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Power Losses Optimization of MMCs Based on quantum genetic algorithm for HVdc Transmission Application

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年第4期72卷 1902-1915页

作者： Zhao, Jifeng Xu, Peidong Wu, Xinyue Pei, Jia Fu, Hong Li, Yutan Jiangsu Vocat Inst Architectural Technol Sch Intelligent Mfg Xuzhou 221116 Peoples R China Anhui Univ Sch Elect Engn & Automat Hefei 230601 Peoples R China Xinjiang Career Tech Coll Kuitun 833200 Peoples R China

Modular multilevel converters (MMCs) obtain widespread utilization in high-voltage direct current (HVdc) applications scenarios. The cost of power losses plays a significant part in MMC's operating costs. Hence, this article proposes a quantum genetic algorithm-based power losses optimization control (QGA-PLOC). By comprehensively considering the power losses of the MMC, the quantum genetic algorithm determines the first-best value of the injected second circulating current magnitude and phase angle in the arm, as well as the optimal MMC power losses under given conditions. The quantum genetic algorithm incorporates the quantum state vector representation into genetic encoding and utilizes quantum logic gates for chromosome evolution, greatly improving the algorithm's performance and significantly enhancing its computational efficiency and global optimization capability. Moreover, introducing the quantum genetic algorithm into the field of MMC power losses optimization offers a new path to address the acquisition of the optimal circulating current reference value in power loss optimization problems. MMC Simulation and experiment are also conducted, and the research results verify the effectiveness of the proposed QGA-PLOC for MMCs.

关键词： Operating costs modular multilevel converter quantum genetic algorithm quantum genetic algorithm circulation current injection circulation current injection power losses optimization power losses optimization power losses optimization

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quantum genetic algorithm for dynamic economic dispatch with valve-point effects and including wind power system

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2011年第2期33卷 189-197页

作者： Lee, Jia-Chu Lin, Whei-Min Liao, Gwo-Ching Tsao, Ta-Peng Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung Taiwan Natl Taipei Univ Technol Dept Elect Engn Taipei Taiwan

An optimization algorithm is proposed in this paper to solve the problem of the economic dispatch that includes wind power generation using quantum genetic algorithm (QGA). In additional to the detail introduction for models of general economic dispatch as well as their associated constraints, the effect of wind power generation is also included in this paper. On the other hand, the use of quantum genetic algorithms to solve the process of economic dispatch is also discussed and real scenarios are used for simulation tests later on. After comparing the algorithm used in this paper with several other algorithms commonly used to solve optimization problems, the results show that the algorithm used in this paper is able to find the optimal solution most quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost saving for the power generation after adding (or not adding) wind power generation is also discussed. The actual operating results prove that the algorithm proposed in this paper is economical and practical as well as superior. They are quite valuable for further research. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Power generation system containing wind power generation Economic dispatch quantum genetic algorithm

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quantum genetic algorithm assisted high speed and precision pump-probe thermoreflectance characterization of micro-/nano-structures

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2024年 224卷

作者： Xu, Yongze He, Yang Yang, Jinfeng Zhou, Yan Wu, Aihua Yu, Cui Zhai, Yuwei Liu, Yan Wu, Dihai Guo, Huaixin Sun, Huarui Harbin Inst Technol Sch Sci Key Lab Micronano Optoelect Informat Syst Shenzhen 518055 Peoples R China Harbin Inst Technol Minist Ind & Informat Technol Key Lab Micronano Optoelect Informat Syst Shenzhen 518055 Peoples R China Nanjing Normal Univ Inst Phys Frontiers & Interdisciplinary Sci Phonon Engn Res Ctr Jiangsu ProvSch Phys & Techno Ctr Quantum Transport & Thermal Energy Sci Nanjing 210023 Peoples R China Hebei Semicond Res Inst Metrol & Maintenance Dept Shijiazhuang 050051 Peoples R China Natl Key Lab Solid State Microwave Devices & Circu Shijiazhuang 050051 Peoples R China Huawei Technol Co Ltd Dongguan 523808 Peoples R China Natl Key Lab Solid State Microwave Devices & Circu Nanjing 210016 Peoples R China Shanxi Univ Collaborat Innovat Ctr Extreme Opt Taiyuan 030006 Peoples R China

The rapid and precise extraction of thermophysical properties remains an enormous challenge in pumpprobe thermoreflectance, and quantum algorithms present significant potential for addressing thermal transport problems. This paper introduces an innovative application of the quantum genetic algorithm to the fitting of experimental data from pump -probe thermoreflectance. Initially, a physical model based on the thermal transmission matrix is developed to compute the heat transport of multilayer micro -/nano -structures. The quantum genetic algorithm is then employed for multiparameter optimization in the extraction of thermophysical properties and tested on three samples. Both simulation and experimental results demonstrate that the quantum genetic algorithm assisted pump -probe thermoreflectance, capable of extracting thermophysical properties with high precision in just one minute, is approximately 30 times faster than the conventional method and 10 times faster than the genetic algorithm. Furthermore, measurement sensitivity and algorithmic randomness are analyzed. The reasons behind the phenomenon of equivalent fitting results and the indication of non -convex optimization are also presented.

