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Enhancement of grid-connected photovoltaic system using ANFIS-GA under different circumstances

Saeed VAFAEI,Alireza REZVANI,Majid GANDOMKAR,Maziar IZADBAKHSH

《能源前沿（英文）》 2015年 第9卷 第3期   页码 322-334 doi: 10.1007/s11708-015-0362-x

摘要： In recent years, many different techniques are applied in order to draw maximum power from photovoltaic (PV) modules for changing solar irradiance and temperature conditions. Generally, the output power generation of the PV system depends on the intermittent solar insolation, cell temperature, efficiency of the PV panel and its output voltage level. Consequently, it is essential to track the generated power of the PV system and utilize the collected solar energy optimally. The aim of this paper is to simulate and control a grid-connected PV source by using an adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA) controller. The data are optimized by GA and then, these optimum values are used in network training. The simulation results indicate that the ANFIS-GA controller can meet the need of load easily with less fluctuation around the maximum power point (MPP) and can increase the convergence speed to achieve the MPP rather than the conventional method. Moreover, to control both line voltage and current, a grid side P/Q controller has been applied. A dynamic modeling, control and simulation study of the PV system is performed with the Matlab/Simulink program.

关键词： photovoltaic system     maximum power point (MPP)     adaptive neuro-fuzzy inference system (ANFIS)     genetic algorithm (GA)    

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approach for improvement and optimization of karanja biodiesel using response surface methodology and geneticalgorithm

Sunil DHINGRA, Gian BHUSHAN, Kashyap Kumar DUBEY

《能源前沿（英文）》 2013年 第7卷 第4期   页码 495-505 doi: 10.1007/s11708-013-0267-5

摘要： This paper described the production of karanja biodiesel using response surface methodology (RSM) and genetic algorithm (GA). The optimum combination of reaction variables were analyzed for maximizing the biodiesel yield. The yield obtained by the RSM was 65% whereas the predicted value was 70%. The mathematical regression model proposed from the RSM was coupled with the GA. By using this technique, 90% of the yield was obtained at a molar ratio of 38, a reaction time of 8 hours, a reaction temperature of 40 oC, a catalyst concentration of 2% oil, and a mixing speed of 707 r/min. The yield produced was closer to the predicted value of 94.2093%. Hence, 25% of the improvement in the biodiesel yield was reported. Moreover the different properties of karanja biodiesel were found closer to the American Society for Testing & Materials (ASTM) standard of biodiesel.

关键词： optimization of karanja biodiesel     genetic algorithm (GA)     response surface methodology (RSM)     percentage improvement in the biodiesel yield     properties of biodiesel    

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Practical optimization of deployable and scissor-like structures using a fast GA method

M. SALAR, M. R. GHASEMI, B. DIZANGIAN

《结构与土木工程前沿（英文）》 2019年 第13卷 第3期   页码 557-568 doi: 10.1007/s11709-018-0497-z

摘要： This paper addresses practical sizing optimization of deployable and scissor-like structures from a new point of view. These structures have been recently highly regarded for beauty, lightweight, determine behavior, proper performance against lateral loads and the ability of been compactly packaged. At this time, there is a few studies done considering practical optimization of these structures. Loading considered here includes wind and gravity loads. In foldable scissor-like structures, connections have a complex behavior. For this reason, in this study, the authors used the ABAQUS commercial package as an analyzer in the optimization procedure. This made the obtained optimal solutions highly reliable from the point of view of applicability and construction requirements. Also, to do optimization task, a fast genetic algorithm method, which has been recently introduced by authors, was utilized. Optimization results show that despite less weight for aluminum models than steel models, aluminum deployable structures are not affordable because they need more material than steel structures and cause more environmental damage.

关键词： optimization     scissor-like structures     deployable structures     genetic algorithm     ABAQUS    

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Optimization of cold-end system of thermal power plants based on entropy generation minimization

《能源前沿（英文）》 2022年 第16卷 第6期   页码 956-972 doi: 10.1007/s11708-021-0785-5

摘要： Cold-end systems are heat sinks of thermal power cycles, which have an essential effect on the overall performance of thermal power plants. To enhance the efficiency of thermal power plants, multi-pressure condensers have been applied in some large-capacity thermal power plants. However, little attention has been paid to the optimization of the cold-end system with multi-pressure condensers which have multiple parameters to be identified. Therefore, the design optimization methods of cold-end systems with single- and multi-pressure condensers are developed based on the entropy generation rate, and the genetic algorithm (GA) is used to optimize multiple parameters. Multiple parameters, including heat transfer area of multi-pressure condensers, steam distribution in condensers, and cooling water mass flow rate, are optimized while considering detailed entropy generation rate of the cold-end systems. The results show that the entropy generation rate of the multi-pressure cold-end system is less than that of the single-pressure cold-end system when the total condenser area is constant. Moreover, the economic performance can be improved with the adoption of the multi-pressure cold-end system. When compared with the single-pressure cold-end system, the excess revenues gained by using dual- and quadruple-pressure cold-end systems are 575 and 580 k$/a, respectively.

