• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1039-1046
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• 2017

Campus microgrid is designed and built by considering not only power generation but also power consumption management as connected microgrid type because the main goal of the campus microgrid is to save power consumption costs. There are many functions to achieve the goal and they are mainly to use generation-based functions such as islanding operation for peak management and for emergency events. In power distribution operation, Conservation Voltage Reduction (CVR) is applied in order to reduce power consumption. The CVR is defined as a function for load consumption reduction by voltage reduction in order to reduce peak demands and energy consumption. However, application of CVR to microgrid is difficult because the microgrid cannot control a tap of transformer in a substation and the microgrid normally is not designed with phase modifying equipment like a step-voltage-regulator which can control voltage in power distribution system operation. In addition, an impact of the CVR is depended on load characteristics such as a normal load, a rated power, and synchronous motors. Therefore, this paper proposes an application of CVR using linear voltage control based AVR in campus microgrid with power consumption reduction considering characteristics of load and component in the microgrid. The proposed system can be applied to each buildings by a configuration of power distribution cables; and the application results and CVR factor are presented in this paper.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.67-77
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• 2017

Demands for housing has diversified recently due to low birth rate and the growth of aging population. Also, a share of idle houses and obsolete houses over 20 years old is gradually rising. Therefore, there is a need for a sustainable, environment-friendly improvement policy that is in line with a new housing paradigm and avoids full-scale new construction, such as a customized housing renovation plan considering local economic circumstances. Therefore, afforestation system applicable to buildings are assessed positively, but lack objective performance evaluation. Through one-year, long-term monitoring of replicated obsolete buildings that have poor insulation performance, this study calculated monthly average power consumption and analyzed power charges by applying pricing plans before and after the revision of progressive tax in order to examine economic effects expected by applying the afforestation system. In the obsolete buildings, the study showed that monthly average power consumption was reduced by 16.6kWh with 5.2% average reduction rate. Highest reduction was made in July at 11.3%. Aggregate monthly power consumption charges were relatively high in winter before and after the revision of progressive tax. Power charges reduction effect was highest in March when monthly power consumption was reduced to 300kWh level by applying the afforestation system.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.991-994
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• 2016

This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.292-300
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• 2013

Nowadays, energy saving has become a hot topic and information and communication technology has become a major power consumer. In long term evolution advanced (LTE-A) networks, heterogeneous deployments of low-power nodes and conventional macrocells provide some new features, such as coverage extension, throughput enhancement, and load balancing. However, a large-scale deployment of low-power nodes brings substantial energy consumption and interference problems. In this paper, we propose a novel switching strategy (NS), which adaptively switches on or off some low-power nodes based on the instantaneous load of the system. It is compatible with the microcells' load balancing feature and can be easily implemented on the basis of existing LTE-A specifications. Moreover, we develop an analytical model for analyzing the performance of system energy consumption, block rate, throughput, and energy efficiency. The performance of NS is evaluated by comparison with existing strategies. Theoretical analysis and simulation results show that NS not only has a low block rate, but also achieves a high energy efficiency.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.99-104
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• 2011

It has to take quantitative energy usage of high school education facilities in nations to set goals of their energy reduction. Therefore, The purpose of this study is to present various analysis result of energy consumption that is a statistic alanalysis of high school education facilities in Korea to set the goal of energy saving. This study has enforced analysis and has provided used energy for the year 2008 and general information from 2022 high school education facilities in 16 cities in South Korea by the relevant agency. Used energy sources in high school education facilities are electricity, gas for heating, oil, coal, water, and this study has changed the various used energy sources as unit 'kWh' only for comparison and analysis them.

