Elect & Elect Engn State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China

A numerical method for determining the five-parameter model of photovoltaic cells is presented in the paper. Explicit equations are applied to analyze the relations between parameters which are solved by an optimization algorithm. Lambert W function is implemented to convert the I-V characteristic implicit equation to an explicit one, so the output current and voltage of photovoltaic cells can be obtained by substituting the five parameters into the explicit I-V equation. Several cells are used to verify the accuracy of the proposed method from different aspects. It is found that the proposed method gives precise results and can be applicable to various types of photovoltaic cells. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Photovoltaic cells Five-parameter model Explicit equation optimization algorithm Lambert W function

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An outward search to increase population diversity for optimization algorithms

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APPLIED SOFT COMPUTING 2022年第0期129卷

作者： Tsai, Hsing-Chih Natl Univ Kaohsiung Dept Civil & Environm Engn Kaohsiung Taiwan Natl Univ Kaohsiung Dept Civil & Environm Engn 700Kaohsiung Univ Rd Kaohsiung 81148 Taiwan

Outward search (OS) is a new scheme proposed to provide diverse forms for improving convergence in evolutionary algorithms. Rather than using new functionalities, OS is performed using the differential -vector equations of an evolutionary algorithm. Three OS schemes are recommended in this study to obtain solutions that improve the performance of an evolutionary algorithm. The first one uses the original equations of the algorithm to generate either an OS solution or a candidate solution. The second utilizes the original equations to produce an OS solution and a candidate solution simultaneously for one individual. The last employs equations of another algorithm to create an OS solution for the studied algorithm. Three bio-inspired algorithms were examined using the CEC2015 benchmark suite to compare the respective performances of the proposed OS schemes. The results of the comparison indicate that searching regions outward from the current area outperformed examining oppositional locations obtained by opposition-based learning. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Outward search Search region optimization algorithm CEC2015

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Best battery storage technologies of solar photovoltaic systems for desalination plant using the results of multi optimization algorithms and sustainable development goals

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JOURNAL OF ENERGY STORAGE 2022年 55卷

作者： Salameh, Tareq Kumar, Polamarasetty P. Olabi, A. G. Obaideen, Khaled Sayed, Enas Taha Maghrabie, Hussein M. Abdelkareem, Mohammad Ali Univ Sharjah Dept Sustainable & Renewable Energy Engn Sharjah 27272 U Arab Emirates Univ Sharjah Sustainable Energy & Power Syst Res Ctr Sharjah 27272 U Arab Emirates GMR Inst Technol Dept Elect Engn Razam Andhra Pradesh India Univ Sharjah Ctr Adv Mat Res Sharjah 27272 U Arab Emirates Minia Univ Chem Engn Dept Elminia Egypt South Valley Univ Fac Engn Dept Mech Engn Qena 83521 Egypt

In this paper, the optimization and multiple-criteria decision analysis (MCDA) of a stand-alone photovoltaic and battery energy system (PV-BES) has been used to supply power to a desalination plant in the United Arab Emirates (UAE). To provide a continuous power supply, different types of battery technologies have been used as a renewable energy storage system in this study as Nickel Iron (Ni-Fe), Lithium Iron Phosphate (LiFePO4), and Lead Acid (PbSO4) with three different depths of discharges. Six different configurations of the PV-BES were modeled. In total, nine metaheuristic optimization algorithms were used in the MATLAB environment to provide an optimal sizing of the PV-BES. The mayfly optimization algorithm has provided the best optimal Annual Levelized Cost (ALC) values compared with the remaining algorithms. The mayfly algorithm has more robustness and faster convergence in providing the optimal global best values. Furthermore, three different approaches of MCDA and weights methods were used. The inputs and the results for the optimization process in addition to the sustainable development goal (SDGs) from the united nation (UN) were used as criteria for MCDA. The PV-Li-ION at 50 % depth of discharge (DOD) was the best option among all cases based on the six configurations and nine optimization algorithms.