关键词： cold-end system     entropy generation minimization     optimization     economic analysis     genetic algorithm (GA)    

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基于GA-ANN的震灾风险预测模型研究

刘明广,郭章林

《中国工程科学》 2006年 第8卷 第3期   页码 83-86

摘要：

对震灾的各种主要风险因素进行系统的辨识和分析，并建立了震灾风险预测的遗传神经网络模型，用实例证明了该模型的可行性与有效性，为决策部门提供一种有效的震灾风险预测方法。

关键词： 地震灾害     风险因素     人工神经网络     遗传算法     预测    

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Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 863-889 doi: 10.1007/s11709-019-0523-9

摘要： This study concerns with the design optimization of steel skeletal structures thereby utilizing both a real-life specification provisions and ready steel profiles named hot-rolled I sections. For this purpose, the enhanced genetic algorithm methodology named EGAwMP is utilized as an optimization tool. The evolutionary search mechanism of EGAwMP is constituted on the basis of generational genetic algorithm (GGA). The exploration capacity of EGAwMP is improved in a way of dividing an entire population into sub-populations and using of a radial basis neural network for dynamically adjustment of EGAwMP’s genetic operator parameters. In order to improve the exploitation capability of EGAwMP, the proposed neural network implementation is also utilized for prediction of more accurate design variables associating with a new design strategy, design codes of which are based on the provisions of LRFD_AISC V3 specification. EGAwMP is applied to determine the real-life ready steel profiles for the optimal design of skeletal structures with 105, 200, 444, and 942 members. EGAwMP accomplishes to increase the quality degrees of optimum designations Furthermore, the importance of using the real-life steel profiles and design codes is also demonstrated. Consequently, EGAwMP is suggested as a design optimization tool for the real-life steel skeletal structures.

关键词： design optimization     genetic algorithm     multiple populations     neural network    

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退火-遗传算法寻优及其实现

王英

《中国工程科学》 2008年 第10卷 第7期   页码 57-59

摘要：

分析了遗传算法及退火算法的优缺点，提出用退火算法改进遗传算法局部的最优值搜索效率低问题。退火算法与遗传算法融合后，使算法在寻优结果上更加迅速精确。通过水泥的配比工程实例，与单纯的遗传算法的结果进行对比，说明该方法是有效的。

关键词： 遗传算法     退火算法     遗传算法改进    

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Optimal design of steel portal frames based on genetic algorithms

CHEN Yue, HU Kai

《结构与土木工程前沿（英文）》 2008年 第2卷 第4期   页码 318-322 doi: 10.1007/s11709-008-0055-1

摘要： As for the optimal design of steel portal frames, due to both the complexity of cross selections of beams and columns and the discreteness of design variables, it is difficult to obtain satisfactory results by traditional optimization. Based on a set of constraints of the Technical Specification for Light-weighted Steel Portal Frames of China, a genetic algorithm (GA) optimization program for portal frames, written in MATLAB code, was proposed in this paper. The graph user interface (GUI) is also developed for this optimal program, so that it can be used much more conveniently. Finally, some examples illustrate the effectiveness and efficiency of the genetic-algorithm-based optimal program.

关键词： satisfactory     genetic-algorithm-based     Technical Specification     algorithm     efficiency    

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安全性第一准则下的组合贷款模型

唐万生,严维真,宁玉富

《中国工程科学》 2007年 第9卷 第11期   页码 137-141

摘要：

提出了一种在概率准则意义下的组合贷款模型，并设计了基于随机模拟的混合优化算法进行求解。 该算法突破了各种贷款收益率必须服从正态分布的假定，可对贷款收益率是任意分布形式的模型进行求解。 经数值仿真，验证了算法的可行性。

关键词： 组合贷款     安全性第一准则     随机模拟     遗传算法     同步扰动随机逼近    

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A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

《能源前沿（英文）》 2020年 第14卷 第1期   页码 139-151 doi: 10.1007/s11708-017-0484-4

摘要： In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.

