• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.1-10
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• 2010

As processor platforms are continuously moving toward wireless mobile systems, embedded mobile processors are expected to perform more and more powerful, and therefore the development of an efficient power management algorithm for these battery-operated mobile and handheld systems has become a critical challenge. It is well known that a memory system is a main performance limiter in the processor point of view. Although many DVFS studies have been considered for the efficient utilization of limited battery resources, recent works do not explicitly show the interaction between the processor and the memory. In this research, to properly reflect short/long-term memory access patterns of the embedded workloads in wireless mobile processors, we propose a memory buffer utilization as a new index of DVFS level prediction. The simulation results show that our solution provides 5.86% energy saving compared to the existing DVFS policy in case of memory intensive applications, and it provides 3.60% energy saving on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1359-1375
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• 2015

Energy efficiency is critical for Wireless Sensor Networks (WSNs) since sensor nodes usually have very limited energy supply from battery. Sleep scheduling and nodes cooperation are two of the most efficient methods to achieve energy conservation in WSNs. In this paper, we propose an adaptive energy optimization approach for target tracking applications, called Energy-Efficient Node Coordination (EENC), which is based on the grid structure. EENC provides an unambiguous calculation and analysis for optimal the nodes cooperation theoretically. In EENC, the sleep schedule of sensor nodes is locally synchronized and globally unsynchronized. Locally in each grid, the sleep schedule of all nodes is synchronized by the grid head, while globally the sleep schedule of each grid is independent and is determined by the proposed scheme. For dynamic sleep scheduling in tracking state we propose a multi-level coordination algorithm to find an optimal nodes cooperation of the network to maximize the energy conservation while preserving the tracking performance. Experimental results show that EENC can achieve energy saving of at least 38.2% compared to state-of-the-art approaches.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.2
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• pp.1-6
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• 2005

This paper studies the OF-LED(Optical Fiber-LED) illuminated display board system for energy saving. The OF-LED illuminated display board system has PV module, batteries, charge 8t discharge system and dynamic full color display controller. Both maximum power point tracker (MPPT) and constant current & constant voltage controls (CCVC) are used to govern the charging system. This system. improves the charging efficiency of battery. The system is compact and operates only by PV except the rainy days when the sun is unfavorable. in the system display control and charging-discharging control by on-chip microprocessor are simultaneously carried out. To verify the unposed system, me simulation and experiment results show the operating characteristics with a laboratory prototype.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1339-1342
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• 2005

This paper presents a simple AC-DC power conditioner for a squirell-cage induction generator(IG) operating under variable shaft speeds. The necessary reactive power for the IG system is supplied by means of a capacitor bank and a voltage-source PWM converter. Using a capacitor bank to transfer the reactive power to the IG under the rated speed and no-load conditions starts the IG operation and reduces the PWM power converter size. A simple control compensating for changes in the electrical loads as well as the variation in speed was developed to regulate the voltages of the IG system by controlling the rotor flux through its reactive and active currents control implementation. This proposed power conditioning scheme can be used efficiently as a wind power generation system where the output voltage of the IG is maintained constant voltage despite the variable frequency and the DC bus voltage of the PWM converter can be used for either DC applications such as battery charging or AC power applications with 60/50 Hz by connecting a stand alone inverter. The experimental and simulated operating performance results of a 5 kW IG scheme at various speeds and leads are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.547-554
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• 2016

Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.84-92
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• 2006

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• Transactions of the Korean hydrogen and new energy society
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• v.16 no.4
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• pp.364-371
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• 2005

Fuel cell systems(FCS) have a financial and environmental advantage by providing electricity at a high efficiency and useful heat. For use in a residence, a polymer electrolyte fuel cell system(PEFCS) with a battery pack and a hot water storage tank has been modelled and simulated. The system is operated without connection to grid line. Its electric conversion efficiency and heat recovery performance are highly dependent on operation strategies and also on the seasonal thermal and electric load pattern. The output of the fuel cell is controlled stepwise as a function of the state of the battery and/or the storage water tank. In this study various operation strategies for cogeneration fuel cell systems are investigated. Average fuel saving rates at different seasons are calculated to find proper load management strategy. The scheme can be used to determine the optimal operating strategies of PEFCS for residential and building applications.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.765-770
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• 2008

This paper presents the power control for the hybrid electric propulsion system. In this paper, the hybrid propulsion system consists cf the generator and battery as power supply system in ship. The hybrid control system is designed with energy saving algorithm for decreasing the power consumption of power supply system. This paper suggests the method to increase efficiency of hybrid electric propulsion system by developing battery charging system. The performance of power control system is analyzed with the experiment equipment for hybrid propulsion system, and the results showed a good property.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.25-32
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 200 buildings that KEPCO headquarter and branch offices use. And K-BEMS system is composed of PV, battery, and hybrid PCS. KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. In this paper, the results of the project are shown. 9 modes of test results of K-BEMS system and are operational problems were analyzed. And measures to cure the trouble are also suggested. Batteries are operated more than 20% of SOC, and less than 20% of SOC battery protection switches are automatically shutting down the system and the system no longer respond to EMS, ending the supply of PV, and so therefore to continue the PV power supply it was turn out to be necessary that the EMS should automatically change its policy to change PV only supply mode automatically when the Battery Switch automatically operated. To operate the system continuously and automatically, it is necessary to modify the minimum operational SOC value, and in addition to that the EMS computer must remember the last shut-down SOC and Voltage which interrupted the system and add some margin to reflect the measurement error in the system.

• Journal of KIISE
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• v.41 no.10
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• pp.745-761
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• 2014

To address the problems of existing traffic information acquisition systems such as high cost and low scalability, wireless sensor networks (WSN)-based traffic information acquisition systems have been studied. WSN-based systems have many benefits including high scalability and low maintenance cost. Recently, various sensors are studied for traffic surveillance based on WSN, such as magnetic, acoustic, and accelerometer sensors. However, ultrasonic sensor based systems have not been studied. There are many issues for WSN-based systems, such as battery driven operation and low computing power. Thus, power saving methods and specific algorithms with low complexity are necessary. In this paper, we introduce optimal methodologies for power saving of ultrasonic sensors based on the modeling and analysis in detail. Moreover, a new vehicle detection algorithm for low complexity using ultrasonic data is presented. The proposed methodologies are implemented in a tiny microprocessor. The evaluation results show that our algorithm has high detection accuracy.