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Dual temperature parameter control of PEMFC stack based on improved differential evolution algorithm

RENEWABLE ENERGY 2025年 241卷

作者： Chen, Xi Feng, Wentao You, Shuhuai Hu, Yukang Wan, Yixin Zhao, Bin Hunan Inst Sci & Technol Sch Energy & Elect Engn Yueyang 414006 Peoples R China Hunan Inst Sci & Technol Coll Mech Engn Yueyang 414006 Peoples R China Changsha Univ Sci & Technol Sch Elect & Informat Engn Changsha 410000 Peoples R China Hunan Zhongding Thermal Technol Co LTD Yueyang 414006 Peoples R China First High Sch Yueyang Yueyang 414006 Peoples R China

Temperature is a vital parameter that impacts the capability and lifespan of proton exchange membrane fuel cell (PEMFC). Proper temperature control can effectively prevent membrane dehydration or catalyst activity degradation, thereby enhancing the performance of PEMFC. In this paper, a temperature management system model based on dual proportional integral differential (PID) controllers is established to accurately control the temperature of the cooling water and stack. An improved differential evolution algorithm (IDE) is designed to adjust the mutation factor, crossover factor and search range. The parameters of the dual IDE-PID controllers are synchronously optimized to maintain a temperature difference of approximately 5 K between the inlet cooling water and stack. The performance of IDE-PID controller is compared with other control strategies. The results show that the overshoot of IDE-PID controller in controlling the stack temperature is lowered by 83 %, 77 %, and 75 % compared to the Fuzzy-PID, GA (genetic algorithm)-PID and PSO (particle swarm optimization)-PID, respectively. The temperature fluctuations of stack can be controlled below 0.15 K. Meanwhile, IDE-PID controller has a stable control effect at different pressures, relative humidities and air excess ratios. The system is able to make rapid adjustments in the event of sudden external disturbances.

关键词： PEMFC Temperature control Dual PID controllers improved differential evolution algorithm

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improved differential evolution algorithm of model-based diagnosis in traction substation fault diagnosis of high-speed railway

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IET ELECTRICAL SYSTEMS IN TRANSPORTATION 2016年第3期6卷 163-169页

作者： Hu, Keting Liu, Zhigang Huang, Ke Dai, Chengxi Gao, Song Southwest Jiaotong Univ Sch Elect Engn Chengdu Sichuan Peoples R China Sichuan Elect Power Design & Consulting Co LTD Chengdu Sichuan Peoples R China

The traction substation plays an important role in high-speed railway (HSR) as it can provide electric energy for trains, whose fault may threaten the safe and stable operation of HSR. Compared with common diagnosis methods, such as expert systems that heavily depend on professional experience, model-based diagnosis (MBD) has some distinct advantages. However, the inefficiency and incompleteness of calculating minimal hitting sets (MHSs) limit the performance of MBD. To reduce these limitations, the binary differential evolution with secondary population algorithm is proposed to calculate the MHSs. This algorithm can take advantage of differential evolution algorithm to improve the computational efficiency. The secondary population is used to enhance the convergence rate. In addition, the MHSs ensured strategy is proposed to improve the computational accuracy. Experiments are carried out on an actual traction substation in Hefei-Nanning HSR, and the results show that the MHSs can be solved accurately to finish the fault diagnosis of the traction substation in a short time.

关键词： fault diagnosis traction power supplies railway electrification railway safety evolutionary computation convergence Hefei-Nanning HSR convergence rate secondary population algorithm binary differential evolution MHS minimal hitting sets MBD high-speed railway traction substation fault diagnosis model-based diagnosis improved differential evolution algorithm

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Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm

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Frontiers in Energy 2023年第6期17卷 782-795页

作者： Jing ZHANG Tonghe WANG Jiongcong CHEN Zhuoying LIAO Jie SHU School of Energy Science and Engineering University of Science and Technology of ChinaHefei 230026China Guangzhou Institute of Energy Conversion Chinese Academy of SciencesGuangzhou 510640China Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering Changzhou 213001China

China is vigorously promoting the “whole county promotion” of distributed photovoltaics (DPVs). However, the high penetration rate of DPVs has brought problems such as voltage violation and power quality degradation to the distribution network, seriously affecting the safety and reliability of the power system. The traditional centralized control method of the distribution network has the problem of low efficiency, which is not practical enough in engineering practice. To address the problems, this paper proposes a cluster voltage control method for distributed photovoltaic grid-connected distribution network. First, it partitions the distribution network into clusters, and different clusters exchange terminal voltage information through a “virtual slack bus.” Then, in each cluster, based on the control strategy of “reactive power compensation first, active power curtailment later,” it employs an improved differential evolution (IDE) algorithm based on Cauchy disturbance to control the voltage. Simulation results in two different distribution systems show that the proposed method not only greatly improves the operational efficiency of the algorithm but also effectively controls the voltage of the distribution network, and maximizes the consumption capacity of DPVs based on qualified voltage.

