• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• Journal of Information Processing Systems
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• v.17 no.4
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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.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.18 no.1
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• pp.11-18
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• 2022

When wall-thinning in a pipe occurs during operation of nuclear power plant, reinforcement of the pipe needs to be performed. Accordingly, the structural response of the piping system due to introduction of the reinforcement may be re-evaluated. For elastic structural analysis of the piping system with the reinforced pipe using finite element (FE) analysis, the stiffness of the reinforced pipe is needed. In this study, the stiffness matrix of wall-thinned pipe with pad reinforcement or composite reinforcement is analytically derived. The validity of the proposed equations is checked by comparing with systematic finite element (FE) analysis results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.632-639
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• 2018

Recently, a policy has been enforced to supply Plug-in Electric Vehicles (PEVs) but this may require reinforcement of the power system depending on its clustering because PEVs are charged directly from power systems. On the other hand, as the reinforcement of power system is limited by time and budget, it is important to supply the charging demand of PEVs efficiently using the existing power systems to increase the diffusion of PEVs. This paper establishes a charging schedule for Plug-in Electric Vehicles (PEVs) considering the power system constraints. For this, the required amount and time of the charging demand for an individual PEV was modeled to integrate into power systems based on the driving pattern and charging tariff of PEV. Furthermore, the charging schedule of PEVs was established to meet the power system constraints by calculating the operating conditions of the power systems with PEVs.

• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.389-399
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• 2010

Available transfer capability (ATC) is a measure of the transfer capability remaining in a transmission system. Application of unified power flow controllers (UPFCs) could have positive impacts on the ATC of some paths while it might have a negative impact on the ATC of other paths. This paper presents an approach to evaluate the impacts of UPFCs on the ATC from a cost/worth point of view. The UPFC application worth is considered as the maximum cost saving in enhancing the ATC of the paths due to the UPFC implementation. The cost saving is considered as the cost of optimal application of other system reinforcement alternatives (except for UPFC) to reach the same ATC level obtained by UPFC application. UPFC application costs include the maximum cost of alleviating the probable negative impact on the ATC of some paths caused by implementing UPFCs. Optimal system reinforcement is used for systems with UPFCs to determine the aforementioned cost. The proposed method is applied to the IEEERTS and the results are evaluated through a sensitivity analysis. The cost/worth of UPFC application is also used to develop an index for optimal UPFC location and the results are compared with those of other indices. A comparison is finally made with the results obtained using an existing ATC allocation profit-based approach to determine UPFC application worth.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.30-32
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• 2006

New building, reinforcement, maintenance and test of power equipments are always necessary in a power system. Our power system is getting old and the total power capacity is also getting large, so power equipment outages are getting often. Power euipment outages make less margine for a stable condition of a power system operation. Therefore, through overviews and countermeasures against the outage should be made in order to be in a stable operational conditions during the outage. We have too many outages over 300 per month in our power system. So, we can't have enough time to study our power system and to make countermeasures without a helping program. This program is designed to give various and appropriate informations necessary for an outage scheduling. By applying this program, we can raise the job efficiency high and spare the time spent. So we can afford to do through system studies and make good countermeasures. I think this program can contribute greately to power system stable operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• Journal of Power System Engineering
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• v.19 no.1
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• pp.50-55
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• 2015

This study takes AC8A, which is a representative light weight alloy as matrix, and nickel as reinforcement for its superior properties. The manufacturing method applied in this study required low pressure for the infiltration of the metal matrix into the reinforcement. Porous Ni was applied as preform. The fabrication was conducted under 0.3 MPa at 600, 700 and 750 degrees centigrade, respectively. Intermetallic compounds Al3 generated between Al and Ni were observed in the composites. Microstructure, Vickers' hardness and wear characteristics of the composites were also investigated. The result indicates that the structures of compounds created at 650 degree centigrade were distributed densely; the grain size of the substances and the compounds was increased with the infiltration temperature.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.261-268
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• 2020

Genetic algorithms find the optimal solution by mimicking the evolution of natural organisms. In this study, the genetic algorithm was used to enable Pac-Man's reinforcement learning, and a simulator to observe the evolutionary process was implemented. The purpose of this paper is to reinforce the learning of the Pacman AI of the simulator, and utilize genetic algorithm and artificial neural network as the method. In particular, by building a low-power artificial neural network and applying it to a genetic algorithm, it was intended to increase the possibility of implementation in a low-power embedded system.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.04a
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• pp.657-662
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• 1997

In these day, there have been shortage of construction workers and an increase of labor cost in our county. In order to overcome these problems, prefabricated and mechanized system of bar placing have been used in the construction fields. As a part of this tendency, welded wire fabric(WWF) reinforcement were studied several years ago. In this study, the required working hour. the labor power and the construction process of WWF reinforcement for the apartment building slabs are reported. From the result of field investigations, it is showed that the WWF reinforcement facilitates the field placing and the working time of WWF placing is saved, and then the labor cost of WWF reinforcement is less than that of the conventional bar reinforcement.