• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.96-99
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• 2003

As for the Elect-CAD, it was developed a design of the electricity equipment which did manually, a quotation, all kinds of bill writing in the program that Package anger became. Elect-CAD can easily write an estimate back by all kinds of bill writing and estimatic with a design at the same time, and maximization gets an efficiency of work done and can efficiently manage project, and it is a revolutionary program in a management plane.

• KIEAE Journal
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• v.15 no.6
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• pp.5-10
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• 2015

Purpose: To evaluate the economic performance of grid-connected photovoltaic system in residential house, household electricity bill policy of Korea Electric Power Corporation (KEPCO) must be applied precisely, and market tendency and uncertainty of system also need to be considered. In this study, to evaluate the economic feasibility of PV system, we measured PV power generation and electricity consumption of six of Green home in Daejeon through web based remote monitoring system. Method: We applied Monte-Carlo simulation based on life cycle cost analysis, to reflect an uncertainty of main factor in economic feasibility evaluation of photovoltaic system. Result: First, with deterministic analysis, the difference of NPV of cumulative financial savings among households varied from -3,310 ~ 24,170 thousand won, portraying notably big range. Also the possibility of getting the same result was 50% when applying uncertainty. Second, the higher electricity consumption is, the more economic feasibility of photovoltaic system increases because KEPCO uses progressive taxation in household electricity bill policy. Third, The contribution to variance of electricity price increases in NPV varied from 98.5% to 99.9%. While the inflation rate and annual degradation contributed very little to none.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1256-1262
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• 2016

As the population of camping is increased in campsites and auto camp sites, the electrical equipment can safely supply electricity to users in a variety of electricity bill policy is required in the campsite. In this paper, we develop the vending machine for electricity that can control the outdoor electrical outlet from the management server using the Z-Wave WPAN and android mobile application. The developed vending machine for electricity consists of the management server, the controller, the outdoor outlet box, and the mobile application. The management server provides reservation and electricity bill payment to users. The management server controls the electrical outlet box through the controller to safely supply electricity to users. The controller that is a relay device between the management server and the switch controls switches based on Z-Wave mesh network. Outdoor electrical outlet box has 2 meter switches. We receive the relevant authorization to provide commercial electricity services using the outdoor electrical outlet box in the campsite.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.9
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• pp.20-27
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• 2014

The power consumption pattern of high-speed railway has rarely during night time. But, during service time, the power is consumed irregularly related to train operation. Especially certain unusual about 1-2 days of service time interval to indicate the power consumption is rapidly growing phenomenon, which causes the capacity of the power contract is the annual electricity bill to rise rapidly as the cause. Normally, amount of peak power consumption bill rate at railway substation is over 20% of total electrical bill. Therefore, high-speed railway substation is expected to be considerably larger savings by reducing the peak power of the default charge(demand power).

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.10
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• pp.381-386
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• 2016

An optimization algorithm is developed based on a simulation case of a single family house model equipped with PV arrays. To increase the nationwide use of PV power generation facilities, a market-competitive electricity price needs to be introduced, which is determined based on the time of use. In this study, quadratic programming optimization was applied to minimize the electricity bill while maintaining the indoor temperature within allowable error bounds. For optimization, it is assumed that the weather and electricity demand are predicted. An EnergyPlus-based house model was approximated by using an equivalent RC circuit model for application as a linear constraint to the optimization. Based on the RC model, model predictive control was applied to the management of the cooling load and electricity for the first week of August. The result shows that more than 25% of electricity consumed for cooling can be saved by allowing excursions of temperature error within an affordable range. In addition, profit can be made by reselling electricity to the main grid energy supplier during peak hours.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.159-168
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• 2020

Current residential electricity rates, which are charged regardless of consumption patterns, have a problem of restricting consumer choice. In order to improve the problem, the Korea government started a demonstration project based on Time-Of-Use(TOU) pricing from September 2019. However, the analysis of its effect is still limited. This study analyzed the changes and limitations of TOU pricing compared to the current progressive pricing. The result showed that the high rate payer's bill decreased by up to 33.8 % while the low rate payer's bill increased by up to 117.7 %. This can lead to the problem of accepting electricity rates from a social point of view. In this study, TOU pricing based on progressive pricing was proposed to overcome the problem. The results presented the rate changes depending on the power consumption patterns while decreasing the average rate change from 32 % to -1.9 %. It means that the proposed pricing can support the TOU effect while maintaining the framework of the existing progressive pricing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1278-1285
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• 2018

For saving electricity bill, energy storage system(ESS) is being installed in factories, public building and commercial building with a Time-of-Use(TOU) tariff which consists of demand charge(KRW/kW) and energy charge(KRW/kWh). However, both of peak reduction and ESS special tariff are not considered in an analysis of initial cost payback period(ICPP) on ESS. Since it is difficult to reflect base rate by an amount of uncertain peak demand reduction during mid-peak and on-peak periods in the future days. Therefore, the ICPP on ESS can be increased. Based on this background, this paper presents the advanced analysis method for the ICPP on ESS. In the proposed algorithm, the representative days of monthly electricity consumption pattern for the amount of peak reduction can be found by the k­means clustering algorithm. Moreover, the total expected energy costs of representative days are minimized by optimal daily ESS operation considering both peak reduction and the special tariff through a mixed-integer linear programming(MILP). And then, the amount of peak reduction becomes a value that the sum of the expected energy costs for 12 months is maximum. The annual benefit cost is decided by the amount of annual peak reduction. Two simulation cases are considered in this study, which one only considers the special tariff and another considers both of the special tariff and amount of peak reduction. The ICPP in the proposed method is shortened by 18 months compared to the conventional method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.12
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• pp.103-107
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• 2014

Together with housings, general buildings and industrial facilities, multi-purpose complexes are equipped with various and special equipment. They are often used by many unspecified people, which causes an increase in annual electricity consumption. Because of this, a great amount of money has been spent for electric charge, far more in excess of the budget, so a reasonable electricity rate needs to be estimated. In this study, we surveyed the power consumption, average power use, and annual electricity bill of multi-purpose complexes in the past five years. To see the general tendency of the survey, we conducted a statistical analysis with such parameters as average, maximum, and minimum values. Through regression analysis, we could see the trend of the survey in linear way. Based on the survey, we have developed an electric-rate calculation program to estimate the next year's budget on electricity.

• 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 Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.284-291
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• 2018

As environmental pollution has become worse green technologies to replace or reduce consumption of fossil fuel get spotlight from government, industry and academia globally. It is reported that 40% of carbon dioxide emission is caused by electricity power generation. And 37% of end user electricity power is used by residential costumer in US. Smart Grid is considered as one of promising technology to alleviate severe environmental problem. In residential environment, Home Energy Management System (HEMS) can play a key role for green smart home. The HEMS can give several benefits like aslowering electric utility bill, improvement of efficiency of electric power consumption and integration of generator using renewable energy resources. However just limited functions of HEMS can be used for residential customer in real life because of lack of smart function in home appliances and optimal managing software for HEMS. This study provides comprehensive analysis for Home Energy Management System for residential customer. Simple HEMS system with real products on the market are explained and limitation of current HEMS are also discussed.