检索结果-内蒙古大学图书馆

Economic evaluation of energy storage integrated with wind power

CARBON NEUTRALITY 2023年第1期2卷 16页

作者： Zhang, Xinjing Feng, Lu Li, Xiaoyu Xu, Yujie Wang, Liang Chen, Haisheng Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Energy storage can further reduce carbon emission when integrated into the renewable generation. The integrated system can produce additional revenue compared with wind-only generation. The challenge is how much the optimal capacity of energy storage system should be installed for a renewable generation. Electricity price arbitrage was considered as an effective way to generate benefits when connecting to wind generation and grid. This wind-storage coupled system can make benefits through a time-of-use (TOU) tariff. A proportion of electricity is stored from the wind power system at off-peak time (low price), and released to the customer at peak time (high price). Thus, extra benefits are added to the wind-storage system compared with wind-only system. A particle swarm optimization (PSO) algorithm based optimization model was constructed for this integrated system including constraints of state-of-charge (SOC), maximum storage and release powers etc. The proposed optimization model was to obtain the optimal capacity of energy storage system and its operation control strategy of the storage-release processes, to maximize the revenue of the coupled system considering the arbitrage. Furthermore, the energy storage can provide reserve ancillary services for the grid, which generates benefits. The benefits of energy storage system through reserve ancillary services were also calculated. A case study was analyzed with respect to yearly wind generation and electricity price profiles. The benefit compared with no energy storage scenario was calculated. The impact of the energy storage efficiency, cost and lifetime was considered. The sensitivity and optimization capacity under various conditions were calculated. An optimization capacity of energy storage system to a certain wind farm was presented, which was a significant value for the development of energy storage system to integrate into a wind farm.

关键词： Energy storage Wind-storage coupled system Electricity price arbitrage and ancillary services Compressed air energy storage particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

DIC measurement method based on binocular stereo vision for image 3D displacement detection

JOURNAL OF MEASUREMENTS IN ENGINEERING

引用

JOURNAL OF MEASUREMENTS IN ENGINEERING 2023年第4期11卷 437-452页

作者： Dong, Xue Zibo Vocat Inst Int Sch Zibo Peoples R China

The deformation detection of large machinery is usually achieved using three-dimensional displacement measurement. Binocular stereo vision measurement technology, as a commonly used digital image correlation method, has received widespread attention in the academic community. Binocular stereo vision achieves the goal of three-dimensional displacement measurement by simulating the working mode of the human eyes, but the measurement is easily affected by light refraction. Based on this, the study introduces particle swarm optimization algorithm for target displacement measurement on Canon imaging dataset, and introduces backpropagation neural network for mutation processing of particles in particle swarm algorithm to generate fusion algorithm. It combines the four coordinate systems of world, pixel, physics, and camera to establish connections. Taking into account environmental factors and lens errors, the camera parameters and deformation coefficients were revised by shooting a black and white checkerboard. Finally, the study first conducted error analysis on binocular stereo vision technology in three dimensions, and the relative error remained stable at 1 % within about 60 seconds. At the same time, three algorithms, including the spotted hyena algorithm, were introduced to conduct performance comparison experiments using particle swarm optimization and backpropagation network algorithms. The experiment shows that the three-dimensional error of the fusion algorithm gradually stabilizes within the range of [-0.5 %, 0.5 %] over time, while the two-dimensional error generally hovers around 0 value. Its performance is significantly superior to other algorithms, so the binocular stereo vision of this fusion algorithm can achieve good measurement results.

关键词： binocular stereo vision digital image correlation method backpropagation neural network particle swarm optimization algorithm displacement measurement

来源：评论

学校读者我要写书评

暂无评论

S-box generation algorithm based on hyperchaotic system and its application in image encryption

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2023年第17期82卷 25559-25583页

作者： Yang, Sen Tong, Xiaojun Wang, Zhu Zhang, Miao Harbin Inst Technol Comp Sci & Technol Weihai 264200 Peoples R China