关键词： quantum genetic algorithm Pump-probe thermoreflectance technique Non-convex optimization

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quantum genetic algorithm for adaptive image multi-thresholding segmentation

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INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY 2015年第3期51卷 203-211页

作者： Zhang, Jian Li, Huanzhou Tang, Zhangguo Liu, Chang Sichuan Normal Univ Sch Phys & Elect Engn Chengdu 610066 Sichuan Peoples R China Univ Lumiere Lyon 2 DISP Lab F-69005 Lyon Rhone Province France

An adaptive image multilevel thresholding segmentation algorithm is presented in this paper. The proposed algorithm introduces a parallel quantum genetic algorithm (PQGA) for histogram-based image segmentation. quantum genetic algorithm (QGA) has the advantages of fast convergence speed and strong global search capabilities. And PQGA can improve the computational efficiency of the QGA further. Without predetermining the number of the thresholds, the proposed algorithm that chooses the automatic thresholding criterion as its objective function can obtain the number of the thresholds and the corresponding thresholds accurately. The experimental results demonstrate good performance of the PQGA in solving adaptive multilevel thresholding segmentation problems by comparing with other methods for several test images.

关键词： QGA quantum genetic algorithm multi-thresholding segmentation image segmentation PQGA parallel quantum genetic algorithm ATC automatic thresholding criterion

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quantum genetic algorithm with Rotation Angle Refinement for Dependent Task Scheduling on Distributed Systems 10

Quantum Genetic Algorithm with Rotation Angle Refinement for...

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10th International Conference on Contemporary Computing (IC3)

作者： Gandhi, Tanvi Nitin Alam, Taj Jaypee Inst Informat Technol Dept Comp Sci & Engn Noida India

ISBN: (纸本)9781538630778

Distributed systems are efficient means of realizing High-Performance Computing (HPC). They are used in meeting the demand of executing large-scale high-performance computational jobs. Scheduling the tasks on such computational resources is one of the prime concerns in the heterogeneous distributed systems. Scheduling jobs on such systems are NP-complete in nature. Scheduling requires either heuristic or metaheuristic approach for sub-optimal but acceptable solutions. An application can be divided into a number of tasks which can be represented as Direct Acyclic Graph (DAG). To accomplish high performance, it is important to efficiently schedule these dependent tasks on resources with the satisfaction of the constraints defined for schedule generation. Inspired by quantum computing, this work proposes a quantum genetic algorithm with Rotation Angle Refinement (QGARAR) for optimum schedule generation. In this paper, the proposed QGARAR is compared with its peers under various test conditions to account for minimization of the makespan value of dependent jobs submitted for execution on heterogeneous distributed systems.

关键词： Dependent task scheduling genetic algorithm quantum genetic algorithm Topological sort Rotation angle refinement

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quantum genetic algorithm Based Homing Trajectory Planning of Parafoil System 34

Quantum Genetic Algorithm Based Homing Trajectory Planning o...

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第三十四届中国控制会议

作者： TAO Jin SUN Qinglin ZHU Erlin Chen Zengqiang College of Computer and Control Engineering Nankai University

ISBN: (纸本)9781467374439

Homing Trajectory planning is a core task of autonomous homing of parafoil system. This paper analyzes and establishes a mathematical model, and then proposes a homing trajectory planning method of parafoil system based on quantum genetic algorithm. By using the quantum bit with superposition state to encode the control law and introducing the quantum rotation gate to realize evolution of chromosomes, the proposed method guides and realizes homing trajectory optimization design. Simulation results under different initial states indicate that this method is effective for homing trajectory optimization of parafoil system. Compared with the chaos particle swarm optimization algorithm, the homing precision is even better.

