• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.486_487
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• 2009

This paper presents a method for optimal operation to improve reliability of MicroGrid systems considering load types and interruption cost. The objective functions such as power losses cost, operation cost of dispersed generations, power purchasing cost, and interruption cost are minimized for reliability improvement and efficient operation. The several indices for reliability evaluation are improved by renewable energy sources installation.

• 대한건축학회논문집:계획계
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• 제34권11호
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• pp.45-55
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• 2018

To reduce the energy consumption of HVAC system in buildings, thermally activated building system(TABS) has been applied to low energy building because of energy efficient performance and reduction of peak load. DOAS coupled with a parallel sensible cooling could be promising because TABS handles sensible heat load only. The purpose of this study was to evaluate the indoor thermal environment and cooling operation characteristic of TABS with dedicated outdoor air system(DOAS) in Korea climate. Indoor thermal environment and operation characteristic of TABS integrated with DOAS are investigated at different TABS operation schedules and climate conditions by simulation tests. The result shows that the DOAS is more suitable for hot and humid climates. And also it show that the potential of intermittent operation of TABS.

• 한국물환경학회지
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• 제32권2호
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• pp.191-196
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• 2016

This study aimed to evaluate SBR operation cycle for removing the high-concentration organic matter of distillery wastewater in the ginseng processing plant. The experiment was conducted with the use of a laboratory scale SBR reactor and distillery wastewater as the influent. The results indicated an increase in pH from 4.08 to 7.59 of distillery wastewater after aeration for 2 hours. Also, the optimum SBR operation cycle for the removal of organic matter and nitrogen was 2 hr of aeration and 6 hr of anaerobic conditions. Adjustment of proper pH through aeration time is most critical in the SBR operation for distillery wastewater treatment. In this study, we presented an efficient method for distillery wastewater treatment.

• 한국수소및신에너지학회논문집
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• 제33권5호
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• pp.591-597
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• 2022

Recently, technologies for efficient power grid operation have become important due to climate change. For this reason, predicting power demand using deep learning is being considered, and it is necessary to understand the influence of characteristics of each region, industrial structure, and climate. This study analyzed the power demand of New Jersey in US, with a high urbanization rate and a large service industry, and West Virginia in US, a low urbanization rate and a large coal, energy, and chemical industries. Using recurrent neural network algorithm, the power demand from January 2020 to August 2022 was learned, and the daily and weekly power demand was predicted. In addition, the power grid operation based on the power demand forecast was discussed. Unlike previous studies that have focused on the deep learning algorithm itself, this study analyzes the regional power demand characteristics and deep learning algorithm application, and power grid operation strategy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.140-144
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• 1988

This paper describes requirements for cogenerating in parallel with utility. Cogenerating is the simultaneous generation of energy in two or more forms, usally electricity and heat. Cogeneration is most energy efficient when generating in paralled will the electric utility, but requires proper control and protection. When onsite generation and utility systems are operated in parallel, there are many factors. such as operation mode. point of connection, grounding, synchronizalion. protective relaying, metering, and the like, that must be considered to provide safe and efficient operation.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1068-1075
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• 2021

Wireless sensor network (WSN) can be usefully used in battlefields requiring rapid installation and operation by enabling surveillance and reconnaissance using small sensors in areas where any existing network infrastructure is not formed. As WSN uses battery, energy efficiency acts as a very important issue in network survivability. Layer-based routing protocols have been studied a lot in the aspect of energy efficiency. Many research selected LEACH and PEGASIS protocols as their comparison targets. This study examines the two protocols and LECEEP, a protocol designed by combining their advantages, and proposes a new protocol, A-LECEEP, which is more energy efficient than the others. The proposed protocol can increase energy efficiency compared to the existing ones by eliminating unnecessary transmissions with multiple chains configuration.

• Journal of Semiconductor Engineering
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• 제2권2호
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• pp.130-135
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• 2021

Recently, deep neural networks (DNNs) are actively used for action control so that an autonomous system, such as the robot, can perform human-like behaviors and operations. Unlike recognition tasks, the real-time operation is essential in action control, and it is too slow to use remote learning on a server communicating through a network. New learning techniques, such as reinforcement learning (RL), are needed to determine and select the correct robot behavior locally. In this paper, we propose an energy-efficient DNN processor with a LUT-based processing engine and near-zero skipper. A CNN-based facial emotion recognition and an RNN-based emotional dialogue generation model is integrated for natural HRI system and tested with the proposed processor. It supports 1b to 16b variable weight bit precision with and 57.6% and 28.5% lower energy consumption than conventional MAC arithmetic units for 1b and 16b weight precision. Also, the near-zero skipper reduces 36% of MAC operation and consumes 28% lower energy consumption for facial emotion recognition tasks. Implemented in 65nm CMOS process, the proposed processor occupies 1784×1784 um2 areas and dissipates 0.28 mW and 34.4 mW at 1fps and 30fps facial emotion recognition tasks.

• 한국수소및신에너지학회논문집
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• 제34권6호
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• pp.641-649
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• 2023

This study analyzes the cool-down process of liquid hydrogen storage tanks, which have advantages in terms of large-capacity transfer, storage, and utilization as hydrogen demand increases. A hydrogen liquefaction plant is selected for analysis and an efficient tank cooling method is sought by comparing the time required for the cool-down process with the gas consumption in connection with the gassing-up process required for the operation of the liquid hydrogen storage tank. The results of this study can be referred to in the operation process after the initial start-up and maintenance of the hydrogen liquefaction plant.

• 유기물자원화
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• 제23권3호
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• pp.11-22
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• 2015

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.305-312
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• 2014

This paper discusses real-time peak shaving algorithms for a large-scale battery energy storage system (BESS). Although several transmission and distribution functions could be implemented for diverse purposes in BESS applications, this paper focuses on a real-time peak shaving algorithm for an energy time shift, considering wind power generation. In a high wind penetration environment, the effective load levels obtained by subtracting the wind generation from the load time series at each long-term cycle time unit are needed for efficient peak shaving. However, errors can exist in the forecast load and wind generation levels, and the real-time peak shaving operation might require a method for wind generation that includes comparatively large forecasting errors. To effectively deal with the errors of wind generation forecasting, this paper proposes a real-time peak shaving algorithm for threshold value-based peak shaving that considers fuzzy wind power generation.