S-box is the only non-linear device in the cryptographic algorithm, and its quality determines the lower limit strength of the cryptographic algorithm. However, because the image data is highly correlated, the traditional encryption methods and their S-boxes, such as AES and DES are not suitable for using in image encryption. Based on this, this paper proposes an S-box generation algorithm based on a 4D hyperchaotic system and improved particle swarm optimization. Firstly, this paper improves on the Lorenz chaotic system and proposes a 4D hyperchaotic system with a higher Lyapunov exponent and more complex dynamics. Secondly, the idea of simulated annealing algorithm is introduced into the particle swarm optimization algorithm, which further improves the efficiency of the particle swarm optimization algorithm and improves the problem that the particle swarm optimization algorithm is easy to fall into the local optimal solution. Then an improved particle swarm optimization algorithm is used to optimize the nonlinearity of the S-box to improve the performance of the S-box. Finally, use the generated S-box to design an image encryption algorithm and prove the security of the S-box. The experimental results show that the S-box designed in this paper has excellent performance in the five indicators of Nonlinearity, SAC, BIC-NL, LP, and DP. At the same time, the encryption result can resist common attacks, so it has strong multimedia security.

关键词： 4D hyperchaotic system S-box Image encryption particle swarm optimization algorithm Simulated annealing algorithm

来源：评论

学校读者我要写书评

暂无评论

Grid Scheduling Strategy Considering Electric Vehicles Participating in Multi-microgrid Interaction

引用

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2023年第3期18卷 1557-1572页

作者： Yu, Zexu Dou, Zhenhai Zhao, Ye Xie, Ruishuo Qiao, Mengmeng Wang, Yuanyuan Liu, Lianxin Shandong Univ Technol Coll Elect & Elect Engn Zibo 255049 Peoples R China

With the expansion of the scale of power grid and the increase of the number of microgrids, the energy interaction between microgrids using contact lines will greatly increase the computation of the superior dispatching center. Therefore, the contact lines between microgrids are cancelled, so that the microgrids can realize energy interaction through the distribution network. However, this method may lead to overload of distribution network connections while reducing the computation. Due to its good transfer characteristics, the addition of electric vehicles (EVs) can alleviate the contact line pressure and realize the load transfer of microgrids. On this basis, a grid dispatching model based on the participation of EVs in microgrid interaction is proposed. Contact lines between microgrids are replaced by EVs and 100% transmission through the distribution network. The grid load is optimized with the goal of minimizing total cost, maximizing renewable energy utilization, and maximizing profit of each integrator. In the process of model optimization, aiming at the problem that the speed factor in the particle swarm optimization algorithm cannot take into account the optimal direction and the optimal step size, the adaptive time factor is added to establish a two-layer improved particle swarm optimization algorithm, which realizes the cooperative optimization of load and electricity price. The simulation results show that the total cost and underutilization of renewable energy of IEEE33-node system are reduced by 13.79% and 67.85%, compared with the traditional interaction mode, while they are reduced by 0.425% and 6.11% in IEEE43-node system.

关键词： Electric vehicles Multi-microgrid Interaction particle swarm optimization algorithm Cost benefit analysist Optimal operation

来源：评论

学校读者我要写书评

暂无评论

Application of Genetic and particle swarm optimization algorithms to Portfolio optimization Problem: Borsa Istanbul and Crypto Money Exchange 4

Application of Genetic and Particle Swarm Optimization Algor...

引用

4th International Conference on Computer Science and Engineering (UBMK)

作者： Huseyinov, Ilham Ulucay, Samed Istanbul Aydin Univ Yazilim Muhendisligi Bolumu Istanbul Turkey Istanbul Aydin Univ Bilgisayar Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781728139647

particle optimization (PSO) algorithm and genetic (GA) algorithms are widely used in a variety of optimization problems. Portfolio optimization problems offer minimum risk and maximum profit-based solutions to help investors on optimal investment. Current researches have focused on PSO and GA algorithms based on Markowitz's mean variance method. This paper examines the implementation of PSO and GA algorithms to solve the optimization problem of two portfolios, Borsa Istanbul (BIST) and Cryptocurrency Exchange (KPB). This study also uses Markowitz mean variance method, that is, variance method for risk minimization and mean method for profit maximization. PSO and GA varying coefficients are compared in terms of sharpe risk percentage and portfolio profit. The comparison result is in favor of PSO algorithm.

