• ETRI Journal
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• v.45 no.4
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• pp.650-665
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• 2023

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time were obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and bidirectional long short-term memory network, was applied to the smart metering technique. Power management based on the smart metering technique was executed by multi-objective optimization in the presence of a battery storage system and an electric vehicle. The results of the power management employing the proposed smart metering technique indicate a reduction in electricity cost and amount of power supplied by the grid compared to the results of power management without anomaly detection.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.79-88
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• 2012

Power continues to be a driving force in central processing units (CPU) design. Most of the advanced breakthroughs in power have been in a realm that is applicable to workstation CPUs. Advanced power management systems will manage temperature, dynamic voltage scaling and dynamic frequency scaling in a CPU. The use of power management systems for microcontrollers and embedded CPUs has been modest, and mostly focuses on very large scale integration (VLSI) level optimizations compared to system level optimizations. In this paper, a dynamic frequency controlling (DFC) technique is introduced, to lay the foundation of a system level power management system for commercial microcontrollers. The DFC technique allows a commercial microcontroller to have minor modifications on both the hardware and software side, to allow the clock frequency to change to save power; results in this study show a 10% savings. By adding an additional layer of software abstraction at the interrupt level, the microcontroller can operate without having knowledge of the current clock frequency, and this can be accomplished without having to use an embedded operating system.

• ETRI Journal
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• v.33 no.6
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• pp.973-976
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• 2011

This letter describes an efficient technique for maximum power point tracking (MPPT) of an energy harvesting device. It is based on controlling the device voltage at the point of maximum power. Using a microcontroller with a power saving technique, the MPPT algorithm maintains the maximum power with low power consumption. An experiment shows that the algorithm maximizes the energy transfer power using an energy management IC fabricated in a 0.18-${\mu}m$ process. Compared to direct energy transfer to a battery, the proposed technique is more efficient for low-energy harvesting under variable conditions.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.50-54
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• 2009

In this paper, we address a novel system-level power management technique which is specifically targeted for an ARM 11 MPCore system. Our proposed solution is a DPM technique which includes process monitoring, real time power analysis, and policy application to reduce the power consumption while meeting the performance requirement. One of the main contributions of this paper is that we systematically infer QoS requirements of processes without getting any additional information from the application. When multiple processes are running under various user level policies, priorities of the policy application are determined in such a way that the overall system performance is maintained while power consumption is effectively managed. Experimental results show that our DPM technique is very effective in reducing power consumption without violating system's QoS requirements.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.1965-1970
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• 2016

This paper studies generator rescheduling technique for congestion management in power system with wind farms. The proposed technique is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion subject to operational line overloading. The generator rescheduling method has been used with incorporation of wind farms in the power system. The locations of wind farms are selected based upon power transfer distribution factor (PTDF). Because all generators in the system do not need to participate in congestion management, the rescheduling has been done by generator selection based on the proposed generator sensitivity factor (GSF). The selected generators have been rescheduled using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed methodology has been analyzed on IEEE 14-bus systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.170-176
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• 2009

The efficiently power management is an important requirement traditionally in the mobile communication system which uses battery as their power source. Especially, it has been emphasized in the most devices, which has to provide high performance and various functions with an extended operating time. In this article, the adaptive power management technique for the core CPU unit in Embedded systems used widely for the mobile system thanks to its advantage on power consumption and physical size, is proposed.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1119-1120
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• 2008

The efficiently power management is an important requirement traditionally in the mobile communication system which uses battery as their power source. Especially, it has been emphasized in the most recent devices, which has to provide high performance and various functions with an extended operating time. In this article, the adaptive power management technique for the core processor unit in embedded systems used widely for the mobile system thanks to its advantage on power consumption and physical size, is proposed.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.484-492
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• 2016

Smart grid (SG) technology is now elevating the conventional power grid system to one that functions more cooperatively, responsively, and economically. When applied in an SG the demand side management (DSM) technique can improve its reliability by dynamically changing electricity consumption or rescheduling it. In this paper, we propose a new SG scheduling scheme that uses the DSM technique. To achieve effective SG management, we adopt a mixed pricing strategy based on the Rubinstein-Stahl bargaining game and a repeated game model. The proposed game-based pricing strategy provides energy routing for effective energy sharing and allows consumers to make informed decisions regarding their power consumption. Our approach can encourage consumers to schedule their power consumption profiles independently while minimizing their payment and the peak-to-average ratio (PAR). Through a simulation study, it is demonstrated that the proposed scheme can obtain a better performance than other existing schemes in terms of power consumption, price, average payment, etc.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.3
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• pp.123-128
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• 2017

Electric utilities has been considered the necessity to introduce AM(asset management) of electric power facilities in order to reduce maintenance cost of existing facilities and to maximize profit. In order to make decisions in terms of repairs and replacements for power transformers, not only measuring by counting parts and labor costs, but comprehensive comparison including reliability and cost is needed. Therefore, this study is modeling input cost for power transformer during its entire life and also the life cycle cost (LCC) technique is applied. In particular, this paper presents an application of heuristic harmony search(HS) optimization algorithm to the convergence and the validity of economic life assessment of power transformer from LCC technique. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through an economic life assessment simulation of power transformer using HS optimization algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.891-897
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• 2009

This paper presents a novel load management technique that can lower the peak demand caused by package airconditioner loads in large apartment complex. An intelligent hierarchical load management system composed of a Central Intelligent Management System(CIMS) and multiple Local Intelligent Management Systems(LIMS) is proposed to implement the proposed technique. Once the required amount of the power reduction is set, CIMS issues tokens, which can be used by each LIMS as a right to turn on the airconditioner. CIMS creates and maintains a queue for fair and proper allocation of the tokens among the LIMS requesting tokens. By adjusting the number tokens and queue management policies, desired power reduction can be achieved smoothly. The Markov Birth and Death process and the Balance Equations utilizing the Diffusion Model are employed for evaluation of queue performances during transient periods until the static balances among the states are achieved. The proposed technique is tested using a summer load data of a large apartment complex and give promising results demonstrating the usability in load management while minimizing the customer inconveniences.