作者：
Yin, LinfeiGao, QiGuangxi Univ
Coll Elect Engn Nanning 530004 Guangxi Peoples R China Guangxi Univ
Inst Artificial Intelligence Nanning 530004 Guangxi Peoples R China
The meta-heuristic algorithm inspired by natural may reduce the optimization performance due to excessive imitation. This paper proposes a novel multi-objective proportional-integral-derivative optimization algorithm ...
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The meta-heuristic algorithm inspired by natural may reduce the optimization performance due to excessive imitation. This paper proposes a novel multi-objective proportional-integral-derivative optimization algorithm inspired by mathematical thought to provide a better non-dominated solution for multi-objective problems. The idea of the proportional-integral-derivative control algorithm is introduced to cooperate with multi-objective optimization problems for the first time. The proposed algorithm is employed to store and maintain non-dominated solutions. Two groups of controllers of the proposed algorithm are designed for the multi-objective optimization problems, i.e., exploitative controllers aim to obtain the local optimal solution;explorative controllers aim to obtain the global optimal solution. To verify the effectiveness of the multi-objective proportional-integral-derivative optimization algorithm, eight comparison algorithms are compared with eight benchmark functions;five comparison algorithms are compared under the multi-objective parameters optimization problem of double-fed induction generator-based wind turbines. The results of benchmark functions show that the multi-objective proportional-integral-derivative optimization algorithm has superior convergence performances and outperforms other comparison algorithms. The proposed algorithm has excellent optimization performance to obtain the minimum deviation of rotor speed and reactive power for the wind power system controller. (C) 2021 Elsevier B.V. All rights reserved.
This article reports an optimization procedure for further enhancing the wideband radar cross section (RCS) reduction bandwidth using a checkerboard metasurface (CMS). The improved fruitfly optimization algorithm is u...
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This article reports an optimization procedure for further enhancing the wideband radar cross section (RCS) reduction bandwidth using a checkerboard metasurface (CMS). The improved fruitfly optimization algorithm is used to determine the unit cells dimensions that offer a further enhanced bandwidth. Two previously reported CMSs are chosen: (a) A square-circle pair designed on Rogers 5880 with a thickness of 6.35 mm and (b) a Jerusalem cross pair designed on Rogers 3010 with a thickness of 1.27 mm. First, unit cell (a) is optimized, resulting in an improvement of 7% from the originally reported bandwidth. Similarly, unit cell (b) shows an enhancement of 5%. Because of cost considerations and in the interest of exploring alternative methods, the substrates in both cases are replaced by Taconic TLY-3 with a thickness of 1.57 mm over an air gap of 5 mm. After optimization, this configuration enhances the 10 dB RCS reduction bandwidth substantially to 81% for (a) and 102% for (b). It is also observed that the - 15 dB bandwidth of the Jerusalem cross-based CMS is 48%, which is the widest reported so far. The alternative configurations of (a) and (b) are fabricated and measured. The measurements are in good agreement with the simulation results.
This study deals with the development of an optimal power scheduling controller for energy management of distributed energy resources in the microgrid system. The developed optimized controller is implemented using li...
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This study deals with the development of an optimal power scheduling controller for energy management of distributed energy resources in the microgrid system. The developed optimized controller is implemented using lightning search algorithm to overcome the uncertainties of microgrid energy management and to provide an optimum power delivery to loads with minimum cost. The primary objectives of the proposed optimized controller are to: (i) develop an optimized controller for microgrids energy management, (ii) minimize the total operating cost of the distributed energy resources units, (iii) reduce the environmental emission, and (iv) solve the complicated constraint optimization problems. The proposed optimization algorithm is implemented in the modified IEEE 14-bus test system to optimize the microgrid power management schedule. The optimized controller is executed based on the real load varying conditions recorded in Perlis, Malaysia. It is observed that the optimized controller successfully reduced the amount of power consumption from 971.65 MW to 364.3 MW which in turn saving cost of RM 265432.06. The proposed scheduling optimized controller performance is compared with the recent reported work of backtracking search algorithmoptimization for validation. Result shows that the lightning search algorithm based MG controller produced a cost-effective system with 62.5% of cost saving and 61.98% of carbon dioxide emission reduction which is much higher compared to with MG and backtracking search algorithm based MG optimization, respectively. The effectiveness of the proposed approach outperformed other techniques in terms of minimum total operating cost of distributed energy resources and solving complicated constraints in optimization problems.
The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be...
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The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be installed by 2025. In order to carry out the wind energy project effectively, a preliminary study must be conducted. In this article, we investigated the influence of the wake effect on the efficiency of the turbines' layout in a windfarm. A distributed genetic algorithm is deployed to study the wind turbines' layout in order to alleviate the detrimental wake effect. In the current stage of this research, the historical weather data of weather stations near the site of the 29th windfarm, Taiwan, were collected by Academia Sinica. Our wake effect resilient optimized windfarm showed superior performance over that of the conventional windfarm. Additionally, an operation cost minimization process is also demonstrated and implemented using an ant colony optimization algorithm to optimize the total length of the power-carrying interconnecting cables for the turbines inside the optimized windfarm.
