• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 추계학술대회 논문집 전력기술부문
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• pp.243-245
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• 2007

There are some rebate programs for energy efficient appliances, which are lightings, vending machines, ASDs, motors, transformers, pumps, to reduce national energy consumption in Korea. Among these appliances, motors are of the essential target in the programs because these take about 64% of electrical energy consumption nationally. In this paper reasonable rebate levels are proposed using an advanced diffusion model and avoided cost analyses.

• 자원ㆍ환경경제연구
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• 제22권3호
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• pp.547-580
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• 2013

상품 및 서비스 소비구조의 변경을 통해 에너지절약이 실현될 수 있기 때문에 가정부문의 간접 및 총 에너지소비를 추정할 필요가 있다. 가정부문의 직간접 에너지소비를 보다 정확히 추정하기 위해 본 연구는 기업과 소비자(가정부문) 간 석유제품 및 전력의 가격을 차별화하였다. 한국의 가정부문은 1995-2010년 기간 중 한국 1차 에너지소비 중 55% 이상을 소비하였다. 가정부문의 에너지소비 중 69% 이상이 간접 에너지소비였다. 따라서 가정부문의 직접뿐만 아니라 간접 에너지소비도 에너지절약의 대상이 되어야 한다. 전력 소비는 2009년 한국의 가정부문의 주 에너지소비가 되었다. 생활수준이 향상됨으로써 가정부문은 전력 원단위가 높은 상품과 서비스를 소비하게 되었다. 한국 가정부문이 소비하는 제품의 에너지 원단위가 낮아짐으로써, 에너지소비의 증가율이 감소하게 되었다. 반면에 한국 가정부문의 상품 및 서비스 소비구조는 에너지 다소비형으로 변경되어 오히려 에너지소비 증가를 가속시키는 결과를 초래함으로써, 구조효과는 악화되었다. 이에 따라 에너지정책은 에너지소비를 감소시키기 위해 소비자로 하여금 에너지 저소비형 재화와 용역을 소비하도록 유도하여야 한다. 에너지 저소비형 소비를 촉진시킬 수 있는 주요 수단인 에너지가격 현실화가 요구된다.

• 한국주거학회:학술대회논문집
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• 한국주거학회 2006년도 추계학술발표대회 논문집
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• pp.328-333
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• 2006

A few methodologies have been recently developed to estimate the environmental affect when various materials and components are used in building life cycle. The direct survey method has limitations to analyze the environmental problems because of the limit of survey scope and cost. Therefore, another indirect method has been developed as alternatives. The indirect method is represented as input-output analysis. This paper aimed at analyzing the estimation the environmental affect of building materials and works at building construction, utilizing the input-output analysis as a indirect estimation method. The results suggested that the building works is overally responsible for the energy consumption and $CO_2$ emission. In other words, Over the 80% of the total consumption and $CO_2$ emission are resulted at the building work.

• ETRI Journal
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• 제30권1호
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• 전기학회논문지
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• 제59권6호
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• pp.1046-1052
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• 2010

In residential house, photovoltaic (PV) system among various alternatives in renewable energy system is the most efficient and feasible solution for reducing energy consumption and electricity cost. However, relatively high initial cost make people reluctant to install PV system in their houses. Therefore, in the initial state for PV system installation in the house, it is very important to decide proper capacity of the PV system considering the expected energy usage and solar energy supplying condition with the house. This paper proposes a novel optimization model for deciding appropriate capacity of the PV system for residential house. The objective function of the model is to minimize the annual cost including electricity bill, operation and maintenance cost, and annual fixed cost calculated from the initial installation cost based on capital recovery factor (CRF). The model also shows the optimal inclining angle of PV panels of the system. In this paper, we estimate the PV output using PVWATTS (PV simulator of Office of Energy Efficiency and Renewable Energy) and find optimal solutions by Sequential Quadratic Programming (SQP) method using MATLAB software. The proposed approach is finally applied to a residential model house in Gangneung, Gangwon-Do and verified its feasibility for adopting to PV system design for residential houses.

• 설비공학논문집
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• 제13권3호
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• pp.200-208
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• 2001

In indoor temperature control of a heat pump, a reduction in energy consumption is very important. However, most control schemes for heat pumps have focused only on control performance such s settling time and steady-state error. In this paper, the model predictive control (MPC) which includes the energy-related variable in this cost function is proposed. By computing the control signal minimizing this cost function, the trade-off between energy reduction and temperature control performance can be obtained. Since the MPC required the process model, the dynamic mode of a heat pump is also obtained by the system identification technique. Performance of the proposed MPC considering energy efficiency is compared with the two other control schemes. It si shown that the proposed scheme can consume less energy thant hte others in achieving similar control performance.

• 토지주택연구
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• 제10권3호
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• pp.9-16
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• 2019

This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• 에너지공학
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• 제26권4호
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• pp.127-142
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• 2017

2014.7월 유연탄 개별소비세 부과 이후 고열량탄 및 기준 구간내 상위 열량탄 선호 현상 등 사용량 왜곡 현상이 나타나 평균 도입열량 상승으로 추가적인 연료도입 비용이 발생하였다. 이에 따라 고열량탄 위주의 호주/러시아탄 비중이 확대된 반면 중,저열량탄 위주의 인도네시아탄 비중이 축소되었다. 이는 유연탄의 특성 반영이 미흡한 과세 제도에 따라 나타난 현상으로 사용량 왜곡 뿐 아니라 해외자원 개발 동기부여 저해, 연소기술 개발 차질 등의 문제가 있어 이를 해결 하기 위한 개선 방안이 필요할 것이다. 적정 세수를 유지하면서 사용량 왜곡을 해소할 수 있는 개선방안으로 5,000kcal/kg 기준열량 비례 부과방식과 5,000kcal/kg 기준 열량 세액단가와 동일한 상하 200kcal/kg 단위 총 15 구간 세분화 부과방식이 있으며 이를 통해 사용량 왜곡 현상 해소는 물론 세수증대와 연료도입 비용 절감의 효과가 있을 것으로 예상한다.

• 설비공학논문집
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• 제26권4호
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• pp.145-150
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• 2014

Many studies are being conducted with the aim of reducing the energy consumption in data centers, which are one of the highest consumers of energy. The use of an air-side economizer system that uses external air during intermediate and winter seasons is being considered for reducing the energy consumption of air conditioners. In this study, using the energy simulation, we evaluated the energy performance of a central chilled water cooling system and air-side economizer system in domestic data centers. Further, the cost-effectiveness of the air-side economizer was analyzed through Life-Cycle Cost Analysis. The results showed that with the use of air-side economizer systems, the energy costs increased as the applied filter grade increased; however, unlike existing central chilled water systems, it would break even within 2 years.