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Application of memetic algorithm for selective harmonic elimination in multi-level inverters

IET POWER ELECTRONICS 2015年第9期8卷 1733-1739页

作者： Kumle, Alireza Niknam Fathi, Seyed Hamid Jabbarvaziri, Faramarz Jamshidi, Mehdi Yazdi, Seyed Saeed Heidari Amirkabir Univ Technol Dept Elect Engn Tehran 15916 Iran

Multi-level inverter (MLI) is a promising technology, able to generate high-quality power with lower switching frequency. Therefore it leads to high conversion efficiency and low switching losses. Selective harmonic elimination is a fundamental frequency switching strategy that theoretically provides desirable output waveform for MLIs by elimination of low order harmonics. Unfortunately, complexity, non-linearity and solvability features attached to this method have limited its industrial application. In this study, a particle swarm optimisation (PSO)-based memetic algorithm (MA) guided by mesh adaptive direct search is introduced as a suitable choice for the harmonic optimisation problem. This algorithm is precise and applicable to any MLI. The results show that MA converges to the exact solution for feasible modulation index. When the problem has no exact solution, the algorithm finds a relatively proper solution to regulate the fundamental component of the voltage. Furthermore, the comparison between MA and other methods shows that the probability of convergence of MA is higher than others. For 48% of the analysed data MA reaches to a fitness value lower than 10(-30) whereas this probability is 5% for PSO and almost zero for genetic algorithm and bee algorithm. The proposed method has been implemented on a cascade seven-level inverter.

关键词： invertors harmonics suppression particle swarm optimisation search problems genetic algorithms memetic algorithm selective harmonic elimination multilevel inverters MLI high-quality output power low switching losses high conversion efficiency fundamental frequency switching strategy low order harmonics minimisation particle swarm optimisation PSO-based MA mesh adaptive direct search harmonic optimisation problem modulation index evolutionary algorithms convergence probability genetic algorithm bee algorithm cascade seven-level inverter

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Prediction of water pollution sources using artificial neural networks in the study areas of Sivas, Karabuk and Bartin (Turkey)

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ENVIRONMENTAL EARTH SCIENCES 2015年第9期73卷 5333-5347页

作者： Keskin, Tulay Ekemen Dugenci, Muharrem Kacaroglu, Fikret Karabuk Univ Dept Environm Engn TR-78050 Karabuk Turkey Karabuk Univ Dept Ind Engn TR-78050 Karabuk Turkey Mugla Sitki KOCMAN Univ Dept Geol Engn TR-48000 Mugla Turkey

The determination of the rock types from which the water is recharged/discharged is an essential component of hydrochemical, hydrogeological and water pollution studies. Especially, detection of sources of groundwater contamination is very important in terms of human health and other living organism. This study aims at prediction of water pollution sources using artificial neural networks (ANNs) in Sivas, Karabuk and Bartin areas of Turkey, which have different types of rocks, agricultural activity and mining activity. In this study, a model based on ANNs was developed for forecast to the water discharging from different types of rocks and the water pollution sources in the study areas. Back propagation and bee algorithm (BA) were used in ANN training. For achieving the aim of the study, 14 hydrochemical data set were used. The best ANN classification of water discharging from different type of rocks was accomplished with 80 % accuracy using BA. These results indicate that the researches that are similar to this study can provide quite convenience for the assessment of groundwater pollution sources when applied on a large and regional scale.

关键词： Hydrogeochemistry Water contamination Artificial neural networks (ANNs) bee algorithm Turkey

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Hybrid Artificial Intelligence-Based PBA for Benchmark Functions and Facility Layout Design Optimization

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JOURNAL OF COMPUTING IN CIVIL ENGINEERING 2012年第5期26卷 612-624页

作者： Cheng, Min-Yuan Lien, Li-Chuan Natl Taiwan Univ Sci & Technol Dept Construct Engn Taipei 106 Taiwan