关键词： distributed photovoltaics(DPVs) cluster partitioning improved differential evolution algorithm voltage control consumption capacity of distributed photovoltaics

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An improved differential evolution algorithm for solving a distributed assembly flexible job shop scheduling problem

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MEMETIC COMPUTING 2019年第4期11卷 335-355页

作者： Wu, Xiuli Liu, Xiajing Zhao, Ning Univ Sci & Technol Beijing Dept Logist Engn Sch Mech Engn Room 514B Beijing 100083 Peoples R China

The single-factory manufacturing is gradually transiting to the multi-factory collaborative production with the globalization. The decentralization of resources and the heterogeneity of the production modes make it difficult to solve this kind of problem. Therefore, the distributed assembly flexible job shop scheduling problem (DAFJSP) is studied. DAFJSP can be decomposed into several flexible job shop scheduling problems and several single machine factory scheduling problems. To begin with, a mixed integer linear programming model for the DAFJSP is formulated to minimize the earliness/tardiness and the total cost simultaneously. Then, an improved differential evolution simulated annealing algorithm (IDESAA) is proposed. The balanced scheduling algorithm is designed to trade off the two objectives. Two crossover and mutation operators are designed. Due to its strong robustness, simulated annealing is integrated to local search the best Pareto solutions. The greedy idea combined with the Non-Dominated Sorted selection is employed to select the offspring. Finally, comprehensive experiments are conducted and the results show that the proposed algorithm can solve DAFJSP effectively and efficiently.

关键词： Distributed assembly flexible job shop scheduling problem improved differential evolution algorithm Balanced algorithm Earliness/tardiness Cost

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An improved differential evolution algorithm for the task assignment problem

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2011年第4期24卷 616-624页

作者： Zou, Dexuan Liu, Haikuan Gao, Liqun Li, Steven Xuzhou Normal Univ Sch Elect Engn & Automat Xuzhou 221116 Jiangsu Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Liaoning Peoples R China Univ S Australia Div Business Adelaide SA 5001 Australia

An improved differential evolution algorithm (IDE) is proposed to solve task assignment problem. The IDE is an improved version of differential evolution algorithm (DE), and it modifies two important parameters of DE algorithm: scale factor and crossover rate. Specially, scale factor is adaptively adjusted According to the objective function values of all candidate solutions, and crossover rate is dynamically adjusted with the increasement of iterations. The adaptive scale factor and dynamical crossover rate are combined to increase the diversity of candidate solutions, and to enhance the exploration capacity of solution space of the proposed algorithm. In addition, a usual penalty function method is adopted to trade-off the objective and the constraints. Experimental results demonstrate that the optimal solutions obtained by the IDE algorithm are all better than those obtained by the other two DE algorithms on solving some task assignment problems. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： improved differential evolution algorithm Task assignment problem differential evolution algorithm Scale factor Crossover rate Penalty function method

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Spectrum parameter estimation in Brillouin scattering distributed temperature sensor based on cuckoo search algorithm combined with the improved differential evolution algorithm

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OPTICS COMMUNICATIONS 2015年 357卷 15-20页

作者： Zhang, Yanjun Yu, Chunjuan Fu, Xinghu Liu, Wenzhe Bi, Weihong Yanshan Univ Sch Informat Sci & Engn Qinhuangdao 066004 Peoples R China Key Lab Special Fiber & Fiber Sensor Yanshan Hebei Province Peoples R China

lii Lhe distributed optical fiber sensing system based on Brinouin scattering, strain and temperature are the main measuring parameters which can be obtained by analyzing the Brillouin center frequency shift. The novel algorithm which combines the cuckoo search algorithm (CS) with the improved differential evolution (IDE) algorithm is proposed for the Brillouin scattering parameter estimation. The CS-IDE algorithm is compared with CS algorithm and analyzed in different situation. The results show that both the CS and CS-IDE algorithm have very good convergence. The analysis reveals that the CS-IDE algorithm can extract the scattering spectrum features with different linear weight ratio, linewidth combination and SNR. Moreover, the BOTDR temperature measuring system based on electron optical frequency shift is set up to verify the effectiveness of the CS-IDE algorithm. Experimental results show that there is a good linear relationship between the Brillouin center frequency shift and temperature changes. (C) 2015 Elsevier B.V. All rights reserved

关键词： Distributed fiber sensors Brillouin scattering spectrum Cuckoo search algorithm improved differential evolution algorithm

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improved differential evolution algorithm FOR SOLVING MULTI-PERSON NONCOOPERATIVE GAME

JOURNAL OF NONLINEAR FUNCTIONAL ANALYSIS

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JOURNAL OF NONLINEAR FUNCTIONAL ANALYSIS 2022年 2022卷

