• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.3
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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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.10
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• pp.733-738
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• 2012

It is important issue to reduce the electric energy to save the operating cost of HVAC system. Even if electrical energy is the clean energy, it is difficult and takes high cost for storage of electricity. These cause the high peak load of electric energy for HVAC in summer season. In korea, government impose the electric charge with several grade for the purpose of cut-off the peak load of electricity. Government has a policy to support to design and install the heat/ice storage system using midnight electricity. In this study, analysis of cooling load and operating characteristics for ice storage system are performed. And, also economical efficiency is compared between ordinary charge system of electricity and midnight rate charge of electricity. The systematic and economical supports are needed for expansion of usage of energy saving equipments.

• ETRI Journal
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• v.43 no.3
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• pp.427-435
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• 2021

Data filtering is an essential task for improving the energy efficiency of radiofrequency identification (RFID) networks. Among various energy-efficient approaches, clustering-based data filtering is considered to be the most effective solution because data from cluster members can be filtered at cluster heads before being sent to base stations. However, this approach quickly depletes the energy of cluster heads. Furthermore, most previous studies have assumed that readers are fixed and interrogate mobile tags in a workspace. However, there are several applications in which readers are mobile and interrogate fixed tags in a specific area. This article proposes a model for dynamic clustering-based data filtering (DCDF) in mobile RFID networks, where mobile readers are re-clustered periodically and the cluster head role is rotated among the members of each cluster. Simulation results show that DCDF is effective in terms of balancing energy consumption among readers and prolonging the lifetime of the mobile RFID networks.

• Journal of the Korean Institute of Gas
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• v.13 no.5
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• pp.1-6
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• 2009

This paper presents the fuel consumption effects of LPG vehicle depending on the atmospheric temperature, LP gas leakage of vaporizer, viscosity of engine oil and engine load conditions. The fuel consumption test results show that when the temperature of engine temperature rises, the fuel consumption efficiency increases in general. The fuel consumption efficiency for an atmosphere temperature of $24.2^{\circ}C$ is 13.6% high compared to that of $1^{\circ}C$. No leak vaporizer on fuel consumption efficiency is 5.3% high compared to that of the LP gas leak vaporizer. The fuel economy of new engine oils is just 1.1% high compared to that of used oils with a LPG vehicle mileage of 9,500km. This is not an influential factor compared with an atmospheric temperature and a LP gas leakage. The more important factors on the fuel consumption efficiency are driving conditions such as a rapid braking, abrupt start and fast acceleration. The test results indicate that the normal start is 32.3% high compared to that of an abrupt start and the fast acceleration is 10.8% high compared with that of an abrupt start. And the fuel consumption efficiency for a rapid braking is 18.3% higher than that of an abrupt start. These indicate that the driving condition is very important to reduce the fuel consumption rate.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.693-700
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• 2024

As of the end of March 2022, the total area of domestic industrial complexes is 606 km2, which is only about 0.6% of the total land area. However, as of 2018, the annual energy consumption of domestic industrial complexes is 110,866.1 thousand TOE, accounting for 53.5% of the country's total energy consumption and 83.1% of the entire industrial sector energy consumption. In addition, industrial complexes have a significant impact on the environment, accounting for 45.1% of the country's total greenhouse gas emissions and 76.8% of industrial sector greenhouse gas emissions. Under this background, in this study, in order to contribute to the energy efficiency of industrial complexes, a prediction study on energy demand and supply for an industrial complex in Korea using machine learning was conducted. In addition, a simulator UI screen was designed to more efficiently convey information on energy demand/supply prediction results and energy consumption status. Among the machine learning algorithms, Multi-Layer Perceptron (MLP) was used, and Bayesian Optimization was applied as an optimization technique for the prediction model. The energy prediction model for the industrial complex built in this study showed a prediction accuracy of 87.90% for compressed air demand and 99.54% for the flow rate available for the public air compressor.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.3 no.2
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• pp.25-30
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• 2007

The final energy consumption in the building sector in Korea represents almost 20% of the total energy consumption. Besides, Space heating and hot water generation in Korea are based on fossil fuels, with a serious environmental impact. This study describes thermal performance of heating demonstration system using close-loop ground source heat pump installed at Korean minjok leadership academy. The results of the experimental study, it retrieve the investment cost for 3years 8months and reduction amount of $CO_2$are 293,900 $kgCO_2$.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.19-24
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• 2014

Many people all over the world have been conducting a great deal of research to solve the problem of global warming since the great majority consider reduction of CO2 as the only solution for that. That is why the production and conservation of energy is thought to be highly crucial. while it is important to produce energy with the high efficiency, the efficient use of the energy is also important. This paper focused on the development of devices for the reducing electricity which is a primary energy source used in homes, shops, buildings, factories and so on. Also the objective of this paper is to develop the inference mechanism as the core component of the devices. Therefore, in this paper, we propose the inference algorithm for reducing the electricity consumption using SARIMA mode and present the feasibility of the procedure.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.3
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• pp.29-36
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• 2003

Reducing the energy consumption while maintaining pulp quality is an important objective of today's paper industry. Enzymatic treatment of fibers and the application of dry strength agent were investigated as methods to reduce energy consumption during refining and to upgrade fiber characteristics. Modification of recycled fibers with an enzyme was effective in improving relining efficiency and reducing refining energy. Optimization of dry strength agent application conditions including stock pH, cationic demand, zeta potential, etc. were found to be very important for improving its effectiveness.

• Journal of the Korean Solar Energy Society
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• v.32 no.1
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• pp.56-66
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• 2012

This study evaluated the economic benefits by comparing Cooling-Heating System with the existing system in the public library. The building's annual energy consumption was measured by adding the figures of the absorber chillers, the air conditioners and heaters in the building. The total amount of annual energy consumption was 143.51RT in air-conditioning and 83.66RT in heating. So, We made the capacity of geothermal heat pumps three 50RTs in order to check up this system. In order to estimate each construction and equipment cost and to evaluate economical efficiency, LCC(Life Cycle Cost) method was used and the service life of the building was sixty years. The result of analysis was that the geothermal cooling-heating system was more efficient than the existing system in public library.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.19-26
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• 2018

One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don't need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.