Facility layout design (FLD) presents a particularly interesting area of study because of its relatively high level of attention to aesthetics and usability qualities, in addition to common engineering objectives such as cost and performance. However, FLD present a difficult combinatorial optimization problem for engineers. Swarm intelligence (SI), an approach to decision making that integrates collective social behavior models such as the bee algorithm (BA) and particle swarm optimization, is being increasingly used to resolve various complex optimization problems. This study proposes a new optimization hybrid swarm algorithm, the particle bee algorithm (PBA), which imitates the intelligent swarming behavior of honeybees and birds. This study also proposes a neighborhood-windows (NW) technique for improving searching efficiency and a self-parameter-updating (SPU) technique for preventing trapping into a local optimum in high-dimensional problems. This study compares the performance of PBA with that of genetic algorithm (GA), differential evolution (DE), bee algorithm, and particle swarm optimization for multidimensional benchmark function problems. Additionally, this study compares PBA performance against bee algorithm and particle swarm optimization (PSO) performance in practical FLD problems. Results show that PBA performance is comparable to those of the mentioned algorithms in the benchmark functions and can be efficiently employed to solve practical FLD problem with high dimensionality. DOI: 10.1061/(ASCE)CP.1943-5487.0000163. (C) 2012 American Society of Civil Engineers.

关键词： Facility layout design Swarm intelligence bee algorithm Particle swarm optimization Particle bee algorithm Benchmark function

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Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm

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IET POWER ELECTRONICS 2018年第10期11卷 1673-1680页

作者： Memon, Mudasir Ahmed Mekhilef, Saad Mubin, Marizan Univ Malaya Dept Elect Engn Fac Engn Power Elect & Renewable Energy Res Lab PEARL Kuala Lumpur 50603 Malaysia

This study presents selective harmonic elimination pulse width modulation technique-based hybrid asynchronous PSO-Newton-Raphson (APSO-NR) algorithm for the elimination of undesired harmonics in cascaded H-bridge multilevel inverter. The proposed algorithm is applicable to all levels of MLI having equal and non-equal DC sources. In the proposed method, ring topology-based APSO algorithm is hybrid with NR method. APSO worked as a global search technique and NR is used for the refinement of best solutions. APSO-NR is applied to the seven-level inverter to eliminate fifth and seventh harmonics. In simulations, the performance of the proposed algorithm is compared with genetic algorithm, bee algorithm and particle swarm optimisation. The results proved that the proposed algorithm is efficient, and gives more precise firing angles in less number of iterations with high capability of tackling local optima. For the 48% of modulation index range, APSO-NR minimised the fitness function value lower than (10-25). The proposed algorithm is validated through the experimental implementation of the three-phase seven-level inverter.

关键词： genetic algorithms harmonics suppression Newton-Raphson method PWM invertors particle swarm optimisation minimisation evolutionary computation seventh harmonics genetic algorithm bee algorithm seven-level inverter hybrid APSO algorithm selective harmonic elimination pulse modulation technique hybrid asynchronous PSO-Newton-Raphson algorithm undesired harmonics cascaded H-bridge multilevel inverter nonequal DC sources NR method global search technique fifth harmonics APSO-NR algorithm particle swarm optimisation MLI

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Improvement of power utilisation capability for a three-phase seven-level CHB inverter using an improved selective harmonic elimination-PWM scheme by sharing a desired proportion of power among the H-bridge cells

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IET POWER ELECTRONICS 2019年第12期12卷 3242-3253页

作者： Kundu, Sourabh Bhowmick, Supratik Banerjee, Subrata Natl Inst Technol NIT Durgapur Dept Elect Engn Durgapur 713209 India

An improved selective harmonic elimination-pulse width modulation (SHE-PWM) scheme has been proposed for a three-phase seven-level cascaded H-bridge (CHB) inverter that enhances the power utilisation capability of the inverter by sharing the desired amount of power among the H-bridge cells and also eliminates both 5th- and 7th-order harmonic components from the inverter output voltage maintaining the desired fundamental voltage component for a wide range of modulation index. Compared to conventional SHE-PWM, this scheme introduces two additional switching in the first cell, while the second and the third cells are switched at advanced switching angles. The differential search algorithm (DSA) technique has been applied to solve the proposed SHE-PWM scheme, and it exhibited comparatively better performance than the algorithm based on genetic algorithm, bee algorithm and particle swarm optimisation. The effectiveness of the proposed scheme has been verified by both simulation and experimental study on a seven-level CHB inverter. Finally, the proposed scheme has been applied to the closed-loop constant V/f control of the induction motor drive application. It has been established that the proposed scheme is independent of the load power factor angle, and it improved the power conversion efficiency of the conventional SHE-PWM scheme.

