• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1416-1427
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• 2010

Except for some fields, Smart Grid-related technology in Korea is considered to be below the level of developed countries. Under this situation, this study is conducted to look into IT technology related to Smart Grid and draw prospective IT R&D fields in the Smart Grid Industry. To seek out prospective IT R&D fields, the two-stage process evaluating economics, political property, and technical validity. According to the result, four fields of (1) sensor, (2) information protection, (3) AMI middleware, (4) electricity management are selected as prospective fields. The sensor and AMI middleware fields focus on development of key technology, so the strategy that launches leading products in global market faster than other countries(Focusing & First Mover Strategy). The information protection felid is divided into the safety technology for the felid electricity network and the personal & corporate information protection technology, and therefore the R&D Sharing strategy is efficient. For the electricity management filed, a strategic alliance for developing component technology of Grid is desirable.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.217-229
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• 2016

Increased evidences reveal that the global climate change adversely affect on the environment. Smart grid system is one of the ways to reduce greenhouse gas emissions in the electricity generation sector. Since 2013, Korea Electric Power Corporation (KEPCO) has installed smart grid station in KEPCO office buildings. The goal of this paper is two folds. One is to quantify the reduction in greenhouse gas emissions through smart grid stations installed in KEPCO office buildings as a part of pilot project. Among components of smart grid stations, this research focused on the photovoltaic power system (PV) and energy storage system (ESS). The other is to estimate the reduction in greenhouse gas emissions when PV is applied on individual houses. Results show that greenhouse gas emissions reduce 5.8~11.3% of the emissions generated through the electricity usage after PV is applied in KEPCO office buildings. The greenhouse gas emissions reduction from ESS is not apparent. When PV of 200~500 W is installed in individual houses, annual greenhouse gas emission reduction in 2016 is expected to be approximately $2.2{\sim}5.4million\;tCO_2-eq$, equivalent to 6~15% of greenhouse gas emissions through the electricity usage in the house hold sector. The saving of annual electricity cost in the individual house through PV of 200 W and 500 W is expected to be 47~179 thous and KRW and 123~451 thousand KRW, respectively. Results analyzed in this study show the environmental effect of the smart grid station. In addition, the results can be further used as guidance in implementing similar projects.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.33-39
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• 2020

A smart grid is a next-generation power grid that can improve energy efficiency by applying information and communication technology to the general power grid. The smart grid makes it possible to exchange information about electricity production and consumption between electricity providers and consumers in real-time. Advanced metering infrastructure (AMI) is the core technology of the smart grid. The AMI provides two-way communication by installing a modem in an existing digital meter and typically include smart meters, data collection units, and meter data management systems. Because the AMI requires data collection units to control multiple smart meters, it is essential to ensure network availability under heavy network loads. If the load on the work done by the data collection unit is high, it is necessary to allocation new data collection units to ensure availability and improve energy efficiency. In this paper, we discuss the allocation scheme of data collection units for the energy efficiency of the AMI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.232-239
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• 2007

There is an increasing concern to interconnect DG(Distributed Generation) units into a distribution system and operate and maintain the system power quality within a proper level to distribution companies, regional electricity utilities and industrial customers. Recently, this situation makes many experts estimate a next generation of distribution system which is composed of some micro-grids. But the proposed micro-grid is only mentioned as a small grid with some DG units, some power quality compensators, communication and control equipments. In this paper, a topology and an operation/control algorithm of the micro-grid which is able to supply the electricity with high reliability and quality, are proposed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1390-1396
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• 2013

The paper estimated the reasonable market price of lead-acid battery energy storage system (BESS) intended for demand management of electricity customers. As time-of-use (TOU) tariffs have extended to a larger number of customers and gaps in the peak and off-peak rates have gradually risen, deployment of BESS has been highly needed. However, immature engineering techniques, lack of field experiences and high initial investment cost have been barriers to opening up ESS markets. This paper assessed electricity cost that BESS operation could save for customers and, based on the possible cost savings, estimated reasonable prices at which BESSs could become a more prospective option for demand management of customers. Battery scheduling was optimized to maximize the electricity cost savings that BESS would possibly achieve under TOU tariffs conditions. Basic economic factors such as payback period and return on investment were calculated to determine reasonable market prices. Actual load data of 12 industrial customers were used for case studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.7-14
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• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.21-28
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• 2013

The paper proposes an optimal sizing method of a customer's battery energy storage system (BESS) which aims at managing the electricity demand of the customer to minimize electricity cost under the time of use(TOU) pricing. Peak load limit of the customer and charging and discharging schedules of the BESS are optimized on annual basis to minimize annual electricity cost, which consists of peak load related basic cost and actual usage cost. The optimal scheduling is used to assess the maximum cost savings for all sets of candidate capacities of BESS. An optimal size of BESS is determined from the cost saving curves via capacity of BESS. Case study uses real data from an apartment-type factory customer and shows how the proposed method can be employed to optimally design the size of BESS for customer demand management.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.286-287
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• 2018

Recently, the development of renewable energy using solar energy is drawing attention. One of these PV systems, the Dual buck Inverter, is one of the topologies used in conjunction with the system, characterized by high efficiency and shoot-through reduction. However, current distortion appears severely in grid connection. So, in this paper, the method of compensation through PR controller was verified through simulation as an analysis of current distortion components and a control method to improve them.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.1-4
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• 2022

The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.67-72
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• 2022

There has been a significant growth in global population and industrialization, as a consequence demand for electricity is increasing rapidly and the power systems need to increase the electricity generation. Currently, most of generated electricity is generated from fossil fuels. However, there are many financial and environmental concerns associated with the generation of electricity from such resource. Photovoltaic )PV) solar as a renewable resource is promising. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. This paper attempts at reducing the burden and improving the accuracy of the extensive simulations related to integrating PV systems into the electrical grid.