• IE interfaces
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• v.25 no.4
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• pp.441-449
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• 2012

Solar PV(photovoltaic) is paid great attention to as a possible renewable energy source to overcome recent global energy crisis. However to be a viable alternative energy source compared with fossil fuel, its market competitiveness should be attained. Grid parity is one of effective measure of market competitiveness of renewable energy. In this paper, we forecast the grid parity timing of solar PV energy in Korea using two factor learning curve model. Two factors considered in the present model are production capacity and technological improvement. As a result, it is forecasted that the grid parity will be achieved in 2019 in Korea.

• 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.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.202-208
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• 2008

The objectives of this study are to collect the population of each cooling system for gas and electric driven systems, and propose sample design for five cooling systems; ice storage systems, system air-conditioning system, turbo system as electric driven cooling systems, and absorption system and Gas driven Heat Pump (GHP) system as gas driven cooling systems. The sample design are carried out based on types of business, capacity, installation region and year. This study proposes criterion of the sample design for cooling systems for each energy source.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.389-393
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• 1987

This paper describes the configuration of serial interconnection BUS, BitBUS, for Energy Management Systems, and it provides low cost, high performance approach in distributed data acquisition and control applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.351-360
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• 2016

Rapid population growth with high living standards and high electronics use for personal comfort has raised the electricity demand exponentially. To fulfill this elevated demand, conventional energy sources are shifting towards low production cost and long term usable alternative energy sources. Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to advancement in renewable energy technologies and subsequent rise in prices of petroleum products. Wind and solar power are considered feasible replacement to fossil fuels as the prediction of the fuel shortage in the near future, forced all operators involved in energy production to explore this new and clean source of power. Presented paper proposes fuzzy logic based Energy Management System (EMS) for Wind Turbine (WT), Photo Voltaic (PV) and Diesel Generator (DG) hybrid micro-grid configuration. Battery backup system is introduced for worst environmental conditions or high load demands. Dump load along with dump load controller is implemented for over voltage and over speed protection. Fuzzy logic based supervisory control system performs the power flow control between different scenarios such as battery charging, battery backup, dump load activation and DG backup in most intellectual way.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.2
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• pp.34-41
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• 2017

The Pyro project, one of the large national R&D project to construct Korea Advanced Pyroprocessing Facility (KAPF), which has many goals such as development of pyro technology and process equipment, design of equipment and facility, construction, and test operation, is now under research and development. To reduce uncertainty and risk of such complex project, the technical management processes in systems engineering standards and NASA handbook were reviewed, and then the ten common technical management processes were selected for the large national R&D project to meet its goal successfully. And the essential technical management processes were finally suggested for Pyro project in consideration of current situation of the project.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.949-966
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• 2013

Recently, Wireless Body Area Network (WBAN) has promise to revolutionize human daily life. The need for multiple sensors and constant monitoring lead these systems to be energy hungry and expensive with short operating lifetimes. In this paper, we offer a review of existing work of WBAN and focus on energy-aware management in it. We emphasize that nodes computation, wireless communication, topology deployment and energy scavenging are main domains for making a long-lived WBAN. We study the popular power management technique Dynamic Voltage and Frequency Scaling (DVFS) and identify the impact of slack time in Dynamic Power Management (DPM), and finally propose an enhanced dynamic power management method to schedule scaled jobs at slack time with the goal of saving energy and keeping system reliability. Theoretical and experimental evaluations exhibit the effectiveness and efficiency of the proposed method.

• Atmosphere
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• v.34 no.1
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Knowledge Management Research
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• v.9 no.4
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• pp.51-63
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• 2008

Effective energy consumption now becomes one of the area of knowledge management which potentially gives global impact. It is considerable for the energy management to optimize the usage of energy, rather than decreasing energy consumption at any cases. To resolve these challenges, an intelligent and personalized system which helps the individuals control their own behaviors in an optimal and timely manner is needed. So far, however, since the legacy energy management systems are nation-wide or organizational, individual-level energy management is nearly impossible. Moreover, most estimating methods of energy consumption are based on forecasting techniques which tend to risky or analysis models which may not be provided in a timely manner. Hence, the purpose of this paper is to propose a novel individual-level energy management system which aims to realize timely and personalized energy management based on context-aware computing approach. To do so, an index model for energy consumption is proposed with a corresponding service framework.