关键词： PWM invertors genetic algorithms particle swarm optimisation switching convertors harmonics suppression closed loop systems power factor search problems power utilisation capability H-bridge cells 7th-order harmonic components inverter output voltage modulation index advanced switching angles optimal switching angles genetic algorithm bee algorithm seven-level CHB inverter load power factor angle transient condition smooth speed variation induction motor drive application closed-loop constant V-f control convergence rate global optimum solution particle swarm optimisation DSA technique differential search algorithm fundamental voltage component 5th-order harmonic components three-phase seven-level cascaded H-bridge inverter SHE-PWM scheme improved selective harmonic elimination-pulse width modulation scheme three-phase seven-level CHB inverter power conversion efficiency

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Wireless Capsule Endoscopy Video Reduction Based on Camera Motion Estimation

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JOURNAL OF DIGITAL IMAGING 2013年第2期26卷 287-301页

作者： Liu, Hong Pan, Ning Lu, Heng Song, Enmin Wang, Qian Hung, Chih-Cheng Huazhong Univ Sci & Technol Sch Comp Sci & Technol Ctr Biomed Imaging & Bioinformat Wuhan 430074 Hubei Peoples R China Educ Minist Image Proc & Intelligence Control Key Lab Wuhan 430074 Hubei Peoples R China Nanjing Mil Command Chinese PLA Nanjing Cent Hosp Dept Gastroenterol Nanjing 210002 Jiangsu Peoples R China Zhongnan Univ Econ & Law Sch Informat & Safety Engn Wuhan 430073 Hubei Peoples R China Southern Polytech State Univ Sch Comp & Software Engn Marietta GA 30060 USA

Wireless capsule endoscopy (WCE) is a novel technology aiming for investigating the diseases and abnormalities in small intestine. The major drawback of WCE examination is that it takes a long time to examine the whole WCE video. In this paper, we present a new reduction scheme for WCE video to reduce the examination time. To achieve this task, a WCE video motion model is proposed. Under this motion model, the WCE imaging motion is estimated in two stages (the coarse level and the fine level). In the coarse level, the WCE camera motion is estimated with a combination of bee algorithm and Mutual Information. In the fine level, the local gastrointestinal tract motion is estimated with SIFT flow. Based on the result of WCE imaging motion estimation, the reduction scheme preserves key images in WCE video with scene changes. From experimental results, we notice that the proposed motion model is suitable for the motion estimation in successive WCE images. Through the comparison with APRS and FCM-NMF scheme, our scheme can produce an acceptable reduction sequence for browsing and examination.

关键词： Wireless capsule endoscopy bee algorithm SIFT flow Motion estimation

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Two-stage charging strategy of plug-in electric vehicles based on fuzzy control

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COMPUTERS & OPERATIONS RESEARCH 2018年第Aug.期96卷 236-243页

作者： Bandpey, M. Fattahi Firouzjah, K. Gorgani Mazandaran Univ Sci & Technol Fac Engn & Technol Pasdaran St Bubol Iran Univ Mazandaran Fac Engn & Technol Pasdaran St Babol Sar Iran

This paper proposes a two-stage charging strategy for solving charging control issues of plug-in electric vehicle (PEV). At the first stage, the optimal charging of each PEV is calculated with bee algorithm (BA) as an aggregator optimizer. At the second stage, this aggregated power is then distributed among electrical vehicles (EVs) using fuzzy logic controller (FLC). This framework has considered non-linear dynamic feature of PEV batteries in various practical scenarios. Main advantageous of this method are reducing load peak, smoothing transformers load profile, consideration of non-linear dynamic behavior of PEV batteries and proper energy management of batteries in case of unscheduled unplugging of PEVs from charging stations. Finally, simulation results are presented to verify the analysis of the proposed charging control strategy. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Plug-in electric vehicle Charging strategy Fuzzy logic controller bee algorithm

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Comparison of Heuristic Approaches in Weight Optimization of Different Power Levels Transformers

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IETE JOURNAL OF RESEARCH 2023年第5期69卷 2266-2280页

作者： Toren, Murat Mollahasanoglu, Hakki Recep Tayyip Erdogan Univ Dept Elect & Elect Engn TR-53100 Rize Turkey

