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4th International Conference on Intelligent Green Building and Smart Grid (IGBSG)

作者： You, Wen-xia Zhao, Di Wang, Mao-mao China Three Gorges Univ Hubei Prov Key Lab Operat & Control Cascaded Hydr Coll Elect Engn & New Energy Yichang Peoples R China State Grid Xiangyang Power Supply Co Xiangyang Peoples R China

ISBN: (纸本)9781728121482

In order to effectively solve the problem of fluctuation of wind power output, the optimal operation model of wind power pumped storage joint system considering the output fluctuation is established. With scale expansion of the joint system model, the conventional algorithm may have certain limitations. Therefore, according to the characteristics of bat algorithm with dealing with high dimension, multiple constraints, the bat algorithm can be applied to the joint optimization operation of wind power pumped storage joint system. This paper proposes an improved bat algorithm. The results show that the joint operation of wind power pumped storage can effectively stabilize wind power output fluctuation when the improved bat algorithm is used. The convergence speed and optimization precision is obviously improved comparing improved bat algorithm with basic bat algorithm and PSO algorithm.

关键词： wind power pumped storage optimized operation power outputfluctuation improved bat algorithm

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Ulti period optimal scheduling of wind, thermo and storage combined system based on improved bat algorithm 14

Ulti period optimal scheduling of wind, thermo and storage c...

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14th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Chen, Xiangwu Wang, Kaiyan Dong, Kaisong Jia, Rong Xian Univ Technol Elect Power Res Inst Xian Shaanxi Peoples R China Xian Univ Technol Xian Key Lab Intelligent Energy Xian Shaanxi Peoples R China Gansu Prov Elect Power Res Inst Lanzhou Gansu Peoples R China

ISBN: (纸本)9781538694909

In order to solve the environmental pollution caused by traditional thermal power generation and the intermittent and fluctuating problems of renewable energy, a multi time optimal scheduling method, which includes wind power, thermal power and energy storage, is proposed. With the goal of minimum operating cost and maximum wind power consumption, a multi time optimal scheduling model for wind and fire storage system is established. In addition to the operation and maintenance costs and depreciation costs, the power loss and the loss caused by charge discharge efficiency in the process of state switching are considered. The cost of energy storage is taken into account in the established energy storage cost function. bat algorithm is used to solve the model. Considering the shortcomings of the diversity of bat algorithm, Halton sequence is introduced to improve the algorithm. Finally, the improved IEEE 30 node system is used as an example test system to verify the effectiveness of the proposed method, and it is concluded that the proposed scheduling model can improve the capacity of wind power consumption, reduce the power output of thermal power, save the cost of coal consumption and reduce the total cost of the system operation.

关键词： Microgrid energy storage utilization ratio of wind power optimal scheduling improved bat algorithm

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Research on multi-UAVs route planning method based on improved bat optimization algorithm

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COGENT ENGINEERING 2023年第1期10卷

作者： Wang, Yongcheng Hu, Yaqin Zhang, Guohui Cai, Chenxiao Zhengzhou Univ Aeronaut Dept Ind Engn Zhengzhou 450046 Peoples R China Zhengzhou Univ Aeronaut Dept Ind Engn Sch Management Engn Zhengzhou Peoples R China Nanjing Univ Sci & Technol Sch Automat Nanjing Peoples R China

In a complex navigation environment, it is very important to solve the problems of multiple constraints and complex calculations in the route planning process of multiple reconnaissance unmanned aerial vehicles (UAVs) to improve the flight reconnaissance effect, and the bat algorithm (BA) with simple parameters has a certain effect on it. Aiming at the problems of unbalanced global optimization and local optimization and slow convergence speed in the later iteration of the BA in the path planning of multi-reconnaissance UAVs, a Levy-based flight search strategy and an improved bat algorithm (IBA) with changing speed are designed. In order to solve the multi-UAV route planning problem, the 3D space is reduced to a divided two-dimensional space based on the "scatter plot" method, and the spatial encoding method is used. Finally, it is proved that the IBA is theoretically more concise and effective than other algorithms.

关键词： improved bat algorithm scatter plot Levy flight inertia weight

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A Novel improved bat algorithm Based on Hybrid Parallel and Compact for Balancing an Energy Consumption Problem

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INFORMATION 2019年第6期10卷 194页

作者： Trong-The Nguyen Pan, Jeng-Shyang Dao, Thi-Kien Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350014 Fujian Peoples R China Univ Manage & Technol Dept Informat Technol Haiphong 180000 Vietnam Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266510 Shandong Peoples R China Chaoyang Univ Sci & Technol Coll Informat Taichung 413 Taiwan

This paper proposes an improved bat algorithm based on hybridizing a parallel and compact method (namely pcBA) for a class of saving variables in optimization problems. The parallel enhances diversity solutions for exploring in space search and sharing computation load. Nevertheless, the compact saves stored variables for computation in the optimization approaches. In the experimental section, the selected benchmark functions, and the energy balance problem in Wireless sensor networks (WSN) are used to evaluate the performance of the proposed method. Results compared with the other methods in the literature demonstrate that the proposed algorithm achieves a practical method of reducing the number of stored memory variables, and the running time consumption.

