检索结果-内蒙古大学图书馆

2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Liu, Ying Sun, Tiepeng Tan, Huidan Tian, Junyang Guigang Power Supply Bureau Guangxi Power Grid Co. Ltd Guangxi Guigang537000 China Power Dispatching Control Center Guangxi Power Grid Co. Ltd Guangxi Nanning530000 China

ISBN: (纸本)9798331506797

The widespread integration of distributed photovoltaic power generation systems has transformed the distribution network from a traditional single power grid to a multi power grid, resulting in poor sensitivity effects. Therefore, this paper proposes a relay protection setting method for distributed photovoltaic access distribution networks based on the gsa algorithm. Design the specific solution process of gsa algorithm and extract real-time data of relay protection settings for distributed photovoltaic access distribution network;Determine the target value of real-time relay protection setting data from both current and voltage aspects, correspond to matching conditions, and obtain the setting result. The experimental results show that the tuning sensitivity of the proposed method is higher than 95%, and it has good tuning effect. © 2025 IEEE.

关键词： Distributed photovoltaic Distribution network Fixed value setting gsa algorithm Relay protection

来源：评论

学校读者我要写书评

暂无评论

Construction of Steering Control System for New Energy Vehicles Based on gsa algorithm

引用

Procedia Computer Science 2025年 261卷 548-556页

作者： Yuancheng You Yajuan Chen School of Intelligent Manufacturing Engineering Chongqing College of Architecture and Technology Chongqing 401331 China

With the democracy of awareness of global environmental protection on the rise, it follows that more and more alarming problems of energy shortage will make new energy vehicles the mainstream trend of future automotive development. The steering control system plays an important role in new energy vehicles, as it has been proven to improve the vehicle’s handling and safety. The intent of this paper was to build a novel energy vehicle steering control system based on the Gravitational Search algorithm (gsa) algorithm. By real-time monitoring and controlling of the steering angle of a vehicle, stability and safety can be enhanced. To solve some of the problems that exist in the currently used steering control systems, a novel construction method for a new energy vehicle steering control system has been presented in this paper based on the gsa algorithm. It has also been demonstrated via experimental verification that this method can dramatically enhance the handling and safety of vehicles. The experimental results showed that, for an angle deviation of 4, the output angle was 3.6, while, for an angle deviation of 5, the output was 4. The steering control system of new energy vehicles based on gsa algorithm can effectively analyze the impact of lateral deviation and angle error on the output angle.

关键词： gsa algorithm new energy vehicle steering control system

来源：评论

学校读者我要写书评

暂无评论

Multi scale optimization scheduling method for comprehensive energy based on dual carbon targets and gsa algorithm

Multi scale optimization scheduling method for comprehensive...

引用

2024 International Conference on Energy Technology and Electrical Power, ETEP 2024

作者： Fang, Huimin Qin, Han Zhao, Chenming State Grid Hefei Electric Power Supply Company Anhui Hefei 230041 China Hefei No.1 High School Anhui Hefei 230041 China

ISBN: (纸本)9781510690400

In the scenario of uncertainty in comprehensive energy output, the large scale of generated data and the introduction of uncertain factors in data mining can easily lead to scheduling analysis falling into local optima. To address the challenges of uncertainty factors and multi-scale characteristics in energy system optimization scheduling, this paper proposes a comprehensive energy multi-scale scheduling model based on dual carbon goals. The model aims to minimize carbon emissions, minimize energy costs, and achieve energy supply-demand balance. Corresponding objective functions are set, and multiple constraints such as energy supply-demand balance constraints, energy conversion and storage constraints, and renewable energy generation constraints are considered. A comprehensive energy multi-scale optimization scheduling model is constructed. This paper introduces the gsa algorithm to solve the model, which performs independent optimization at different time scales and coordinates through feedback mechanisms to output the globally optimal scheduling scheme. The experimental results show that this method exhibits significant superiority in energy utilization efficiency and carbon emission reduction of integrated energy systems. © 2025 SPIE.