关键词： Portfolio optimization Level Variance Model Genetic algorithm particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Low-Carbon Cold-Chain Logistics Path optimization Problem Considering the Influence of Road Impedance

引用

IEEE ACCESS 2023年 11卷 124055-124067页

作者： Zhang, Aobei Zhang, Ying Liu, Yanqiu Shenyang Univ Technol Sch Management Shenyang 100870 Peoples R China

An improved road impedance function in conformity with Chinese city road traffic is designed for calculating the actual transportation time based on real-time traffic information and the complex road environment in the city. The objective function minimizes the total distribution cost, including fixed cost, transportation cost, damage cost, energy cost, penalty cost, and carbon emission cost. A mathematical model is constructed for cold-chain logistics distribution path optimization considering the influence of road impedance. The model is solved using three particle swarm optimization algorithms with improved weights. The experimental results show that the self-adaptive weighted particle swarm optimization algorithm is more efficient in solving this model. Experimental results obtained from the cold-chain logistics path optimization model considering road impedance compared to those of the model without road impedance indicate that the former are closer to the actual situation. Based on the changes in carbon emission and total cost under different carbon taxes, we analyze the critical carbon tax value and the optimal carbon tax value range to improve the economic and environmental benefits in the distribution process. This study should prove to be of great practical significance and application value for logistics enterprises to conduct rational planning of path problems.

关键词： Real-time traffic road impedance function particle swarm optimization algorithm coldchain logistics critical carbon tax value

来源：评论

学校读者我要写书评

暂无评论

Optimal Sizing of Battery and Super-Capacitor Based on the MOPSO Technique via a New FC-HEV Application

引用

ENERGIES 2023年第9期16卷 3902页

作者： Djouahi, Abdeldjalil Negrou, Belkhir Rouabah, Boubakeur Mahboub, Abdelbasset Samy, Mohamed Mahmoud Univ Kasdi Merbah Ouargla Lab Promot & Valorisat Ressources Sahariennes VPRS BP 511 Ouargla 30000 Algeria Univ Kasdi Merbah Ouargla Elect Engn Dept BP 511 Ouargla 30000 Algeria Beni Suef Univ Fac Engn Elect Engn Dept Bani Suwayf 2722165 Egypt

In light of the energy and environment issues, fuel cell vehicles have many advantages, including high efficiency, low-temperature operation, and zero greenhouse gas emissions, making them an excellent choice for urban environments where air pollution is a significant problem. The dynamics of fuel cells, on the other hand, are relatively slow, owing principally to the dynamics of the air compressor and the dynamics of manifold filling. Because these dynamics can limit the overall performance of fuel cell vehicles, two key technologies that have emerged as critical components of electric vehicle powertrains are batteries and supercapacitors. However, choosing the best hybrid energy storage system that combines a battery and a supercapacitor is a critical task nowadays. An electric vehicle simulated application by MATLAB Code is modeled in this article using the multi-objective particle swarm optimization technique (MOPSO) to determine the appropriate type of batteries and supercapacitors in the SFTP-SC03 drive cycle. This application optimized both component sizing and power management at the same time. Batteries of five distinct types (Lithium, Li-ion, Li-S, Ni-Nicl2, and Ni-MH) and supercapacitors of two different types (Maxwell BCAP0003 and ESHSR-3000CO) were used. Each storage component is distinguished by its weight, capacity, and cost. As a consequence, using a Li-ion battery with the Maxwell BCAP0003 represented the optimal form of hybrid storage in our driving conditions, reducing fuel consumption by approximately 0.43% when compared to the ESHSR-3000CO.

关键词： fuel-cell hybrid electric vehicle particle swarm optimization algorithm hydrogen consumption multi-objective function problem energy management strategy

来源：评论

学校读者我要写书评

暂无评论

Evaluation of problems and countermeasures in marketing teaching based on cloud computing data aggregation algorithm

引用

SN APPLIED SCIENCES 2023年第5期5卷 1-12页

作者： Shen, Weinan Suzhou Vocat Univ Sch Management Suzhou 215000 Jiangsu Peoples R China