关键词： improved bat algorithm optimization deployment problems probabilistic model wireless sensor network

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Horizontal Bending Angle Optimization Method for Scraper Conveyor Based on improved bat algorithm

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algorithmS 2019年第4期12卷 84-84页

作者： Liu, Ting Tan, Chao Wang, Zhongbin Xu, Jing Man, Yiqiao Wang, Tuo China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Jiangsu Peoples R China Jiangsu Univ Sci & Technol Marine Equipment & Technol Inst Zhenjiang 212003 Jiangsu Peoples R China China Univ Min & Technol State Key Lab Geomechan & Deep Underground Engn Sch Mech & Civil Engn Xuzhou 221116 Jiangsu Peoples R China

The horizontal bending angle of scraper conveyor has a great influence on the running resistance, the current consumption, coal winning efficiency of the working surface, etc. Approximately 1-3 degrees is usually the range of horizontal bending angle, but does not indicate the optimum bending angle of the coal mining face. To find the optimal horizontal bending angle, an optimization method is proposed. A mathematical calculation model of the running resistance of the scraper is established based on the direction of the shearer operation. Then, a method of adjusting the step size of the search by inertia weight and expanding fly distance range obeying the t-distribution is proposed based on the basic bat algorithm (BA). Finally, an industrial application was conducted in 21220 Changcun fully mechanized coal mining face, Henan Province. The results show that the current consumption by the scraper conveyor was reduced by 31% when the horizontal bending angle of the S-bending area was 0.66 degrees. Meanwhile, the theoretical current has good consistency with the experimental data, and the average absolute error was 3%.

关键词： scraper conveyor S-bending area horizontal bending angle improved bat algorithm inertia weight t-distribution

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Multi-sensor Detection Network based on improved bat algorithm. 3

Multi-sensor Detection Network based on Improved Bat Algorit...

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3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Xie, Jiahao Wei, Daozhi Air Force Engn Univ Grad Coll Xian 710051 Shaanxi Peoples R China Air Force Engn Univ Air & Missile Def Coll Xian 710051 Shaanxi Peoples R China

ISBN: (纸本)9781538645093

In view of the disadvantages of low quality and slow calculation speed in the current establishment of multi-sensor detection network algorithms, this paper introduces an improved bat algorithm to solve the optimal solution of the detection network. The basic bat algorithm was improved by K-means algorithm initialization, speed update using adaptive step size, reverse direction search and mutation operation, and an improved bat algorithm was obtained. Simulation experiments show that the improved algorithm has significantly improved the speed of calculation and optimization. In addition, by comparing the improved bat algorithm with the particle swarm optimization algorithm and bee colony algorithm, it is proved that the proposed algorithm is of higher quality and easier to solve. Get the optimal solution of the probe network.

关键词： improved bat algorithm multi-sensor detection network optimal solution

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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an improved bat algorithm

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WATER 2018年第9期10卷 1130-1130页

作者： Farzin, Saeed Singh, Vijay P. Karami, Hojat Farahani, Nazanin Ehteram, Mohammad Kisi, Ozgur Allawi, Mohammed Falah Mohd, Nuruol Syuhadaa El-Shafie, Ahmed Semnan Univ Fac Civil Engn Dept Water Engn & Hydraul Struct Semnan *** Iran Texas A&M Univ Zachry Dept Civil Engn Dept Biol & Agr Engn 321 Scoates Hall College Stn TX 77843 USA Ilia State Univ Fac Nat Sci & Engn Tbilisi 0162 Georgia Univ Kebangsaan Malaysia Fac Engn & Built Environm Civil & Struct Engn Dept Bangi 43600 Malaysia Univ Malaya Fac Engn Civil Engn Dept Kuala Lumpur 50603 Malaysia

Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, improved bat algorithm (IBA). The major function of the IBA is to optimize the estimated value of the three-parameters associated with the Muskingum model. The IBA acts based on the chaos search tool, which mainly enhances the uniformity and erogidicty of the population. In addition, the current research, unlike the other existing models which consider flood routing, is based on dividing one reach to a few intervals to increase the accuracy of flood routing models. Three case studies with lateral flow were considered for this study, including the Wilson flood, Karahan flood, and Myanmar flood. Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. In addition, increasing the number of intervals for flood routing significantly improved the accuracy of the results. The results indicated that the Sum of Absolute Deviations (SAD) using IBA for the Karahan flood was 117, which had reduced by 83%, 88%, 94%, and 12%, compared to the PSO, GA, HS, and BA, respectively. Furthermore, the achieved results for the Myanmar flood showed that SSD for IBA relative to GA, BA, and PSO