关键词： dual carbon target gsa algorithm Integrated energy system Multi-scale Optimize scheduling

来源：评论

学校读者我要写书评

暂无评论

Solution of multi-objective optimal power flow using gravitational search algorithm

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2012年第8期6卷 751-763页

作者： Bhattacharya, A. Roy, P. K. Dr BC Roy Engn Coll Dept Elect Engn Durgapur W Bengal India

This article presents application of an efficient and reliable heuristic technique inspired by swarm behaviours in nature namely, gravitational search algorithm (gsa) for solution of multi-objective optimal power flow (OPF) problems. gsa is based on the Newton's law of gravity and mass interactions. In the proposed algorithm, the searcher agents are a collection of masses that interact with each other using laws of gravity and motion of Newton. In order to investigate the performance of the proposed scheme, multi-objective OPF problems are solved. A standard 26-bus and IEEE 118-bus systems with three different individual objectives, namely fuel cost minimisation, active power loss minimisation and voltage deviation minimisation, are considered. In multi-objective problem formulation fuel cost and loss;fuel cost and voltage deviation;fuel cost, loss and voltage deviation are minimised simultaneously. Results obtained by gsa are compared with mixed integer particle swarm optimisation, evolutionary programming, genetic algorithm and biogeography-based optimisation. The results show that the new gsa algorithm outperforms the other techniques in terms of convergence speed and global search ability.

关键词： gsa algorithm search problems evolutionary programming Optimisation techniques reliable heuristic technique multiobjective problem formulation fuel cost voltage deviation minimisation swarm behaviours multiobjective OPF problems genetic algorithm multiobjective optimal power flow solution active power loss minimisation IEEE bus systems fuel cost minimisation Newton law of gravity and mass interactions biogeography-based optimisation gravitational search algorithm load flow mixed integer particle swarm optimisation Combinatorial mathematics Power systems

来源：评论

学校读者我要写书评

暂无评论

New Approach for Sediment Yield Forecasting with a Two-Phase Feedforward Neuron Network-Particle Swarm Optimization Model Integrated with the Gravitational Search algorithm

引用

WATER RESOURCES MANAGEMENT 2019年第7期33卷 2335-2356页

作者： Meshram, Sarita Gajbhiye Ghorbani, M. A. Deo, Ravinesh C. Kashani, Mahsa Hasanpour Meshram, Chandrashekhar Karimi, Vahid Rani Durgavati Univ Dept Math & Comp Sci Jabalpur India Univ Tabriz Dept Water Engn Tabriz Iran Near East Univ Fac Engn 10 Mersin TR-99138 Nicosia North Cyprus Turkey Univ Southern Queensland Inst Agr & Environm Sch Agr Computat & Environm Sci Springfield Qld 4300 Australia Univ Mohaghegh Ardabili Dept Water Engn Ardebil Iran

Predicting sediment yield is an important task for decision-makers in environmental monitoring and water management since the benefits of applying non-linear, artificial intelligence (AI) models for optimal prediction can be far reaching in real-life decision support systems. AI-based models are considered to be favorable predictive tools since the nonlinear nature of suspended sediment data series warrants the utilization of nonlinear predictive methods for feature extraction, and for accurate simulation of suspended sediment load. In this study, Artificial Neural Network (ANN) approaches are employed to estimate the monthly sediment load where the two-phase Feed-forward Neuron Network Particle Swarm Optimization Gravitational Search algorithm (FNN-PSOgsa) is developed, and then evaluated in respect to 3 distinct algorithms: the Adaptive Neuro-Fuzzy Inference System (ANFIS), Feed-forward Neuron Network (FNN) and the single-phase Feed-forward Neuron Network Particle Swarm Optimization (FNN-PSO). The study is carried out using the monthly rainfall, runoff and sediment data spanning a 10year period (2000-2009) where about 75% of data are used in model training phase, 25% in testing phase. Three statistical performance criteria namely: the mean absolute error (MAE), Nash-Sutcliffe coefficient (NSE) and the Willmott's Index (WI) and diagnostic plots visualizing the tested results are used to evaluate the performance of four AI-based models. The results reveal that the objective model (the two-phase FNN-PSOgsa model) and the single-phase FNN-PSO model yielded more precise results compared to the other forecast models. This result accorded to an NSE value of 0.612 (for the FNN-PSOgsa model) vs. an NS value of 0.500, 0.331 and 0.244 for the FNN-PSO, FNN and ANFIS models, and WI=0.832 vs. 0.771, 0.692 and 0.726, respectively The study also demonstrated that the FNN model generated slightly better results than the ANFIS model for the estimation of sediment load data but over