关键词： quantum genetic algorithm Parafoil system Homing trajectory planning

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A virtual service placement approach based on improved quantum genetic algorithm

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Frontiers of Information Technology & Electronic Engineering 2016年第7期17卷 661-671页

作者： Gang XIONG Yu-xiang HU Le TIAN Ju-long LAN Jun-fei LI Qiao ZHOU National Digital Switching System Engineering&Technological Research Center Zhengzhou 450002China Department of Mathematics and Computer Science University of AntwerpAntwerp 2020Belgium

Despite the critical role that middleboxes play in introducing new network functionality,management and innovation of them are still severe challenges for network operators,since traditional middleboxes based on hardware lack service flexibility and ***,though new networking technologies,such as network function virtualization(NFV) and softwaredefined networking(SDN),are considered as very promising drivers to design cost-efficient middlebox service architectures,how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for ***,we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and ***,a framework is designed for service placement decision,and an integer linear programming model is proposed to resolve the service placement and minimize the network transport *** a heuristic solution is designed based on the improved quantum genetic *** results show that our proposed method can calculate automatically the optimal placement *** scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.

关键词： Software-defined networking(SDN) Network function virtualization quantum genetic algorithm Middlebox

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Directional Modulation Based on a quantum genetic algorithm for a Multiple-Reflection Model

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Computers, Materials & Continua 2020年第9期64卷 1771-1783页

作者： Yuwei Huang Xiubo Chen Kaiguo Yuan Jianyi Zhang Biao Liu Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Beijing Electronic Science and Technology Institute Beijing100070China Sate Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China School of Computing and Informatics The University of Louisiana at LafayetteLafayetteLA 70503USA.

Directional modulation is one of the hot topics in data security *** fulfill the requirements of communication security in wireless environment with multiple paths,this study takes into account the factors of reflections and antenna radiation pattern for directional *** other previous works,a novel multiple-reflection model,which is more realistic and complex than simplified two-ray reflection models,is proposed based on two *** focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna *** quantum approach has strengths in convergence speed and the globe searching ability for the complicated model with the large-size antenna array and multiple *** this,a phased directional modulation transmission system can be optimized as regards communication safety and improve performance based on the constraint of the pattern of the antenna *** work can spur applications of the quantum evolutionary algorithm in directional modulation technology,which is also studied.

关键词： Directional modulation quantum genetic algorithm phased antenna array multiple reflection

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Authenticity identification of speaker digital recording data based on quantum genetic algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第15期77卷 19399-19413页

作者： Zhou, Chao Pan, Ping Huang, Liang Guizhou Univ Coll Comp Sci & Technol Guiyang 550025 Guizhou Peoples R China

The problem we are trying to solve in this paper is the authenticity identification of speaker digital recording data. As an important basis of the judicial identification, it is crucial to ensure the authenticity of digital recording data. A large number of solutions have been proposed to address the problem. However, classic methods are usually based on logical symbol rather than the physical detection of energy or phase, and these solutions show drawbacks in terms of identification inefficiency, algorithm instability and heavy time overhead. In this paper, we propose to utilize the quantum theory to address the problem. Any tampering operation for digital recording data can lead to the change of charge in the memory, and it can utilize the subtle change to implement the identification. First, we analyze the quantum nature of storage and investigate to extract the transmittance of speech signal as the characteristic value through quantum tunneling theory. Second, aiming at the characteristics of speech signal, we utilize the transmittance to define the rotation angle step function and propose an improved quantum genetic algorithm to detect the change of phase. The proposed method achieves the authenticity identification based on phase detection. The results obtained in this research include the problem can be addressed by phase detection solution based on quantum genetic algorithm, and it shows performance benefits compared with existing solutions by simulation experiment. It is not only theoretically but also practically feasible to realize authenticity identification of speak digital recording data.

关键词： Speaker Digital recording data Authenticity identification quantum genetic algorithm Phase

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Target tracking approach via quantum genetic algorithm

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IET COMPUTER VISION 2018年第3期12卷 241-251页

作者： Jin, Zefenfen Hou, Zhiqiang Yu, Wangsheng Wang, Xin Air Force Engn Univ Informat & Nav Coll Xian 710077 Shaanxi Peoples R China

Aiming at an efficient feature match and similarity search in visual tracking, this study proposes a tracking algorithm based on quantum genetic algorithm. Therein, the global optimisation ability of quantum genetic algorithm is utilised. In the framework of quantum genetic algorithm, the positions of pixels are taken as individuals in population, while scale-invariant feature transform and colour features are taken as target model. Via defining the objective function, individual's fitness values can be measured. Visual tracking is realised when the pixel point with the biggest fitness value is searched and its corresponding position is returned. The experiment results show that the tracking algorithm the authors proposed performs more efficiently when it is compared with the state-of-the-art tracking algorithms.

关键词： genetic algorithms target tracking image colour analysis transforms feature extraction search problems target tracking approach quantum genetic algorithm feature match visual tracking similarity search tracking algorithm pixel position scale-invariant feature transform colour features

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