• International journal of advanced smart convergence
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• v.7 no.4
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• pp.19-26
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• 2018

One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don't need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.116-129
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• 2001

To improve the performance of the inverse halftoning, smoothing masks should be designed optimally by using the accurate information of halftone cells. In this thesis, the method of energy minimization is so defined as to determine the exact information of halftone cell. A heuristic search method is proposed to obtain efficiently the parameters of halftone cells which determine the minimum energy. A halftone-peak modeling method with several functions is proposed and used to get initial values of the parameters. The dimension decomposition technique is also adopted to speed up the search process of energy minimization. Several experiments show that the proposed method extracts correct location of the seed pixel of the halftone cell and the extracted information of the halftone cell can be used to get more exactly smoothed color images. The proposed method can be applied to extract the texture patterns, to separate channel images of a scanned color halftone image, and to extract the moire area in an image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5712-5728
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• 2017

Recently, there are many studies, that considering green wireless cellular networks, have taken the energy consumption of the base station (BS) into consideration. In this work, we first introduce an energy consumption model of multi-mode sharing BS powered by multiple energy sources including renewable energy, local storage and power grid. Then communication load requests of the BS are transformed to energy demand queues, and battery energy level and worst-case delay constraints are considered into the virtual queue to ensure the network QoS when our objective is to minimize the long term electricity cost of BSs. Lyapunov optimization method is applied to work out the optimization objective without knowing the future information of the communication load, real-time electricity market price and renewable energy availability. Finally, linear programming is used, and the corresponding energy efficient scheduling policy is obtained. The performance analysis of our proposed online algorithm based on real-world traces demonstrates that it can greatly reduce one day's electricity cost of individual BS.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.36-44
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• 2014

Exploiting the energy-delay tradeoff for energy saving is critical for developing green wireless communication systems. In this paper, we investigate the delay-constrained energy-efficient packet transmission. We aim to minimize the energy consumption of multiple randomly arrived packets in an additive white Gaussian noise channel subject to individual packet delay constraints, by taking into account the practical on-off circuit power consumption at the transmitter. First, we consider the offline case, by assuming that the full packet arrival information is known a priori at the transmitter, and formulate the energy minimization problem as a non-convex optimization problem. By exploiting the specific problem structure, we propose an efficient scheduling algorithm to obtain the globally optimal solution. It is shown that the optimal solution consists of two types of scheduling intervals, namely "selected-off" and "always-on" intervals, which correspond to bits-per-joule energy efficiency maximization and "lazy scheduling" rate allocation, respectively. Next, we consider the practical online case where only causal packet arrival information is available. Inspired by the optimal offline solution, we propose a new online scheme. It is shown by simulations that the proposed online scheme has a comparable performance with the optimal offline one and outperforms the design without considering on-off circuit power as well as the other heuristically designed online schemes.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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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.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.289-301
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• 2019

Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.434-445
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• 2020

In this study, the minimization of harbor oscillation using permeable breakwater was applied to the actual harbor and investigated an effect of minimization by computer simulation in order to take into account the water quality problems and measures of harbor oscillation by infragravity waves at the same time. The study site is Mukho harbor located at East coast of Korea that harbor oscillation has been occurred frequently. The infragravity waves obtained by analyzing the observed field data for five years focused on the distribution between wave periods of 40 s and 70 s and wave heights in less than 0.1 m was 94% of analyzing data. The target wave periods was 68.0 s. The most effective method of minimization of harbor oscillation by infragravity waves was to install a detached permeable breakwater with transmission coefficient of 0.3 on the outside harbor and replace some area of the vertical wall in the harbor with wave energy dissipating structure to achieve a reflectivity of 0.9 or less. The amplitude reduction rate of this method shown in 27.4%. And the effect of the difference in transmission coefficient of permeable breakwater on the reduction rate of the amplitude was not significant.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.20-28
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• 2016

This paper presents a generation rescheduling method for the enhancement of transient stability in power systems. The priority and the candidate generators for rescheduling are calculated by using the energy margin sensitivity. The generation rescheduling formulates the Lagrangian function with the fuel cost and emission such as NO_x and SO_x from power plants. The generation rescheduling searches for the solution that minimizes the Lagrangian function by using the Newton’s approach. While the Pareto optimum in the fuel cost and emission minimization has a drawback of finding a number of non-dominated solutions, the proposed approach can explore the non-inferior solutions of the multiobjective optimization problem more efficiently. The method proposed is applied to a 4-machine 6-bus system to demonstrate its effectiveness.

• Journal of Energy Engineering
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• v.2 no.3
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• pp.276-284
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• 1993

This study is to obtain some basic data which are prerequisite for the conceptual design of gasification process based on entrained-bed type gasifier. The Gibbs free energy minimization method is used to analyze the chemical equilibrium in the gasifier. The modeling results which consider the conventional mass balance and heat balance are compared with the experimental data published by Electric Power Research Institute. The analysis shows that the reaction in a entrained-bed gasifier is influenced mainly by the amount of oxidant, by the temperature of gasifier and by the type of coals.