关键词： PV-wind-battery hybrid system     size optimization     genetic algorithm    

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Hybrid genetic algorithm for bi-objective resource-constrained project scheduling

Fikri KUCUKSAYACIGIL, Gündüz ULUSOY

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 426-446 doi: 10.1007/s42524-020-0100-x

摘要： In this study, we considered a bi-objective, multi-project, multi-mode resource-constrained project scheduling problem. We adopted three objective pairs as combinations of the net present value (NPV) as a financial performance measure with one of the time-based performance measures, namely, makespan ( ), mean completion time (MCT), and mean flow time (MFT) (i.e., min /max , min /max , and min /max ). We developed a hybrid non-dominated sorting genetic algorithm II (hybrid-NSGA-II) as a solution method by introducing a backward–forward pass (BFP) procedure and an injection procedure into NSGA-II. The BFP was proposed for new population generation and post-processing. Then, an injection procedure was introduced to increase diversity. The BFP and injection procedures led to improved objective functional values. The injection procedure generated a significantly high number of non-dominated solutions, thereby resulting in great diversity. An extensive computational study was performed. Results showed that hybrid-NSGA-II surpassed NSGA-II in terms of the performance metrics hypervolume, maximum spread, and the number of non-dominated solutions. Solutions were obtained for the objective pairs using hybrid-NSGA-II and three different test problem sets with specific properties. Further analysis was performed by employing cash balance, which was another financial performance measure of practical importance. Several managerial insights and extensions for further research were presented.

关键词： backward–forward scheduling     hybrid bi-objective genetic algorithm     injection procedure     maximum cash balance     multi-objective multi-project multi-mode resource-constrained project scheduling problem    

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Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and

Mohammad Sadegh ES-HAGHI, Aydin SHISHEGARAN, Timon RABCZUK

《结构与土木工程前沿（英文）》 2020年 第14卷 第5期   页码 1110-1130 doi: 10.1007/s11709-020-0643-2

摘要： We propose a new algorithm, named Asymmetric Genetic Algorithm (AGA), for solving optimization problems of steel frames. The AGA consists of a developed penalty function, which helps to find the best generation of the population. The objective function is to minimize the weight of the whole steel structure under the constraint of ultimate loads defined for structural steel buildings by the American Institute of Steel Construction (AISC). Design variables are the cross-sectional areas of elements (beams and columns) that are selected from the sets of side-flange shape steel sections provided by the AISC. The finite element method (FEM) is utilized for analyzing the behavior of steel frames. A 15-storey three-bay steel planar frame is optimized by AGA in this study, which was previously optimized by algorithms such as Particle Swarm Optimization (PSO), Particle Swarm Optimizer with Passive Congregation (PSOPC), Particle Swarm Ant Colony Optimization (HPSACO), Imperialist Competitive Algorithm (ICA), and Charged System Search (CSS). The results of AGA such as total weight of the structure and number of analyses are compared with the results of these algorithms. AGA performs better in comparison to these algorithms with respect to total weight and number of analyses. In addition, five numerical examples are optimized by AGA, Genetic Algorithm (GA), and optimization modules of SAP2000, and the results of them are compared. The results show that AGA can decrease the time of analyses, the number of analyses, and the total weight of the structure. AGA decreases the total weight of regular and irregular steel frame about 11.1% and 26.4% in comparing with the optimized results of SAP2000, respectively.

关键词： optimization     steel frame     Asymmetric Genetic Algorithm     constraints of ultimate load     constraints of serviceability limits     penalty function    

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Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion

HUANG Haozhong, SU Wanhua

《能源前沿（英文）》 2008年 第2卷 第1期   页码 86-92 doi: 10.1007/s11708-008-0003-8

摘要： The micro-genetic algorithm (?GA) as a highly effective optimization method, is applied to calibrate to a newly developed reduced chemical kinetic model (40 species and 62 reactions) for the homogeneous charge compression ignition (HCCI) combustion of -heptane to improve its autoignition predictions for different engine operating conditions. The seven kinetic parameters of the calibrated model are determined using a combination of the Micro-Genetic Algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results show that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model over the range of equivalence ratios from 0.1–1.3 and temperature from 300–3 000 K. The results of this study have demonstrated that the mGA is an effective tool to facilitate the calibration of a large number of kinetic parameters in a reduced kinetic model.

