• Title/Summary/Keyword: Energy optimization

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Packet Size Optimization for Improving the Energy Efficiency in Body Sensor Networks

  • Domingo, Mari Carmen
    • ETRI Journal
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    • v.33 no.3
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    • pp.299-309
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    • 2011
  • Energy consumption is a key issue in body sensor networks (BSNs) since energy-constrained sensors monitor the vital signs of human beings in healthcare applications. In this paper, packet size optimization for BSNs has been analyzed to improve the efficiency of energy consumption. Existing studies on packet size optimization in wireless sensor networks cannot be applied to BSNs because the different operational characteristics of nodes and the channel effects of in-body and on-body propagation cannot be captured. In this paper, automatic repeat request (ARQ), forward error correction (FEC) block codes, and FEC convolutional codes have been analyzed regarding their energy efficiency. The hop-length extension technique has been applied to improve this metric with FEC block codes. The theoretical analysis and the numerical evaluations reveal that exploiting FEC schemes improves the energy efficiency, increases the optimal payload packet size, and extends the hop length for all scenarios for in-body and on-body propagation.

A Multi-objective Optimization Method for Energy System Design Considering Initial Cost and Primary Energy Consumption (초기투자비와 1차 에너지소비량을 고려한 에너지시스템의 다중최적 설계 방법론)

  • Kong, Dong-Seok;Jang, Yong-Sung;Huh, Jung-Ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.8
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    • pp.357-365
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    • 2014
  • This paper proposed a multi-objective optimization method for building energy system design using primary energy consumption and initial cost. The designing of building energy systems is a complex task, because life cycle cost and efficiency of building are determined by decisions of engineer during the early stage of design. Therefore, methods such as pareto analysis that can generate various alternatives for decision making are necessary. In this study, the optimization is performed using the NSGAII and case study was carried out for feasibility of the proposed method. As a result, alternative solutions can be obtained for the optimal building energy system design.

Topology Design Optimization of Electromagnetic Vibration Energy Harvester to Maximize Output Power

  • Lee, Jaewook;Yoon, Sang Won
    • Journal of Magnetics
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    • v.18 no.3
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    • pp.283-288
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    • 2013
  • This paper presents structural topology optimization that is being applied for the design of electromagnetic vibration energy harvester. The design goal is to maximize the root-mean-square value of output voltage generated by external vibration leading structures. To calculate the output voltage, the magnetic field analysis is performed by using the finite element method, and the obtained magnetic flux linkage is interpolated by using Lagrange polynomials. To achieve the design goal, permanent magnet is designed by using topology optimization. The analytical design sensitivity is derived from the adjoint variable method, and the formulated optimization problem is solved through the method of moving asymptotes (MMA). As optimization results, the optimal location and shape of the permanent magnet are provided when the magnetization direction is fixed. In addition, the optimization results including the design of magnetization direction are provided.

Resource Allocation for Relay-Aided Cooperative Systems Based on Multi-Objective Optimization

  • Wu, Runze;Zhu, Jiajia;Hu, Hailin;He, Yanhua;Tang, Liangrui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2177-2193
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    • 2018
  • This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

Broadband energy harvester for varied tram vibration frequency using 2-DOF mass-spring-damper system

  • Hamza Umar;Christopher Mullen;Soobum Lee;Jaeyun Lee;Jaehoon Kim
    • Smart Structures and Systems
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    • v.32 no.6
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    • pp.383-391
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    • 2023
  • Energy harvesting in trams may become a prevalent source of passive energy generation due to the high density of vibrational energy, and this may help power structural health monitoring systems for the trams. This paper presents a broadband vibrational energy harvesting device design that utilizes a varied frequency from a tram vehicle using a 2 DOF vibrational system combined with electromagnetic energy conversion. This paper will demonstrate stepwise optimization processes to determine mechanical parameters for frequency tuning to adjust to the trams' operational conditions, and electromagnetic parameters for the whole system design to maximize power output. The initial optimization will determine 5 important design parameters in a 2 DOF vibrational system, namely the masses (m1, m2 (and spring constants (k1, k2, k3). The second step will use these parameters as initial guesses for the second optimization which will maintain the ratios of these parameters and present electrical parameters to maximize the power output from this system. The obtained values indicated a successful demonstration of design optimization as the average power generated increased from 1.475 mW to 17.44 mW (around 12 times).

Prolong life-span of WSN using clustering method via swarm intelligence and dynamical threshold control scheme

  • Bao, Kaiyang;Ma, Xiaoyuan;Wei, Jianming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2504-2526
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    • 2016
  • Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

Shape Optimization of the H-shape Spacer Grid Spring Structure

  • Yoon, Kyung-Ho;Kim, Hyung-Kyu;Kang, Heung-Seok;Song, Kee-Nam;Park, Ki-Jong
    • Nuclear Engineering and Technology
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    • v.33 no.5
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    • pp.547-555
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    • 2001
  • In pressurized light water reactor fuel assembly, spacer grids support nuclear fuel rods both laterally and vertically. The fuel rods are supported by spacer grid springs and grid dimples that are located in the grid cell. The support system allows for some thermal expansion and imbalance of the fuel rods. The imbalance is absorbed by elastic energy to prevent coolant flow- induced vibration damage. Design requirements are defined and a design process is established. The design process includes mathematical optimization as well as practical design method. The shape of the grid spring is designed to maintain its function during the lifetime of the fuel assembly. A structural optimization method is employed for the shape design. Since the optimization is carried out in the linear range of finite element analysis, the optimum solution is verified by nonlinear analysis. A good design is found and the final design is compared with the initial conceptual design. Commercial codes are utilized for structural analysis and optimization.

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Design of Fuzzy Logic Controller for Optimal Control of Hybrid Renewable Energy System (하이브리드 신재생에너지 시스템의 최적제어를 위한 퍼지 로직 제어기 설계)

  • Jang, Seong-Dae;Ji, Pyeong-Shik
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.67 no.3
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    • pp.143-148
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    • 2018
  • In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

Improved AP Deployment Optimization Scheme Based on Multi-objective Particle Swarm Optimization Algorithm

  • Kong, Zhengyu;Wu, Duanpo;Jin, Xinyu;Cen, Shuwei;Dong, Fang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1568-1589
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    • 2021
  • Deployment of access point (AP) is a problem that must be considered in network planning. However, this problem is usually a NP-hard problem which is difficult to directly reach optimal solution. Thus, improved AP deployment optimization scheme based on swarm intelligence algorithm is proposed to research on this problem. First, the scheme estimates the number of APs. Second, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the location and transmit power of APs. Finally, the greedy algorithm is used to remove the redundant APs. Comparing with multi-objective whale swarm optimization algorithm (MOWOA), particle swarm optimization (PSO) and grey wolf optimization (GWO), the proposed deployment scheme can reduce AP's transmit power and improves energy efficiency under different numbers of users. From the experimental results, the proposed deployment scheme can reduce transmit power about 2%-7% and increase energy efficiency about 2%-25%, comparing with MOWOA. In addition, the proposed deployment scheme can reduce transmit power at most 50% and increase energy efficiency at most 200%, comparing with PSO and GWO.

Multi-objective optimization of printed circuit heat exchanger with airfoil fins based on the improved PSO-BP neural network and the NSGA-II algorithm

  • Jiabing Wang;Linlang Zeng;Kun Yang
    • Nuclear Engineering and Technology
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    • v.55 no.6
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    • pp.2125-2138
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    • 2023
  • The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.