• Journal of IKEEE
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• v.13 no.1
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• pp.71-76
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• 2009

As one of the most important requirements for wireless sensor networks, prolonging network lifetime can be realized by minimizing energy consumption in cluster heads as well as sensor nodes. While most of the previous researches have focused on the energy of sensor nodes, we devote our attention to cluster heads because they are most dominant source of power consumption in the cluster-based sensor networks. Therefore, we seek to minimize energy consumption by minimizing the maximum(MINMAX) energy dissipation at each cluster heads. This work requires energy-efficient clustering of the sensor nodes while satisfying given energy constraints. In this paper, we present a constraint satisfaction modeling of cluster-based routing in a heterogeneous sensor networks because mixed integer programming cannot provide solutions to this MINMAX problem. Computational experiments show that substantial energy savings can be obtained with the MINMAX algorithm in comparison with a minimum total energy(MTE) strategy.

• ETRI Journal
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• v.44 no.6
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• pp.885-902
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• 2022

The mmWave cell-free massive MIMO (CFmMIMO), combining the advantages of wide bandwidth in the mmWave frequency band and the high- and uniform-spectral efficiency of CFmMIMO, has recently emerged as one of the enabling technologies for 6G. In this paper, we propose a novel framework for energy-efficient mmWave CFmMIMO systems that uses low-resolution digital-analog converters (DACs) and phase shifters (PSs) to introduce lowcomplexity hybrid precoding. Additionally, we propose a heuristic pilot allocation scheme that makes the best effort to slash some interference from copilot users. The simulation results show that the proposed hybrid precoding and pilot allocation scheme outperforms the existing schemes. Furthermore, we reveal the relationship between the energy and spectral efficiencies for the proposed mmWave CFmMIMO system by modeling the whole network power consumption and observe that the introduction of low-resolution DACs and PSs is effective in increasing the energy efficiency by compromising the spectral efficiency and the network power consumption.

• Journal of the Korean housing association
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• v.23 no.6
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• pp.31-38
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• 2012

In this paper, we draws tendency of the electricity consumption in residential buildings according to inhabitants Composition types and the level of incomes. it is necessary to reduce energy cost and keep energy security through the electricity demand forecasting and management technology. Progressive social change such as increases of single household, the aging of society, increases in the income level will replace the existing residential electricity demand pattern. However, Only with conventional methods that using only the energy consumption per-unit area are based on Energy final consumption data can not respond to those social and environmental change. To develop electricity demand estimation model that can cope flexibly to changes in the social and environmental, In this paper researches propensity of electricity consumption according to the type of residents configuration, the level of income. First, we typed form of inhabitants in residential that existed in Korea. after that we calculated hourly electricity consumption for each type through National Time-Use Survey performed at the National Statistical Office with considering overlapping behavior. Household appliances and retention standards according to income level is also considered.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.17-25
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• 2023

As the range of use of urban unmanned aerial vehicles (UAV) expands, it is necessary to operate UAVs efficiently because of its limited battery capacity. For this, it is required to find the optimal flight profile with various simulations. Therefore, it is important to predict the power and energy consumption of the UAV battery. In this paper, we analyzed the relationship between the speed and acceleration of the UAV and power consumption during the flight. Then, we derived a linear model, which is easily utilized. In addition, we also derived an accurate power consumption model based on deep neural network learning. To find the efficient model, we used learning data as 1) the GPS 3-axis velocity and acceleration data, 2) the IMU 3-axis velocity only, and 3) the IMU 3-axis velocity and acceleration data. The final model shows 5.86% error rate for power consumption and 1.50% error rate for the cumulative energy consumption.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.84-93
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• 2017

This study was carried out to improve the electric power consumption of HVAC in the blow mold machine(BMM) and work environment. The experiment was conducted with the simulated HVAC system of 1/15 of the actual BMM. The temperature of main facility and two preheaters was fixed at 200 and $60^{\circ}C$ respectively in all test conditions. The measured points of temperature were chosen as critical locations considering the work environment. The tendency of temperature distributions decreases as the duct was closed to the main facility. The reduction rate of power consumption of HVAC increases up to 32.3% when both duct and cooling systems are operated. Also the efficiency of HVAC is improved about 9% through the modified design of duct system. It notes that the electric power consumption of HVAC can be reduced by the optimum design and operating condition of duct and cooling system.