In this study, we present a highly practical marketing course. Through learning marketing, we can cultivate students' ability to analyze, solve and practice problems. Therefore, this paper would study the problems encountered in the marketing course through cloud computing technology and propose corresponding countermeasures, so as to better improve students' ability to analyze and solve problems and enhance the effectiveness of the classroom. This paper also analyzed the data aggregation algorithm based on particle swarm optimization (PSO) algorithm. The results showed that when other conditions were the same, only 6 students approve of the traditional marketing teaching mode, accounting for 12%;there were 44 people who did not approve, accounting for 88%. This number was more than half;49 students recognized the optimized marketing teaching mode, accounting for 98%;there was 1 person who did not approve, accounting for 2%. The proportion of people who did not approve after optimization was far less than that of the traditional model, which showed that cloud computing data aggregation algorithm could find out the problems in marketing teaching and provide correct countermeasures to solve them, so that the teaching model could be optimized. (1) The data aggregation algorithm based on cloud computing has a good optimization effect on the evaluation of marketing teaching problems and countermeasures, indicating a new direction for future research. (2) The combination of cloud computing and data aggregation algorithm is not only a novel research perspective, but also a perfect idea. (3) Marketing course is a very important course in today's society. The study of its teaching problems and countermeasures evaluation will help students improve their learning efficiency and enhance their ability to adapt to the society.

关键词： Marketing teaching Cloud computing Data aggregation algorithm Analysis of problems and countermeasures particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Effects of flight parameters for plant protection UAV on droplets deposition rate based on a 3D simulation approach

引用

International Journal of Agricultural and Biological Engineering 2023年第1期16卷 66-72页

作者： Lifeng Xu Zhongzhu Yang Zusheng Huang Weilong Ding Gerhard Buck-Sorlin College of Computer Science&Technology Zhejiang University of TechnologyHangzhou 310026China IRHS INRAEAGROCAMPUS OUESTUniversite d’AngersSFR 4207 QUASAV42 rue Georges Morel49071 BeaucouzécedexFrance

With the development of aviation agricultural technology,the number of farmers adopting the use of drones in daily agricultural activities is growing rapidly in recent *** these,a large portion constitutes agricultural drones being used in pest control and crop protection practices,*** spraying of *** pesticides with drones have proven to be faster than other traditional *** the downside,flight time and range of Unmanned Aerial Vehicles(UAV)are often ***,a proper arrangement of flight height and velocity will greatly improve spraying efficiency.A new strategy to optimize the flight parameters,*** height and flight velocity,for fixed-wing UAV with a 3D simulation-based approach together with an automatic optimization algorithm was proposed in this *** find the optimal parameters for a UAV to fly and spray under certain environmental conditions,a three-dimensional model of the target crop was established first,followed by a detailed simulation of droplet *** a demonstration case,a grass model was developed and used as the target plant,and a physics-based method was used to simulate realistically the movement of the droplets in the air as well as the interaction between the droplets and the plant to obtain the droplet deposition rate under the specified operating ***,the standard particle swarm optimization(PSO)algorithm was used to optimize the UAV operating parameters to obtain the best operating *** results indicate that using the standard PSO algorithm to optimize the operating parameters of the drone could significantly improve the deposition rate and find the best operating parameters.

关键词： unmanned aerial vehicle droplet deposition 3D simulation particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Lyapunov Control of High-Dimensional Closed Quantum Systems Based on particle swarm optimization

引用

IEEE ACCESS 2020年 8卷 49765-49774页

作者： Guan, Xiaoke Kuang, Sen Lu, Xiujuan Yan, Jiazhen Univ Sci & Technol China Dept Automat Hefei 230027 Peoples R China Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China

For high-dimensional closed quantum systems, this paper proposes a novel quantum Lyapunov control scheme based on the particle swarm optimization algorithm and achieves a high-probability population transfer of the system to a non-isolated target eigenstate in the LaSalle invariant set under usual smooth Lyapunov control laws. Via a quadratic Lyapunov function with unknown parameters, a control law with the unknown parameters is designed;based on the LaSalle invariance principle and the energy-level connectivity graph, the stability of the system is analyzed;by using the particle swarm optimization algorithm, a set of optimal parameters is obtained to achieve the control goal. In particular, we propose a path planning method based on the energy-level connectivity graph to determine the initial values of the unknown parameters, which is such that the optimization algorithm can efficiently and conveniently find a set of optimal solutions of the unknown parameters. Numerical simulation experiments on a five-level quantum system and a three-qubit system demonstrate that the proposed Lyapunov control scheme based on the particle swarm optimization algorithm has a good control effect.

关键词： Lyapunov methods Sociology Statistics particle swarm optimization Control systems Quantum entanglement High-dimensional quantum systems Lyapunov control particle swarm optimization algorithm parameter optimization initial values energy-level connectivity graph

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：