In view of the problems that traditional hotel management and service quality are easily affected by service personnel, and the check-in and check-out procedures are cumbersome, a smart hotel management system based o...
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ISBN:
(纸本)9781665483285;9781665483292
In view of the problems that traditional hotel management and service quality are easily affected by service personnel, and the check-in and check-out procedures are cumbersome, a smart hotel management system based on the combination of IoT and artificial intelligence technology is developed. First, process data collection is used to decompose it into relatively independent Sub-projects, and then use the design structure matrix to express the relationship between the sub-projects, and use the corresponding algorithm to identify the iterative relationship, which provides a feasible idea for project planning and process monitoring. Networking technology realizes centralized control and management of access control and hotel equipment, realizes unmanned service in the whole process from check-in to check-out, and improves efficiency by 7.8%.
In order to eliminate the blocking effect of block compressed sensing algorithm, an optimization algorithm of block compressed sensing observation matrix based on block target is studied. The theory of block compresse...
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In order to eliminate the blocking effect of block compressed sensing algorithm, an optimization algorithm of block compressed sensing observation matrix based on block target is studied. The theory of block compressed sensing is to segment the original image with fixed size to obtain the sub blocks, arrange the texture of each sub block, use the compressed sensing observation matrix to sample each sub block, and optimize the observation matrix of block compressed sensing to eliminate the blocking effect. The block target method uses sparse orthogonal basis to make the processed block target conform to sparsity and orthogonality. The sparse coefficient vector is obtained by the basis inverse transformation, and the reflection coefficient of block target is obtained by using the sparse coefficient vector to optimize the observation matrix of block compressed sensing. The experimental results show that the peak signal-to-noise ratio (PSNR) is higher than 31dB when the algorithm is applied to image reconstruction, and the relative support set error of different sparsity and observation times is low, which can effectively eliminate the blocking effect of block compressed sensing algorithm.
The sheet beam traveling-wave tube (SBTWT) with staggered double vane (SDV) structure has attracted much attention as a board band and powerful terahertz and millimeter-wave source. In this paper, the velocity taper f...
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ISBN:
(纸本)9781538682883
The sheet beam traveling-wave tube (SBTWT) with staggered double vane (SDV) structure has attracted much attention as a board band and powerful terahertz and millimeter-wave source. In this paper, the velocity taper for SDV structure is optimized with a recently proposed swarm-intelligence (SI) based optimization algorithm named dragonfly algorithm (DA) in order to enhance the beam-wave interaction efficiency in sheet beam TWT. The optimization result of this algorithm is compared with other commonly used algorithms. The taper optimized with DA is verified with CST particle in cell (PIC) simulations. The efficiency of the optimized structure has been greatly increased in both optimization and PIC simulations.
It is not perfect in view of the fact that the information guidance system of parking spaces in large and medium-sized parking lots at present, it is difficult to find a empty parking spaces in parking lots. One of th...
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ISBN:
(纸本)9781665404457
It is not perfect in view of the fact that the information guidance system of parking spaces in large and medium-sized parking lots at present, it is difficult to find a empty parking spaces in parking lots. One of the problems is large amount of calculation in traditional Dijkstra algorithm. In this paper, the improved Dijkstra algorithm is presented and optimized to find the best parking path with the purpose of looking for the nearest free parking space based on the layout model in parking lot parking guidance. The experiments show that it can find the optimal parking space and the optimal parking path by the improved Dijkstra algorithm, and improve the parking efficiency.
A patent pool strategy was proposed for use in the electric vehicle cell industry to manage patent licensing disputes and litigation. How to promote EV cell innovation diffusion under a patent pool scenario is unclear...
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A patent pool strategy was proposed for use in the electric vehicle cell industry to manage patent licensing disputes and litigation. How to promote EV cell innovation diffusion under a patent pool scenario is unclear. We introduced an innovation diffusion channel model comprising different players with patent licensing relationships and market competition relationships following evolutionary game analysis and simulation. We found the interlinked factors that influenced evolutionary stable strategies with a sensitivity test on all factors to identify the important and unimportant factors. To achieve the maximum return for the players, an optimization algorithm was introduced to find the maximum weighted object function. The decision and policy makers could focus on important factors such as improving the technology's competitive advantages, delivering more profits to its licensees with reasonable licensing fees, and finding the best patent pool strategy with the support of the optimization algorithm
Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return;however, the stra...
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Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return;however, the strategy is unclear in certain scenarios. We tried to explain the question of how to maximize the patent holder's return by appropriate patent license strategy to promote EV cell innovation diffusion, when competition and patent licensing relationship exist in the supply chain. A multistage and multichannel diffusion model of EV cell comprising the patent holder, EV cell producer and EV producers is developed;the evolutionary game is analyzed considering the competition among same stage players and patent licensing relationship among different stage players;and an optimization algorithm is introduced to find the maximum weighted object function of the patent holder. We established the multistage and multichannel diffusion model and found a nonlinear complex relationship between patent holder object function and the key factors including patent royalty pricing and innovation advantage coefficient;in addition, an optimization algorithm is developed based on adopters' decision-making related with competition and patent licensing.
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