关键词： Neural networks PSO algorithm gsa algorithm Sediment load Modelling

来源：评论

学校读者我要写书评

暂无评论

Proposing optimum parameters of TMDs using gsa and PSO algorithms for drift reduction and uniformity

引用

STRUCTURAL ENGINEERING AND MECHANICS 2017年第2期63卷 147-160页

作者： Mirzai, Nadia M. Zahrai, Seyed Mehdi Bozorgi, Fatemeh Univ Tehran Sch Civil Engn Coll Engn Tehran Iran Univ Tehran Sch Civil Engn Coll Engn Ctr Excellence Engn & Management Civil Infrastruc Tehran Iran Iran Univ Sci & Technol Sch Civil Engn Tehran Iran

In this study, the optimum parameters of Tuned Mass Dampers (TMDs) are proposed using Gravity Search algorithm (gsa) and Particle Swarm Optimization (PSO) to reduce the responses of the structures. A MATLAB program is developed to apply the new approach to the benchmark 10 and 40-story structures. The obtained results are compared to those of other optimization methods used in the literature to verify the developed code. To show the efficiency and accuracy of the proposed methods, nine far-field and near-field worldwide earthquakes are applied to the structures. The results reveal that in the 40-story structure, gsa algorithm can reduce the Relative Displacement (RD) and Absolute Acceleration (AA) up to 43% and 21%, respectively while the PSO decreases them by 50% and 25%, respectively. In contrast, both gsa and PSO algorithms reduce the RD and AA about 29% and 21% for the 10-story structure. Furthermore, using the proposed approach the required TMD parameters reduce by 47% and 63% in the 40 and 10-story buildings in comparison with the referenced ones. Result evaluation and related comparison indicate that these methods are more effective even by using smaller TMD parameters resulting in the reduction of acting force from TMD, having smaller stiffness and damping factors while being more cost effective due to its decreased parameters. In other words, the TMD with optimum parameters can play a positive role in both tall and typical structures.

关键词： gsa algorithm PSO algorithm TMD optimization vibration reduction

来源：评论

学校读者我要写书评

暂无评论

Interactive design and multidisciplinary optimization of geostationary communication satellite

引用

INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM 2019年第4期13卷 1519-1540页

作者： Berrezzoug, Salima Boudjemai, Abdelmadjid Bendimerad, Fethi Tarik Algerian Space Agcy Ctr Satellite Dev CDS Space Instrumentat Res Dept BP 4065 Ibn Rochd Usto Oran Algeria Tlemcen Univ Lab Telecommun LTT Dept Telecommun BP 230 Pole Chetouane Algeria Algerian Space Agcy Space Mech Res Dept Ctr Satellite Dev CDS BP 4065 Ibn Rochd Usto Oran Algeria

Currently, the design of large geostationary communication satellites is becoming more and more complex systems. On the one hand, customers are demanding high performance communications systems and this for 15-20 years orbital lifetimes. And the other hand, given the large volume and mass of communications satellites, an added constraint that resides in the volume under the launcher fairing which is sometimes represents a great handicap for the technological development of large space systems due to the technological limitation of launchers at the time. Increasing the performance and reliability of communication satellites, tools and methods are needed;the multidisciplinary design optimization methods (MDO) can be useful for this type of complex system. In geostationary communication satellite systems design, there are usually more than one design objectives, which a design team should take into account. These objectives involve system performance measures like mass, size, cost, reliability, power efficiency and system robustness. In a good design procedure, the tradeoffs between competing objectives should be incorporated so that the design team can make an informed decision. In this paper the generic geostationary communication satellite MDO problem is formulated to minimize the total mass of the satellite system under a number of practical constraints including launch vibration and acoustic disciplines. In this paper a gravitational search algorithm based on the law of gravity and mass interactions is introduced. In the proposed algorithm, the searcher agents are a collection of masses which interact with each other based on the Newtonian gravity and the laws of motion. From the results obtained in this paper and after optimization, the total mass of the studied GEO communication satellite is decreased by 185.3 kg (i.e., 7.3% of the total mass). In the case of the presence of two disciplines, acoustics and vibration, we notice that the mass becomes 3470 kg, which

