• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.568-574
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• 2001

The variations of real time electric power price in competitive electricity markets have influence on electric power demands of the consumers. The effects of the consumers for electric power price can be expressed the price elasticity coefficient of the power demand as a measurement. Residential, commercial, and industrial consumers with different characteristics cause the different price elasticity of the power demand due to changing the pattern of consumption. It is necessary that the effects of electric power demands as a function of elasticity coefficient for each loads should be analyzed in Korea which is processing deregulated electric market. Therefore, this paper calculate the elasticity coefficient of each loads and analysis the effects of electric power demands as a function of elasticity coefficient of inflexible and flexible consumers in competitive electricity market.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.14 no.4
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• pp.1-6
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• 2018

In this study, the energy consumption of the typical floor was compared by the total energy comsumption of the building in highrise building. In gerneral, many researchers are studying on the typical floor in highrise buildings for avoiding complexity in energy simulation. But few papers are studied on energy consumption along the floors. In the model bulding, the energy consumption data were acquired by BEMS system in 2011. According the data, the total net energy consumption was $193.99kWh/m^2$ for all area and the total net energy consumption was $247.61kWh/m^2$ for HVACR area. The total electricity and gas energy are used 47.7% for heating and cooling, 33.5% for lighting and plug, 12.9% for conveyance power and 5.9% for restaurant. In comparison of only ground floor, amount of energy consumption in the lobby is 10%, and 90% of total energy consumption is used in the typical floor. For this result, energy simulation on the typical floor is acceptable for calculating the total energy consumption in the highrise building.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.1
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• pp.49-55
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• 2010

The objectives of this study are to analyze the energy independence plan and to propose a suitable sewage treatment plant in Korea. The total amount of electricity consumption for public sewage treatment plant was estimated as 1,812 GWh in 2007. It was estimated that total 16 sewage treatment plants with renewable energy systems produced electricity of 15 GWh per year, which could replace 0.8% of total electricity used for sewage treatment. It was found that domestic sewage treatment plants with power generation plants by digestion gas were installed in 7 places and produced electricity of 13 GWh per year. It was also found that the power generation plants by digestion gas were the most cost-effective for sewage treatment plant out of the renewable energy systems based on the benefit-cost analysis.

• Journal of the Korean Institute of Gas
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• v.17 no.1
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• pp.42-48
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• 2013

The global warming of the Korean Peninsula proceeds most rapidly in the world and its abnormal climate is more deepening. In the result of the surged electricity consumption by intense heat of summer and severe cold of winter, electricity supply and demand status is in hard situation. Currently, the supply of natural gas is increased because natural gas has the lowest greenhouse-gas emissions among the existed fossil fuel. Natural gas cooling has a lot of advantage such as decreasing electricity peak, reducing construction expenses in additional power plant, operating natural gas storage facilities efficiently, and playing a role as distributed generations. Therefore, this study analyzes the economic feasibilities of gas cooling as an alternative for electric power load management.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.121-129
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• 2009

Inspection of an Electrical Meter is an action of measuring power usage to charge electricity rates and Electricity AMR(Automatic Meter Reading) is a system to automatize the action. AMR has been highlighted because it can reduce metering cost by substituting an automatic system for personnel and strengthen customer service. In this paper, we proposed and developed a smart card based AMR framework SCEMS as an alternative to other current AMR Models. This proposed SCEMS uses a java card based multi-application smart card and supports customer service such as various meter rates according to electricity consumption pattern data per household and transaction data that are accumulated in a smart card. This research can be a solution to the problems such as diversity, heterogeneity, and complexity that environmental changes will cause soon to the power supply industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.123-129
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• 2014

This paper suggests that it provides a electricity management system for wasting electricity, from power demand growth environments. This Energy management system based on ICT(Information & Communication Technology) can control Smart Power Outlet connecting to this system with Web Browser and Android phone, anytime, anywhere. Through analysis of acquisition data from them, this proposed system can monitor and control power consumption efficiently. This system was organized mesh network of Smart Power Outlet, gateway by wireless Zigbee, and ESS(Energy Saving System) by TCP/IP beyond existing limit of communication distance and space.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.63-71
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• 2014

As power consumption increases, more power utilities are required to satisfy the demand and consequently results in tremendous cost to build the utilities. Another issue in construction of power utilities to meet the peak demand is an inefficiency caused by surplus power during non-peak time. Therefore, most power company considers power demand management with time-based electricity rate policy which applies different rate over time. This paper considers an optimal machine operation problem under the time-based electricity rates. In TOC (Theory of Constraints), the production capacities of all machines are limited to one of the bottleneck machine to minimize the WIP (work in process). In the situation, other machines except the bottleneck are able to stop their operations without any throughput loss of the whole manufacturing line for saving power utility cost. To consider this problem three integer programming models are introduced. The three models include (1) line shutdown, (2) block shutdown, and (3) individual machine shutdown. We demonstrate the effectiveness of the proposed IP models through diverse experiments, by comparing with a TOC-based machine operation planning considered as a current model.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.405-421
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• 2019

Predicting how much energy to use is an important issue in society. However, it is more difficult to capture the usage characteristics of residential buildings than other buildings. This paper provides time series analysis methods for electricity consumption in a residential building. Temperature is closely related to electricity demand. An error correction model, which is a method of adjusting the error with time, is applied when a cointegration relation is established between variables. Therefore, we analyze data via ECMs with consideration of the temperature effect.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.