• Journal of Construction Engineering and Project Management
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• v.3 no.3
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• pp.23-34
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.375-385
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.1
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• pp.65-71
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• 2011

Since 2003, policies and practices related to the reduction of CO₂ gas emission from ships has been discussing by the International Maritime Organization. The representative emission index and indicator are the EEDI (Energy Efficiency Design Index) for the new ships and EEOI (Energy Efficiency Operational Indicator) during the voyage. For the CO₂ emission monitoring system, the SEEMP (Ship Energy Efficiency Management Plan) is also on the table. This global preparations to reduce theCO₂ emission is not except for the surface transportation. This research report elucidates the recent stream on the IMO CO₂ emission from ship and detail explanation on the EEDI and EEOI.

• Journal of Drive and Control
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• v.17 no.2
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• pp.38-44
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• 2020

Various efforts have been initiated to reduce the energy consumption of the compressor as it is one of the approaches to saving a large portion of the fixed cost of the production site. Various results of reducing the energy consumption of the compressor have been reported, but to reduce the energy consumption of the compressors fundamentally, regular management of the compressor should ensure optimum operation. This requires periodic on-site visits by experts, but is often overlooked as a cost issue, resulting in the use of the compressor in low-efficiency conditions. Thus, it is necessary to develop a low-cost evaluation technology for compressor condition monitoring and efficiency analysis to ensure that the compressor is always driven at the optimum efficiency without imposing undue burden on the compressor user. In this study, a sensor was installed at the inlet, outlet, and power supply of the compressor, and a method for evaluating the energy consumption of the compressor using the minimum sensor was derived. The experimental results are presented to show the validity of the proposed method. It was confirmed that the energy consumption of the compressor can be easily as well as efficiently evaluated by using the method developed in this study.

• Journal of the Korean Solar Energy Society
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• v.28 no.3
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• pp.15-20
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• 2008

Building-integrated photovoltaics(BIPV) are increasingly incorporated into new domestic and industrial buildings as a principal or ancillary source of electrical power, and are one of the fastest growing segments of the photovoltaic industry. This paper presents design, operational features analysis, and PCS(Power Conditioning System) of grid-connected 30kW BIPV set up on the library of Dongshin University. For a sustainable photovoltaics system in this area, the data of the BIPV system are collected and analyzed by monitoring system using LabView. PCS of the grid-connected BIPV system, also, is designed for optimal operation with characteristics suggested in this paper.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.E
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• pp.299-302
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• 1994

At a nuclear power plant, environmental radioactivity monitoring is routine work for the radiation safety management For the environmental monitoring of tritium($^3$H) activity in water sampled liquid scintillation counting( LSC) method is applied to measure low- energy beta activity from tritium in the samples. The $^3$H activity is measured using the BECKMAN 5801 system at the KRISS( Korea Research Institute of Standards and Science) for evaluating the lower limits of detection( LLD) of $^3$H measurement and the measuring capability of low-level $^3$H activity at four nuclear Power Plant sites. The LSC systems used for low-level $^3$H activity measurements at the nuclear Power Plants are confirmed to satisfy throughout an intercomparison study under the experimental arrangements by the KRISS.

• Smart Media Journal
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• v.3 no.2
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• pp.37-42
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• 2014

In this paper, the function design of smart media platform control with smart monitoring, and displaying modules which have the priorities of smart plug based smart outlet, is proposed for electrical suppliance of essential information appliance in emergency power consumption situation(blackout, peaktime etc). The effect of power management will be maximized by this smart gateway interlocking with ESS(energy storage system) which has bi-directional power transmission control modules, and smart outlet based on the priority control actions.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.279-286
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• 2013

This paper introduces a new method for identification of building energy performance problems. The presented method is based on automated analysis and visualization of deviations between actual and expected energy performance of the building using EPAR (Energy Performance Augmented Reality) models. For generating EPAR models, during building inspections, energy auditors collect a large number of digital and thermal imagery using a consumer-level single thermal camera that has a built-in digital lens. Based on a pipeline of image-based 3D reconstruction algorithms built on GPU and multi-core CPU architecture, 3D geometrical and thermal point cloud models of the building under inspection are automatically generated and integrated. Then, the resulting actual 3D spatio-thermal model and the expected energy performance model simulated using computational fluid dynamics (CFD) analysis are superimposed within an augmented reality environment. Based on the resulting EPAR models which jointly visualize the actual and expected energy performance of the building under inspection, two new algorithms are introduced for quick and reliable identification of potential performance problems: 1) 3D thermal mesh modeling using k-d trees and nearest neighbor searching to automate calculation of temperature deviations; and 2) automated visualization of performance deviations using a metaphor based on traffic light colors. The proposed EPAR v2.0 modeling method is validated on several interior locations of a residential building and an instructional facility. Our empirical observations show that the automated energy performance analysis using EPAR models enables performance deviations to be rapidly and accurately identified. The visualization of performance deviations in 3D enables auditors to easily identify potential building performance problems. Rather than manually analyzing thermal imagery, auditors can focus on other important tasks such as evaluating possible remedial alternatives.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.488-490
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• 2006

In the electric power industry, It is important that the supply of energy must always be guaranteed. To satisfy these requirements, various forms of technologies are needed, such as RFID tag, reader, sensor network, middleware and so on. WSN (Wireless Sensor Network) technologies of the electric power industry are in the early stage and there is no clear guideline for developing electric facility management system using WSN. Relevant experience is limited, the challenge will be to derive requirement from business practice and to determine whether it is possible or not. To explore this issue, we focus on researching and field test of prototype system in Korea Electric Power Corporation (KEPCO). In this paper we describe requirement from power industry. And we introduce design and implementation of the power facility monitoring system.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.259-268
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• 2016

KEPCO installed AMI (Advanced Metering Infrastructure) metering system for low-voltage customers from 2008. AMI metering system of KEPCO has operated 2.55 million customers and will plan to operate 22 million customers until 2020. KEPCO developed AMI NMS (Network Management System) to operate the meter reading network efficiently. NMS monitors the network status of DCUs (Data Concentration Unit) and modems. NMS provides functionalities of data collection and analysis. It collects property data of network device, network topology information, communication performance information, fault information, and etc. It analyzes collected data and controls network devices by remote access. AMI NMS collects about 370 MIBs (Mangement Information Bases) using SNMP (Simple Network Management Protocol). This paper introduces main functionalities, designed context, and implemented service screen.