• 제목/요약/키워드: energy optimization

검색결과 2,423건 처리시간 0.024초

Joint Optimization for Residual Energy Maximization in Wireless Powered Mobile-Edge Computing Systems

  • Liu, Peng;Xu, Gaochao;Yang, Kun;Wang, Kezhi;Li, Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권12호
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    • pp.5614-5633
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    • 2018
  • Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

Topology Optimization of Plane Structures using Modal Strain Energy for Fundamental Frequency Maximization

  • Lee, Sang-Jin;Bae, Jung-Eun
    • Architectural research
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    • 제12권1호
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    • pp.39-47
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    • 2010
  • This paper describes a topology optimization technique which can maximize the fundamental frequency of the structures. The fundamental frequency maximization is achieved by means of the minimization of modal strain energy as an inverse problem so that the strain energy based resizing algorithm is directly used in this study. The strain energy to be minimized is therefore employed as the objective function and the initial volume of structures is used as the constraint function. Multi-frequency problem is considered by the introduction of the weight which is used to combine several target modal strain energy terms into one scalar objective function. Several numerical examples are presented to investigate the performance of the proposed topology optimization technique. From numerical tests, it is found to be that the proposed optimization technique is extremely effective to maximize the fundamental frequency of structure and can successfully consider the multi-frequency problems in the topology optimization process.

Two Stage Hybrid Optimization을 사용한 ESS 최적 운전 전략에 대한 연구 (A Study on ESS Optimal Operation Strategy Using Two Stage Hybrid Optimization)

  • 공은경;손진만
    • 전기학회논문지
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    • 제67권7호
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    • pp.833-839
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    • 2018
  • This paper presents an analysis and the methodology of optimal operation strategy of the ESS(Energy Storage System) for reduce electricity charges. Electricity charges consist of a basic charge based on the contract capacity and energy charge according to the power usage. In order to use electrical energy at minimal charge, these two factors are required to be reduced at the same time. QP(Quadratic Programming) is appropriate for minimization of the basic charge and LP(Linear Programmin) is adequate to minimize the energy charge. However, the integer variable have to be introduced for modelling of different charge and discharge efficiency of ESS PCS(Power Conversion System), where MILP(Mixed Integer Linear Programming) can be used. In this case, the extent to which the peak load savings is accomplished should be assumed before the energy charge is minimized. So, to minimize the electricity charge exactly, optimization is sequentially performed in this paper, so-called the Two Stage Hybird optimization, where the extent to which the peak load savings is firstly accomplished through optimization of basic charge and then the optimization of energy charge is performed with different charge and discharge efficiency of ESS PCS. Finally, the proposed method is analyzed quantitatively with other optimization methods.

Policy research and energy structure optimization under the constraint of low carbon emissions of Hebei Province in China

  • Sun, Wei;Ye, Minquan;Xu, Yanfeng
    • Environmental Engineering Research
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    • 제21권4호
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    • pp.409-419
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    • 2016
  • As a major energy consumption province, the issue about the carbon emissions in Hebei Province, China has been concerned by the government. The carbon emissions can be effectively reduced due to a more rational energy consumption structure. Thus, in this paper the constraint of low carbon emissions is considered as a foundation and four energies--coal, petroleum, natural gas and electricity including wind power, nuclear power and hydro-power etc are selected as the main analysis objects of the adjustment of energy structure. This paper takes energy cost minimum and carbon trading cost minimum as the objective functions based on the economic growth, energy saving and emission reduction targets and constructs an optimization model of energy consumption structure. And empirical research about energy consumption structure optimization in 2015 and 2020 is carried out based on the energy consumption data in Hebei Province, China during the period 1995-2013, which indicates that the energy consumption in Hebei dominated by coal cannot be replaced in the next seven years, from 2014 to 2020, when the coal consumption proportion is still up to 85.93%. Finally, the corresponding policy suggestions are put forward, according to the results of the energy structure optimization in Hebei Province.

Sizing, shape and topology optimization of trusses with energy approach

  • Nguyena, Xuan-Hoang;Lee, Jaehong
    • Structural Engineering and Mechanics
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    • 제56권1호
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    • pp.107-121
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    • 2015
  • The main objective of this research is to present the procedures of combining topology, shape & sizing optimization for truss structure by employing strain energy as objective function under the constraints of volume fractions which yield more general solution than that of total weight approach. Genetic Algorithm (GA) is used as searching engine for the convergence solution. A number of algorithms from previous research are used for evaluating the feasibility and stability of candidate to accelerate convergence and reduce the computational effort. It is followed by solving problem for topology & shape optimization and topology, shape & sizing optimization of truss structure to illustrate the feasibility of applying the objective function of strain energy throughout optimization stages.

건물에너지 효율향상을 위한 최적화 툴의 개발 (Development of Optimization Program for the Building Energy Efficiency Improvement)

  • 한수곤;임병찬;허정호;권한솔
    • 대한설비공학회:학술대회논문집
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    • 대한설비공학회 2005년도 동계학술발표대회 논문집
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    • pp.223-228
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    • 2005
  • This study develops an optimization program to use optimum design of building HVAC system reducing building energy use and cost. Doe20pt developed is an interface program between DOE2 and GenOpt to perform the optimization procedure more easily. The optimum results can be used to estimate the economical efficiency concerning the building management.

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Enhanced Hybrid XOR-based Artificial Bee Colony Using PSO Algorithm for Energy Efficient Binary Optimization

  • Baguda, Yakubu S.
    • International Journal of Computer Science & Network Security
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    • 제21권11호
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    • pp.312-320
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    • 2021
  • Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

건물에너지사용특성이 신재생에너지시스템 최적화 비율에 미치는 영향분석 (Analysis of Effects of Building Energy Consumption Characteristics on the Optimization Ratio for New and Renewable Energy Systems)

  • 이용호;홍준호;김용경;조영흠;황정하
    • 한국태양에너지학회 논문집
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    • 제34권5호
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    • pp.117-126
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    • 2014
  • This study developed a KRESS program designed to find the optimization ratio for new and renewable energy systems and analyze the effects of building energy consumption characteristics on the ratio. In spite of clear differences in predicted energy consumption and energy consumption by the loads among 18 facilities, the current formula for obligatory supply ratios applies a correction coefficient according to the building purposes based on energy consumption per each unit area in medical facilities and thus reflects no energy consumption characteristics according to the building purposes. The optimization ratio for new and renewable energy systems was the same for all facilities when the correction coefficients by the building purposes and new and renewable energy sources were all applied. When the correction coefficients were not applied, however, the optimization ratio varied according to building energy consumption characteristics. The findings raise a need to test the correction coefficients in order to select new and renewable energy systems that take into account energy consumption characteristics by the building purposes and loads and reflect economy, environmental performance, and technology.

Techno-Economic Optimization of a Grid-Connected Hybrid Energy System Considering Voltage Fluctuation

  • Saib, Samia;Gherbi, Ahmed;Kaabeche, Abdelhamid;Bayindir, Ramazan
    • Journal of Electrical Engineering and Technology
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    • 제13권2호
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    • pp.659-668
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    • 2018
  • This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

  • Park, Hong Seok;Nguyen, Trung Thanh
    • Journal of Computational Design and Engineering
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    • 제1권4호
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    • pp.256-265
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    • 2014
  • Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.