关键词： homogeneous     different     combustion     autoignition     compression    

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Improved genetic algorithm and its application to determination of critical slip surface with arbitrary

LI Liang, CHI Shichun, LIN Gao, CHENG Yungming

《结构与土木工程前沿（英文）》 2008年 第2卷 第2期   页码 145-150 doi: 10.1007/s11709-008-0016-8

摘要： In order to overcome the problem of being trapped by the local minima encountered in applying the simple genetic algorithm (GA) to search the critical slip surface of the slope, an improved procedure based on the harmony search algorithm is proposed. In the searching computation, the new solutions are obtained from the whole information of the current generation. The proposed method may be applied to calculate the minimum factors of safety of two complicated soil slopes. Comparison of the results with existing examples given by other authors has shown that the proposed method is feasible for stability analysis of soil slopes.

关键词： information     algorithm     Comparison     generation     feasible    

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Multi-objective optimal design of braced frames using hybrid genetic and ant colony optimization

Mehdi BABAEI,Ebrahim SANAEI

《结构与土木工程前沿（英文）》 2016年 第10卷 第4期   页码 472-480 doi: 10.1007/s11709-016-0368-4

摘要： In this article, multi-objective optimization of braced frames is investigated using a novel hybrid algorithm. Initially, the applied evolutionary algorithms, ant colony optimization (ACO) and genetic algorithm (GA) are reviewed, followed by developing the hybrid method. A dynamic hybridization of GA and ACO is proposed as a novel hybrid method which does not appear in the literature for optimal design of steel braced frames. Not only the cross section of the beams, columns and braces are considered to be the design variables, but also the topologies of the braces are taken into account as additional design variables. The hybrid algorithm explores the whole design space for optimum solutions. Weight and maximum displacement of the structure are employed as the objective functions for multi-objective optimal design. Subsequently, using the weighted sum method (WSM), the two objective problem are converted to a single objective optimization problem and the proposed hybrid genetic ant colony algorithm (HGAC) is developed for optimal design. Assuming different combination for weight coefficients, a trade-off between the two objectives are obtained in the numerical example section. To make the final decision easier for designers, related constraint is applied to obtain practical topologies. The achieved results show the capability of HGAC to find optimal topologies and sections for the elements.

关键词： multi-objective     hybrid algorithm     ant colony     genetic algorithm     displacement     weighted sum method     steel braced frames    

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标题 作者 时间 类型 操作

Enhancement of grid-connected photovoltaic system using ANFIS-GA under different circumstances

Saeed VAFAEI,Alireza REZVANI,Majid GANDOMKAR,Maziar IZADBAKHSH

期刊论文

approach for improvement and optimization of karanja biodiesel using response surface methodology and geneticalgorithm

Sunil DHINGRA, Gian BHUSHAN, Kashyap Kumar DUBEY

期刊论文

Practical optimization of deployable and scissor-like structures using a fast GA method

M. SALAR, M. R. GHASEMI, B. DIZANGIAN

期刊论文

Optimization of cold-end system of thermal power plants based on entropy generation minimization

期刊论文

基于GA-ANN的震灾风险预测模型研究

刘明广,郭章林

期刊论文

Optimal design of steel skeletal structures using the enhanced genetic algorithm methodology

Tugrul TALASLIOGLU

期刊论文

退火-遗传算法寻优及其实现

王英

期刊论文

Optimal design of steel portal frames based on genetic algorithms

CHEN Yue, HU Kai

期刊论文

安全性第一准则下的组合贷款模型

唐万生,严维真,宁玉富

期刊论文

A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

期刊论文

Hybrid genetic algorithm for bi-objective resource-constrained project scheduling

Fikri KUCUKSAYACIGIL, Gündüz ULUSOY

期刊论文

Evaluation of a novel Asymmetric Genetic Algorithm to optimize the structural design of 3D regular and

Mohammad Sadegh ES-HAGHI, Aydin SHISHEGARAN, Timon RABCZUK

期刊论文

Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion

HUANG Haozhong, SU Wanhua

期刊论文

Improved genetic algorithm and its application to determination of critical slip surface with arbitrary

LI Liang, CHI Shichun, LIN Gao, CHENG Yungming

期刊论文

Multi-objective optimal design of braced frames using hybrid genetic and ant colony optimization

Mehdi BABAEI,Ebrahim SANAEI

期刊论文