作者： Li, Huimin Xiang, Shuwen Huang, Shiguo Jia, Wensheng Yang, Yanlong Guizhou Univ Coll Math & Stat Guiyang 550025 Peoples R China Guiyang Univ Coll Math & Informat Sci Guiyang 550005 Peoples R China Zhengzhou Univ Light Ind Dept Math & Informat Sci Zhengzhou 450002 Peoples R China

In this paper, the nonzero sum multi-person noncooperative game is considered, and this game can be viewed as a global optimization problem. For solving this problem, an improved differential evolution algorithm is proposed. Our algorithm combines multi-strategy differential operators and crossover operators with a random walk. First, the population is initialized by a set of good points. Second, the single mutation mode is replaced by a multi-mode. Meanwhile, a random walk mechanism is introduced in the crossover process of the differential evolution algorithm. The convergence of the improved algorithm is then proved by using an infinite product method. Finally, the proposed algorithm is illustrated via some numerical examples, and the experimental results show that the proposed new algorithm can solve the multi-person game.

关键词： Global optimization problem improved differential evolution algorithm Multi-person noncooperative game Nash equilibrium

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A two-step approach for damage detection in laminated composite structures using modal strain energy method and an improved differential evolution algorithm

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COMPOSITE STRUCTURES 2016年第Jul.期147卷 42-53页

作者： Vo-Duy, T. Ho-Huu, V. Dang-Trung, H. Nguyen-Thoi, T. Ton Duc Thang Univ Inst Computat Sci Div Computat Math & Engn Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Civil Engn Ho Chi Minh City Vietnam

The paper presents a two-step approach based on modal strain energy method and an improved differential evolution algorithm for damage detection in laminated composite structures. First, the modal strain energy based method is employed to identify a set of potential damaged elements. Then, the improved differential evolution algorithm is utilized to minimize the function of mode shape error with design variables relating to the extent of identified damaged elements. Here, the function of mode shape error is defined by the shift between the mode shape of the damaged structure and that of the healthy structure. The proposed approach is applied for a cross-ply (0 degrees/90 degrees/0 degrees) laminated composite beam and a cross-ply (0 degrees/90 degrees/0 degrees) square laminated composite plate with multiple damaged elements. In addition, the effect of noise on the accuracy of damage identification is also investigated. Numerical results show that the proposed approach is effective for damage detection in laminated composite beam and plate structures for both cases with noise and without noise. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Damage identification Modal strain energy improved differential evolution algorithm Composite structure Mode shape error

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Multi-stage method to identify structural damage using multiple damage location assurance criterion and an improved differential evolution algorithm

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2017年第1期10卷 1066-1081页

作者： Wu, Chunli Liu, Hanbing Qin, Xuxi Tan, Guojin Gu, Zhengwei Jilin Univ Coll Transportat Changchun 130021 Jilin Peoples R China

For the damage identification technique of civil structures, the reduction of the computational cost for methods based on the optimization algorithms is the most crucial step. In this study, a fast multi-stage method is developed that uses the multiple damage location assurance criterion and an improved differential evolution algorithm. In the new method, the suitable damage range is selected in different stages to reduce the computational cost of structural analysis. Five mutation operators are analysized not only in the basic differential evolution algorithm but also in the improved one. A new adaptive scaling factor with a segmented function is proposed which can operate the decay rate to avoid the premature phenomenon. The results of the study show that the precise locations and extents of structural damage are successfully realized. It is also shown that the multi-stage method using the improved differential evolution algorithm is substantially faster as compared to the basic one and can be used as an efficient and powerful measure of structural damage identification.

关键词： damage identification multiple damage location assurance criterion improved differential evolution algorithm multi-stage method adaptive scaling factor

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Non-intrusive Load Monitoring Method Based on improved differential evolution algorithm 11

Non-intrusive Load Monitoring Method Based on Improved Diffe...

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11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Lu, Chunguang Ma, Lvbin Xu, Tao Ding, Guofeng Wu, Chenghuan Jiang, Xuedong State Grid Zhejiang Elect Power Res Inst Hangzhou 310014 Peoples R China Zhejiang Huayun Informat Technol Co Ltd Hangzhou 310012 Peoples R China State Grid Ningbo Elect Power Co Ningbo 315000 Peoples R China Zhejiang Univ Hangzhou 310027 Peoples R China

ISBN: (纸本)9781728121659

Non-intrusive load monitoring is an efficient way to identify the load and get the details of the user's power consumption information. This paper proposes a new non-intrusive load monitoring method based on improved differential evolution algorithm. Firstly, the advantages of non-intrusive load monitoring are briefly introduced. Secondly, the detailed procedure of load identification of household appliances by improved differential evolution algorithm is described. At last, an experimental platform is established to test the effectiveness of the proposed non-intrusive load monitoring method. By introducing the signal-to-noise ratio and load identification rate, the performance of improved differential evolution algorithm is studied.

关键词： Household appliances Non-intrusive load monitoring improved differential evolution algorithm Signal-to-noise ratio Load identification rate

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