关键词： flood routing Muskingum model hydrologic models improved bat algorithm Wilson flood Karahan flood

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Multi-step wind speed forecasting based on a hybrid forecasting architecture and an improved bat algorithm

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ENERGY CONVERSION AND MANAGEMENT 2017年 143卷 410-430页

作者： Xiao, Liye Qian, Feng Shao, Wei Univ Elect Sci & Technol China Sch Phys Elect Chengdu 610054 Peoples R China Peking Univ Dept Elect Engn & Comp Sci Beijing Peoples R China

As one of the most promising sustainable energy sources, wind energy plays an important role in energy development because of its cleanliness without causing pollution. Generally, wind speed forecasting, which has an essential influence on wind power systems, is regarded as a challenging task. Analyses based on single-step wind speed forecasting have been widely used, but their results are insufficient in ensuring the reliability and controllability of wind power systems. In this paper, a new forecasting architecture based on decomposing algorithms and modified neural networks is successfully developed for multi-step wind speed forecasting. Four different hybrid models are contained in this architecture, and to further improve the forecasting performance, a modified bat algorithm (BA) with the conjugate gradient (CG) method is developed to optimize the initial weights between layers and thresholds of the hidden layer of neural networks. To investigate the forecasting abilities of the four models, the wind speed data collected from four different wind power stations in Penglai, China, were used as a case study. The numerical experiments showed that the hybrid model including the singular spectrum analysis and general regression neural network with CG-BA (SSA-CG-BA-GRNN) achieved the most accurate forecasting results in one-step to three-step wind speed forecasting. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Hybrid forecasting architecture improved bat algorithm Singular spectrum analysis, wind speed forecasting

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Application Research of RBF Neural Network Based on improved bat algorithm in Fault Diagnosis of Train-Ground Wireless Communication Equipment

Application Research of RBF Neural Network Based on Improved...

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Chinese Automation Congress

作者： Yaolin Cui Cheng Li Yunshui Zheng Shenhua Baoshen Railway company Limited Ordos China School of Automation and Electrical Engineering Lanzhou Jiatotong University Lanzhou China

Considering the ambiguity, complexity and uncertainty of the train-ground wireless communication equipment, to locate the cause of the fault in time and improve the diagnostic accuracy, a fault diagnosis method for the train-ground wireless communication equipment with improved bat algorithm (IBA) optimized RBF neural network is proposed. In order to improve the global search ability of the bat algorithm, based on the standard bat algorithm, the fuzzy RBF neural network structural parameters are optimized by improving the inertia weight of the bat algorithm and then performing the Gaussian mutation operation on the bat algorithm. Therefore, the fault diagnosis model of train-ground wireless communication equipment based on IBA optimized fuzzy RBF neural network is established. The simulation results show that compared with the standard BA-optimized fuzzy neural network, the accuracy of fault diagnosis of the IBA optimized fuzzy RBF neural network is greatly improved, and the number of trainings is reduced to 29 steps.

关键词： Train-ground wireless communication equipment Fuzzy RBF neural network improved bat algorithm Fault diagnosis

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improved bat algorithm for structural reliability assessment: application and challenges

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MULTIDISCIPLINE MODELING IN MATERIALS AND STRUCTURES 2016年第2期12卷 218-253页

作者： Chakri, Asma Khelif, Rabia Benouaret, Mohamed Badji Mokhtar Univ UBMA Dept Mech Engn Ind Mech Lab Annaba Algeria

Purpose - The first order reliability method requires optimization algorithms to find the minimum distance from the origin to the limit state surface in the normal space. The purpose of this paper is to develop an improved version of the new metaheuristic algorithm inspired from echolocation behaviour of bats, namely, the bat algorithm (BA) dedicated to perform structural reliability analysis. Design/methodology/approach - Modifications have been embedded to the standard BA to enhance its efficiency, robustness and reliability. In addition, a new adaptive penalty equation dedicated to solve the problem of the determination of the reliability index and a proposition on the limit state formulation are presented. Findings - The comparisons between the improved bat algorithm (iBA) presented in this paper and other standard algorithms on benchmark functions show that the iBA is highly efficient, and the application to structural reliability problems such as the reliability analysis of overhead crane girder proves that results obtained with iBA are highly reliable. Originality/value - A new iBA and an adaptive penalty equation for handling equality constraint are developed to determine the reliability index. In addition, the low computing time and the ease implementation of this method present great advantages from the engineering viewpoint.

关键词： Metaheuristic Adaptive penalty equation FORM improved bat algorithm Most probable point Reliability index

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