In this study, the weight of distribution type transformers and power transformers, which are used extensively in the industry, is optimized. A heuristic approach that uses the Firefly algorithm, Ant Colony algorithm, and the bee algorithm to determine the weight of transformers is described. Optimization of the iron weight components effective in the weight of a transformer to be produced in multi-type is provided. It is aimed to reduce the transformer cost, increase the life cycle of the transformer, and increase the efficiency by obtaining the optimum current density (s) and iron section (C) values which are the variable parameters used in the iron weight calculation of the transformer. In the study, it is determined that heuristic optimization algorithms, which provide more effective and efficient values than traditional approaches, give better results. These popular algorithms, in the weight parameters of 50 and 1000 kVA transformer powers, can obtain a lower weight value of 9.6% with the weight obtained by the bee algorithm, 7.4% by the Ant Colony algorithm and 11% by the firefly algorithm than the weight obtained through the classical method. According to the heuristic optimization results, it shown that optimum 50 and 1000 kVA transformer weights can be determined and less costly transformer designs can be made.

关键词： Ant colony algorithm bee algorithm firefly algorithm transformer weight optimization

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Energy Efficient Congestion Aware Resource Allocation and Routing Protocol for IoT Network using Hybrid Optimization Techniques

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WIRELESS PERSONAL COMMUNICATIONS 2021年第2期117卷 1187-1207页

作者： Praveen, K. V. Prathap, P. M. Joe St Peters Coll Engn & Technol Dept Informat Technol Avadi 600054 Tamil Nadu India RMD Engn Coll Dept IT Kavaraipettai 601206 Tamil Nadu India

The idea of Smart City incorporates a few ideas being technology, economy, governance, people, management, and infrastructure. This implies a Smart City can have distinctive communication needs. Wireless technologies, for example, WiFi, Zig bee, Bluetooth, WiMax, 4G or LTE have introduced themselves as a solution for the communication in Smart City activities. Nonetheless, as the majority of them utilize unlicensed interference, coexistence and bands issues are increasing. So to solve the problem IoT is used in smart cities. This paper addresses the issues of both resource allocation and routing to propose an energy efficient, congestion aware resource allocation and routing protocol (ECRR) for IoT network based on hybrid optimization techniques. The first contribution of proposed ECRR technique is to employ the data clustering and metaheuristic algorithm for allocate the large-scale devices and gateways of IoT to reduce the total congestion between them. The second contribution is to propose a queue based swarm optimization algorithm for select a better route for future route based on multiple constraints, which improves the route discovering mechanism. The proposed ECRR technique is implemented in Network Simulator (NS-2) tool and the simulation results are compared with the existing state-of-art techniques in terms of energy consumption, node lifetime, throughput, end-to-end delay, packet delivery ratio and packet overheads.

关键词： Internet of things Smart cities Ant algorithm bee algorithm

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Optimization of proton exchange membrane fuel cell's end plates

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SN APPLIED SCIENCES 2020年第8期2卷 1-8页

作者： Habibnia, Mostafa Shirkhani, Mohammadreza Tamami, Peyman Ghasemi Islamic Azad Univ Jouybar Branch Dept Mech Engn Jouybar Iran Islamic Azad Univ Sari Branch Dept Mech Engn Sari Iran Tarbiat Modares Univ Dept Mech Engn Tehran Iran

In this study, we present the optimization of end plates to produce uniform pressure and low content on the gas diffusion layer in polymer membrane fuel cell. For this purpose the end plates and the influence of parameters on the gas diffusion layer pressure has been investigated. Parameters studied are the thickness of the end plate, the depth of the bipolar plates groove and the clamping pressure applied to the end plates. After defining their values in the Abaqus finite element software, mechanical analysis has been carried out to examine the stress distribution on the gas diffusion layer and the results have been extracted. By extracting the results of the analysis and importing into the Adaptive Network-based Fuzzy Inference Systems in MATLAB software, a numerical relationship between the influential values and the outputs is extracted. By investigating these relationships and defining the objective function, we investigate the algorithm required for the equation and uniformity of stress distribution on the gas diffusion layer. In this research, the bee algorithm has been used and it has been evaluating the effective parameters of the optimum fuel cell state. After final review of the results, the suggested optimum state of the bee algorithm is the thickness of the end plate 12 mm, the depth of the bipolar plate groove is 0.1077 mm and the clamping pressure is 11.0199 MPa.

关键词： PEM fuel cell End plate Optimization bee algorithm

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