关键词： Multidisciplinary design optimization Satellite gsa algorithm Discipline Acoustics Mass Vibration Interactive design Subsystem Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Board-level Intelligent Built-in Test Design of Digital Input Module by Improved BP Neural Network 9

Board-level Intelligent Built-in Test Design of Digital Inpu...

引用

9th IEEE Data Driven Control and Learning Systems Conference (DDCLS)

作者： Wang, Yasong Huang, Congzhi Zhang, Jianhua Hou, Guolian North China Elect Power Univ Sch Control & Comp Engn Beijing Peoples R China North China Elect Power Univ Key Lab Power Stn Energy Transfer Convers & Syst Beijing Peoples R China

ISBN: (纸本)9781728159225

The built-in test (BIT) technology plays a major role in heavy-duty gas turbine control system. The accuracy of BIT is a guarantee for the normal operation of the equipment. In the actual production process, conventional BIT has a relatively high false alarm rate. In this paper, an intelligent built-in test (BIT) design method was presented for digital input (DI) module using a back propagation (BP), which was optimized by improved adaptive gravitational search algorithm (IAgsa) for quantitative analysis. In order to improve defect of the basic gravitational search algorithm (gsa), a tent map for population chaos initialization was proposed. Firstly, the status information that can reflect the failure of the DI module was chosen as experimental data. Then, these data were handled by normalization. After that, multiple IAgsa-BP models were established with status information about DI module. The output of these models can fully represent the fault status of the DI module. Finally, the experimental results are shown to validate the effectiveness of the proposed approaches.

关键词： Intelligent BIT Tent map gsa algorithm BP neural network DI module

来源：评论

学校读者我要写书评

暂无评论

Gravitational Search and Sine Cosine algorithms to Enhance the VSC-HVDC System Performance Under Different Disturbances

Gravitational Search and Sine Cosine Algorithms to Enhance t...

引用

IEEE International Conference on Innovations in Power and Advanced Computing Technologies

作者： Ghayad, Mohamed S. Badra, Niveen M. Attia, Mahmoud A. Abdelaziz, Almoataz Y. Kumar, Sanjay Kumar, Sachin Saket, R. K. Ain Shams Univ Dept Phys & Engn Math Fac Engn Cairo Egypt Ain Shams Univ Dept Elect Power & Machines Fac Engn Cairo Egypt Future Univ Egypt Fac Engn & Technol Cairo Egypt IIT BHU Varanasi Dept Elect Engn Varanasi Uttar Pradesh India

ISBN: (纸本)9781538681909

This paper focuses in studying the dynamic response of the voltage source converters high-voltage direct current (VSC-HVDC) connected to grid. In order to get faster response the magnitude of the active power, reactive power and the DC link voltage should be controlled. Optimizing the parameters of PI (proportional & integration) controller is necessary to control the said quantities. In this context meta-heuristic optimization methods i.e. gravitational search algorithm (gsa) and sine cosine algorithm (SCA) are used to obtain optimal parameters of PI controller. gsa algorithm is based on the gravity law for Newton while SCA depends on mathematical model based on cosine and sine functions. It is worthy to mention these algorithms have an efficient global search capability. Using MATLABT Simulink, model of VSC-HVDC system is presented. This system is exposed to different disturbances for demonstrating its dynamic response. Simulation results exhibit the dynamic response is improved with the optimal gains than that of default ones.

关键词： VSC-HVDC Reactive power Optimization gsa algorithm SCA algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：