• KIEAE Journal
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• v.17 no.3
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• pp.75-81
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• 2017

Purpose: The energy consumption of apartment units is affected by the lifestyle of the residents rather than system technology. In this study the numerical analysis of assumed energy consumption correlation factors with arbitrary value due to uncertainty. It is intended to be used as a simulation correction value which can be utilized as a predicted value of actual energy usage. The correction value of the simulation is set in the developed form of the existing process that derives the actual usage amount. The simulation results used in the existing evaluation system are used to maintain the useful value as the current system evaluation scale and predict the actual capacity. Method: The method of the study is to statistically analyze the data frames of all complexes capable of collecting the annual energy usage and to reconstruct the population by adding the variables that are expected to be correlated. Repeat the data frame configuration with variables that are assumed to be highly correlated with energy use levels. Determine whether there is correlation or not. The intensity of the external characteristics of the building equipment related to the energy consumption is presented as the quantitative value. Result: The correlation between electricity consumption and trading price since 2010 is analyzed as (Correlation coefficient 0.82). These results are higher than (Correlation coefficient 0.79), which is the correlation between residential area and trading price. This paper signifies the starting point of the methodology that broadens the field of view of verification of simulation feasibility limited to the prediction technique focused on the simulation tool and the element technology scope.The diversified phenomenon reproduction method develops the existing energy simulation method.It can be completed with a simulation methodology that can infer actual energy consumption.

• Asian Journal of Business Environment
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• v.4 no.2
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• pp.17-21
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• 2014

Purpose - The paper analyzes basic indicators characterizing the volume of energy sector activity in the Russian Federation, Privolzhsky Federal district, Republic of Tatarstan. Research design, data, and methodology - The study analyzed data from the Privolzhsky Federal district, specifically, industrial production volume, electricity production, energy consumption, energy-balance data, capital investments, and capital investment structure. An array of data has been investigated in recent years. The dataset's dynamics were analyzed in 1998. Fixed capital investment dynamics were studied in 1946 the figures were converted to a comparable form using the index method. Trends were analyzed using multivariate statistics methods and the Statgraphics software package. Results - Hypothesis 1. There are sectoral disproportions in energy flows,taking into account the volume of electricity production and consumption. Trends in electricity production in general coincide with industrial production volume trends. Energy flows have disparities in individual territorial units, and in general. Hypothesis 2. The degree of sectoral economic stability decreases with insufficient levels of investment in fixed capital energy organizations. Conclusions - Because totalelectricity production is largely determined by fixed capital investments, the study of their trends and patterns will coordinate efforts on investment operations in this area.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.79-88
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• 2017

One of the important applications of activity sensing in the home is energy monitoring. Many previous methodologies for detecting and recognizing household appliances have been proposed. This paper presents an approach that uses an energy metering circuit (EMC) to classify and identify the various electrical devices in home based on root-mean-square (RMS) consumed current value. EMC gathers the RMS current values created by appliance state transition (e.g., on to off) and apparatus operating process. In this paper, an identification algorithm is proposed to detect a change in current levels using the standard deviation of current signals and their average values. In addition, characteristic of the appliance is extracted concerning four feature parameters concerning the number of current levels, the minimum level, the maximum level, and signal-to-noise ratio (SNR) of them. Experiment results validate the reliable performance of the proposed identification method for 11 representative appliances.

• Journal of the Korean Wood Science and Technology
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• v.36 no.6
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• pp.41-48
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• 2008

The required energy for the heat treatment of pine log was evaluated in this study. A proper heat treatment of pine log infected by pinewood nematode (Bursaphelenchus xylophilus) can prevent spreading of the infection by pinewood nematode and make the infected pinewood valuable again. The FAO (Food and Agriculture Organization of the United Nations) heat treatment standard for various types of infected wood for which a heat treatment of the core part of the wood is necessary is 30 minutes at $56^{\circ}C$, taking into account the international standards for phytosanitary measures (ISPM No. 15). In this study, the energy consumption during the heat treatment was separated into two kinds of energy, initial energy for heating kiln drier and to reach set point temperature and relative humidity and the required energy supplementing heat loss. The initial required energy per unit time is greater than that during the treatment. The energy consumption per unit time varied little during the heat treatment. As a result, the set point relative humidity with set dry bulb temperature and density of wood dependent on moisture content are very important factors to change energy consumption in the experiment. The heat treatment at higher temperature and higher humidity levels requires more energy consumption but less treatment time. It is expected that a more effective energy program could be planed for the heat treatment of pine log through this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4781-4803
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• 2017

Environmental monitoring systems using Wireless Sensor Networks (WSNs) face the challenge of high power consumption, due to the high levels of multi-hop data communication involved. In order to overcome the issue of fast energy depletion, a proof-of-concept implementation proves that adopting a clustering algorithm in environmental monitoring applications will significantly reduce the total power consumption for environment sensor nodes. In this paper, an energy-efficient WSN-based environmental monitoring system is proposed and implemented, using eight sensor nodes deployed over an area of $1km^2$, which took place in the city of Tabuk in Saudi Arabia. The effectiveness of the proposed environmental monitoring system has been demonstrated through adopting a number of real experimental studies.

