• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.638-644
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• 2010

This paper presents ideas of service scenarios for home residents using electric power monitoring system per appliance, the implementation of the monitoring system, and analysis of acquired electric power usage pattern. By acquiring and analyzing electric power usage pattern, home residents can get information of power usage pattern of every legacy (non-Demand Response-ready) appliance. Further they can get pieces of recommendation how to reduce energy consumption, intelligent standby power blocking service, and alarming service to abnormality of appliances. In order to check the feasibility of the ideas, a system that can acquire electric power pattern per appliance is implemented, and electric power pattern of some appliances are stored to a database and it was analyzed to show if auto-identification of a type of a device is possible, which is a basic required function for the scenarios presented.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.9
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• pp.604-612
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• 2012

Self-management plan for GHG (Greenhouse Gas) reduction should be prepared in academic facilities, which occupy a large amount of energy consumption. In this study, a university was chosen as one of the major academic facilities and its energy consuming pattern and GHG emission were analyzed. The results have shown that annual $CO_2$ emission from university buildings was 10,452 ton-$CO_2$ (0.65 ton-$CO_2/m^2$), and dependent upon 78.0% electricity, 20.5% LNG and 1.5% oil, respectively as energy sources. According to more detail analysis by usage of energy consumption, appliances occupies 36.7% followed by gas heating (18.9%), lighting (18.6%), heating with electricity (12.5%), cooling with electricity (10.2%), transportation (1.5%), gas cooling (1.2%) and cooking (0.4%). Furthermore, annual $CO_2$ emissions per unit area and a student by electricity usage were evaluated to 51.30 kg-$CO_2/m^2$ and 981.86 kg-$CO_2$/capita, respectively and those by LNG usage were 14.61 kg-$CO_2/m^2$ and 241.01 kg-$CO_2$/capita.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.4
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• pp.65-74
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• 2010

This study is for Hanbuk Mountain Range within Gyeonggi province which is to propose the conservation plan by each damage pattern through site survey of the mountain range. The damage patterns are classified by siding, pointing and lining. The total damaged area is 103 areas: The siding pattern is damaged by developing farmland, mineral and quarry mining, dam, large scale development complex and cemetery park; The pointing pattern is including the development of road, transmission tower and way and mountaineering trail; The construction of electricity and communication facility, military facility, mobile communication station, heliport and shelter. The damages by developing road and large scale development complex are the most cause, and military facility, dam and reservoir, and residential area are the main causes, respectively. One of the compromised situation Hanbuk-Mountain Range usage as per section 7 section (18.45%), 12 section (18.45%) is the largest number of compromised has been surveyed, undermine the situation if you look at the usage by the road 25 locations (24.22%), military facilities and dam and reservoir to undermine this 11 established respectively (10.68%) were the most undermine. Therefore, this research propose the conservation plan as follow: first, need to understand, educate and publicize on Hanbuk-Mounatin Range; second, manage through the regulations and ordinance of Gyeonggi province; third build and expand the law for protecting Baekdu-Great Mountain Range.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.300-306
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• 2011

In this paper, we suggest a usage profiles for electric home appliances. In Korea, it is published the records for total consumption of electricity in a house but the electric home appliance consumption records in a households are not. To build the data, we must collect the usage of every appliances in a house and the information of the household which live in the house. Unfortunately, it is hard to get the data because of the worry about the breach of privacy. In this paper, we make a scenarios on the electricity consumption pattern of a few households type. Based on the conjecture, we make the power consumption profiles for some home appliances. Comparison to the total electric consumption records for a house, we found our scenarios are quite reasonable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.13-20
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• 2020