关键词： Microgrid PV-BES Batteries technology optimization algorithm Reverse osmosis SDGs Energy storage

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An Intelligent optimization Method of Reinforcing Bar Cutting for Construction Site

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 637-655页

作者： Zhaoxi Ma Qin Zhao Tianyou Cang Zongjian Li Yiyun Zhu Xinhong Hei Department of Civil Engineering and Architecture Xi’an University of TechnologyXi’an710048China State Key Laboratory of Rail Transit Engineering Informatization(FSDI) Xi’an710043China Department of Computer Science and Engineering Xi’an University of TechnologyXi’an710048China

To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable *** one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction *** cutting waste increases construction costs and generates a considerable amount of CO_(2)*** study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable *** the proposed algorithm,the integer linear programming algorithm was applied to solve the *** was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data *** proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction *** the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation *** the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.

关键词： Building construction rebar work cutting stock problem optimization algorithm integer linear programming

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Distributed neurodynamic optimization for multi-energy management with time-varying external disturbances considering time-varying emission limitations and load demand in multi-microgrid

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ISA TRANSACTIONS 2023年第1期139卷 337-356页

作者： Li, Wenwen Wang, Hui He, Xing Southwest Univ Sch Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China Chongqing Normal Univ Sch Math Sci Chongqing 401331 Peoples R China

An emerging time-varying distributed multi-energy management problem (MEMP) considering time-varying load and emission limitations for resisting time-varying external disturbances and communication time delays in the multi-microgrid (MMG) system is investigated. Each microgrid (MG) contains some smaller microgrids (SMGs), which are connected by energy routers (ERs) of the system and can monitor energy in real-time with each other. In addition, a time-varying multi-energy management optimization model (MEMOM) is proposed in this paper in order to minimize the total cost of the MEMP which considers environmental cost, renewable energy cost and fuel cost. Furthermore, time-varying distributed neurodynamic optimization algorithms are proposed for solving the above MEMP based on consensus theory and sliding mode control technique. Compared with the optimization algorithms which consist of symbolic functions proposed in traditional energy management problems, algorithms consisting of hyperbolic tangent functions proposed in this paper can effectively reduce the oscillation of the algorithms and improve the stability of algorithms. Furthermore, the algorithm can converge the optimal trajectory of optimization problems with time-varying external disturbances and communication time delays. Meanwhile, the stability and convergence of the algorithms are proved theoretically by constructing appropriate Lyapunov functions. Finally, the performance evaluation re-sults of numerical simulations show that the proposed algorithms can efficiently handle energy trading under time-varying load and maintain excellent stability with time-varying external disturbances and communication time delays.(c) 2023 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Multi-energy management Multi-microgrid Time-varying external disturbances Communication time delays Time-varying distributed neurodynamic optimization algorithm Time-varying emission limitations

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Uncertainty optimization Based Feature Selection Model for Stock Marketing

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COMPUTATIONAL ECONOMICS 2024年第1期63卷 357-389页

作者： Sinha, Arvind Kumar Shende, Pradeep Natl Inst Technol Dept Math Raipur Chhattisgarh India

Market analyzers use different parameters as features in the market data to analyze the market trends. The feature's values act as a signal to market fluctuations. Many studies have examined these features to predict market movement more effectively. However, the method to minimize the uncertainties associated with the features is not available in the literature. This exploratory study introduces the uncertainty optimization based feature selection method for stock marketing. We introduce a notion of certainty region of the feature as the set of feature values, which signify particular happening with certainty. We use rough set theory to find the feature's certainty region and uncertainty region and measure each feature's significance. The feature whose certainty region is the maximum is the most significant in the feature space. Hence we group the features by minimizing the uncertainty region of the most informative features to get feature subsets for feature selection. We propose an algorithm based on uncertainty optimization to find subsets of the feature set for effectiveness and performance enhancement in the feature selection. We obtain the decision rules with comprehensive coverage and excellent support using the selected features. The accuracy of classification using the chosen parameters is up to 85.91%, which is higher than 79.54% of the complete feature set. The study provides an uncertainty optimization model for more efficient market movement prediction.