• Proceedings of the KIEE Conference
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• 2007.11b
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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.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.1088-1090
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• 1993

This paper shows efficient peak demand control method in office buildings. With a rapid growth of national economics and living standard, electrical energy consumption markedly increased. Expecially, it is increased electrical energy comsumption in the office buildings and thus an energy conservation through efficient use of electricity became more important. From the data of electric equipment capacity and electric power consumption for 96 buildings, current levels of demand factor and a growth trend of peak loads by office buildings were surveyed and analyzed. In addition the efficient peak demand control method in office buildings were studied.

• Journal of the Korean Wood Science and Technology
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• v.35 no.6
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• pp.50-56
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• 2007

FAO standard for heat sterilization of wood, International standards for phytosanitary measures (ISPM) No.15, must meet heat-treated wood core temperature to be higher than $56^{\circ}C$ and keep the temperature for more than 30 minutes. This study was carried out to analyze the heat treatment characteristics of domestic pinewood sterilized with the FAO standard. To enhance the effectiveness of heat treatment process in mountainous district energy consumption and time required to reach target temperature were evaluated at various temperature and relative humidity conditions and moisture contents of wood. Heat-treatment of high temperature and high humidity reduced the required heating time. Lower humidity levels at same temperature reduced energy consumption per unit time. However, lower humidity levels could not reduce total energy consumption greatly because longer treatment time was required at that condition. It is necessary to estimate energy consumption and predict treatment time in dynamic heating and cooling situations, because it frequently happens not to meet optimum treatment condition due to poor surrounding climates and operation performance of heat treatment facility in real field.

• Journal of Community Nutrition
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• v.6 no.2
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• pp.61-66
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• 2004

This study was performed to investigate the nutritional status associated with alcohol consumption in Korean adults men and women. The data was derived from the 2001 Korean National Health and Nutrition Survey. The number of subjects included were 6090 (Men: 2789, Women: 3031) aged 20 (equation omitted) < 65y. Men consuming moderate alcohol ((equation omitted) 24 g/day but < 48g/day) had higher intakes of energy and vitamin B groups than the ones consuming less than 24g/day. Heavy drinking men reporting more than 48g alcohol/day were observed as having 3207.2kcal of energy intake (130% of Korean RDA) and significantly elevated levels in most of the nutrients. For women drinkers, when the alcohol consumption was moderate ((equation omitted) 12g/day but 24g/day) or heavy((equation omitted) 36g/day) the energy intake was 2188.9kcal(100% of RDA) or 2627.5kcal (130% of RDA). The other nutrients protein, fat, calcium, iron and vitamin B group were also higher in women with heavy alcohol consumption. Heavy drinking women showed significantly higher weight, BMI and HDL-C. In contrast, heavy drinking men did not show any significant difference in BMI but showed significantly elevated blood pressure, HDL-C and lower serum cholesterol.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.408-417
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• 2022

Although traditionally perceived as being a visualization and asset management resource, the relatively rapid rate of improvement of computing power, coupled with the proliferation of cloud and edge computing and the IoT has seen the expanded functionality of modern Digital Twins (DTs). These technologies, when applied to buildings, are now providing users with the ability to analyse and predict their energy consumption, implement building controls and identify faults quickly and efficiently, while preserving acceptable comfort and well-being levels. Furthermore, when these building DTs are linked together to form a community DT, entirely new and novel energy management techniques, such as demand side management, demand response, flexibility and local energy markets can be unlocked and analysed in detail, creating circularity in the economy and making ordinary building occupants active participants in the energy market. Through the EU Horizon 2020 funded TwinERGY project, three different levels of DT (consumer - building - community) are being created to support the creation of local energy markets while optimising building performance for real-time occupant preferences and requirements for their building and community. The aim of this research work is to demonstrate the development of this new, interrelated, multi-level DT that can be used as a decision-making tool, helping to determine optimal scenarios simultaneously at consumer, building and community level, while enhancing and successfully supporting the community's management plan implementation.