One of the major issues surrounding big data is the availability of massive time-based or telemetry data. Now, the appearance of low cost capture and storage devices has become possible to get very detailed time data to be used for further analysis. Thus, we can use these time data to get more knowledge about the underlying system or to predict future events with higher accuracy. In particular, it is very important to define custom tailored contract offers for many households and businesses having smart meter records and predict the future electricity usage to protect the electricity companies from power shortage or power surplus. It is required to identify a few groups with common electricity behavior to make it worth the creation of customized contract offers. This study suggests big data transformation as a side effect and clustering technique to understand the electricity usage pattern by using the open data related to smart meter and KNIME which is an open source platform for data analytics, providing a user-friendly graphical workbench for the entire analysis process. While the big data components are not open source, they are also available for a trial if required. After importing, cleaning and transforming the smart meter big data, it is possible to interpret each meter data in terms of electricity usage behavior through a dynamic time warping method.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.68-77
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• 2018

Regarding demand response (DR) by residential users (R-users), the users try to reduce electricity costs by adjusting their power consumption in response to the time-varying price. However, their power consumption may be affected not only by the price, but also by user convenience for using appliances. This paper proposes a methodology for appliance scheduling (AS) that considers the user convenience based on historical data. The usage pattern for appliances is first modeled applying the copula function or clustering method to evaluate user convenience. As the modeling results, the comfort distribution or representative scenarios are obtained, and then used to formulate a discomfort index (DI) to assess the degree of the user convenience. An AS optimization problem is formulated in terms of cost and DI. In the case study, various AS tasks are performed depending on the weights for cost and DI. The results show that user convenience has significant impacts on AS. The proposed methodology can contribute to induce more DR participation from R-users by reflecting properly user convenience to AS problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.407-413
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• 2011

This paper presents an electrical power monitoring system for home energy management and an automatic appliance-identification algorithm based on the electricity-usage patterns collected during the monitoring tests. This paper also discusses the results of the field tests of which the proposed system was voluntarily deployed at 13 homes. The proposed monitoring system periodically measures the amount of power consumption of each appliance with a pre-specified time interval and effectively displays the essential information provided by the monitored data which is required users to know in order to save power consumption. Regarding the field tests of the monitoring system, the households responded that the system was useful in saving electricity and especially the electricity-usage patterns per appliances. They also considered that the predicted amount of the monthly power consumption was effective. The proposed appliance-identification algorithm uses 4 patterns: Zero-Crossing Rate(ZC), Variation of On State(VO), Slope of On State(SO) and Duty Cycle(DC), which are applied over the 2 hour interval with 25% of it on state, and it yielded 82.1% of success rate in identifying 5 kinds of appliances: refrigerator, TV, electric rice-cooker, kimchi-refrigerator and washing machine.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.9-15
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• 2010

Recently, Smart Grid is a emerging topic in power and communication industry. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. In order to successful implementation of Smart Grid, energy management function will be the key factor that coordinates and optimally controls the various loads according to the operating condition and environments, and the load patterns in residential and commercial building will be required as fundamental element for load management. In this study, we collects many types of energy usage data of electric appliances, analyze their load curves, and make the general load patterns for electrical appliance.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.279-283
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• 2009

Distributed generation(DG) of combined cooling, heat. and power(CCHP)has been gaining momentum in recent year as efficient, secure alternative for meeting increasing energy demands. This paper presents the energy performance of microturbine CCHP system equipped with an absorption chiller by modelling it in hospital building. The orders of study were as following. 1)The list and schedule of energy consumption equipment in hospital were examined such as heating and cooling machine, light etc. 2) Annual report of energy usage and monitoring data were examined as heating, cooling, DHW, lighting, etc. 3) The weather data in 2007 was used for simulation and was arranged by meteorological office data in Daejeon. 4) Reference simulation model was built by comparison of real energy consumption and simulation result by TRNSYS and ESP-r. The energy consumption pattern of building were analyzed by simulation model and energy reduction rate were calculated over the cogeneration. As a result of this study, power generation efficiency of turbine was about 30% after installing micro gas turbine and lighting energy as well as total electricity consumption can be reduced by 40%. If electricity energy and waste heat in turbine are used, 56% of heating energy and 67% of cooling energy can be reduced respectively, and total system efficiency can be increased up to 70%.