关键词： Stock market Uncertainty optimization Rough set Feature selection optimization algorithm

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Analytic Gradient Computation and Applications in Multitarget Multi-Impulse Trajectory optimization

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2024年第2期47卷 347-357页

作者： Zhang, Nan Di, Wu Baoyin, Hexi Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China

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Genetic optimization algorithms for Supersonic Heat Addition

Genetic Optimization Algorithms for Supersonic Heat Addition

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Villa, Louis Purdue Univ Aeronaut & Astronaut 2038 Puget Dr W Lafayette IN 47906 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

As technologies continue to be developed to enable the private and commercial use of super and hypersonic aerospace systems, one of the many issues that must be addressed is the optimization of supersonic flow paths that involve both area change and heat addition, such as those present in scramjets. The ever-expanding capability of computers to solve complex optimization problems can help decrease the development cost of propulsion systems by removing guesswork involved in early experimental design. This paper works to develop a novel approach for numerically computing flow properties along an arbitrary flow path with both area change and heat addition. Using the numerical approach as a performance metric, this paper will go on to implement a genetic algorithm that finds the optimal geometry and fuel addition profiles to maximize the thrust a propulsion device can generate. This tool is designed both for use as a computational rapid prototyping to inform early design choices for supersonic propulsion systems as well as a baseline metric for the performance of later iterations of design refinement, such as computational fluid dynamics models and experimental results. The presented approach is unique in the minimalistic nature of the code implementation and the lack of previous knowledge required of the solution space.

关键词： optimization algorithm Axially Symmetric Flow Propulsion System Genetic algorithm Computational Fluid Dynamics Cloud Computing Scramjet Aerospace System Rapid Prototyping Mach Number

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Examination and Evaluation of High-Efficiency Motor Drive Using Motors for Electric Vehicle Equipped with optimization algorithms 12

Examination and Evaluation of High-Efficiency Motor Drive Us...

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12th IEEE Energy Conversion Congress and Exposition-Asia (ECCE-Asia)

作者： Kawamura, Suguru Wakasa, Yuta Miino, Yuu Takagi, Shigeyuki Tokyo Univ Technol Sch Engn Hachioji Tokyo Japan

ISBN: (纸本)9781728163444

We have proposed a novel control method that in which proportional-integral (PI) control and optimized control are combined to stabilize permanent-magnet synchronous motors (PMSMs) for electric vehicles (EVs). The inverter current, which maximizes the torque and minimizes power, is calculated by the optimized control method. The simulations and experiments were performed to verify the effectiveness of the control. The experiment was carried out using the RX62T micromputer, which is an IC for automobile control, and a digital control system (PE-Expert4). Compared with the conventional speed PI control, the optimized control suppresses the decrease in motor speed and shortens the recovery time. As a result, we confirmed that the responsiveness was improved by 3 3 %. From this result, the optimized control method. which simultaneously controls and monitor speed, was shown to be effective in solving the problems of the conventional method.

关键词： optimization algorithm permanent magnetic synchronous motor RX621 microcomputer hill-climbing method

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Buckling and Fundamental Frequency optimization of Tow-Steered Composites Using Layerwise Structural Models

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AIAA JOURNAL 2023年第9期61卷 4149-4163页

作者： Sanchez-Majano, Alberto Racionero Pagani, Alfonso Polytech Univ Turin Dept Mech & Aerosp Engn I-10129 Turin Italy

Variable-angle-tow (VAT) composite laminates can eventually improve the mechanical performance of lightweight structures by taking advantage of a larger design space compared to straight-fiber counterparts. Here, we provide a scalable low- to high-fidelity methodology to retrieve the tow angles that maximize the buckling load and the fundamental frequency of VAT plates. A genetic algorithm is used to solve the optimization problem in which the objective function is mimicked using a surrogate model. Both unconstrained and manufactured-constrained problems are solved. The surrogates are built with outcomes from numerical models generated by means of the Carrera unified formulation, which enables to obtain straightforwardly different degrees of accuracy by selecting the order of the structural theory employed. The results show both the validity and flexibility of the proposed design approach. It is shown that, although the optimal design fiber angle orientations are consistently similar, discrepancies in the prediction of the buckling load or fundamental frequency can be found between high-fidelity layerwise and low-to-refined equivalent-single-layer models, of which classical laminated plate or first-shear deformation theories are degenerate examples.

关键词： Buckling Analysis Structural Modeling and Simulation Fiber Volume Fraction Genetic algorithm Finite Element Method optimization algorithm Mechanical and Structural Vibrations Composite Structures Variable Stiffness Composites Variable-angle Tow

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