• Proceedings of the KIEE Conference
• /
• 2000.11a
• /
• pp.58-60
• /
• 2000

In this paper we present an estimation method of electric energy[kWh] for load management of pole-transformer. For the electric energy estimation, we use the nonlinear load research based estimation(NLRE) algorithm. The NLRE curve is the normalized annual cumulative energy consumption for a particular day in a year. And, it is used for the coefficient estimation. Estimation method of suggested electric energy of pole-transformer used billing cycle electric energy estimation equation is verified as comparison billing cycle electric energy and estimated electric energy. We can reduce the error of peak load estimation by suggested method than the conventional method in domestic.

• KEPCO Journal on Electric Power and Energy
• /
• v.8 no.2
• /
• pp.127-135
• /
• 2022

With the advent of high technologies such as the 4th Industrial Revolution and artificial intelligence and big data, efforts are being made to solve urban problems and improve the quality of life by applying new technologies in the smart city field. In addition, as carbon neutrality has emerged as an important issue due to global warming, smart city energy platform technologies such as urban energy management, efficiency improvement, and carbon reduction are in the spotlight. In order to effectively manage urban energy, energy resource information such as electricity, water, gas, hot water, heating, etc. must be collected from the management system of various energy utilities and managed on the central platform. The centrally integrated data is delivered to external city management systems that require city energy information through an energy platform. This study developed a CIM profile for smart city energy monitoring required to provide energy data to external systems. Electric data model were designed using the CIM class of IEC 61970, and water, gas, and heat data model were designed in compliance with the UML-based design ideas of IEC 61970.

• Proceedings of the KSR Conference
• /
• 2002.10b
• /
• pp.1007-1012
• /
• 2002

In this paper, a regeneration inverter is proposed using 3-level inverter. Electric regeneration means regeneration brake in electric railway vehicles. Induction motors, generally used with railway vehicles, convert the electric energy to the movement energy when vehicle is running. When the vehicle stop, the induction motor convert the movement energy to the electric energy. Usually, this energy is used with another running vehicle in the same section. If there is no vehicle around when the regeneration is occurred, regeneration energy is consumed by heat energy with resistors. The proposed inverter is capable of reuse this regeneration energy in another place.

• KEPCO Journal on Electric Power and Energy
• /
• v.7 no.2
• /
• pp.301-307
• /
• 2021

After the spread of the data collection devices such as smart meters, energy data is increasingly collected in a variety of ways, and its importance continues to grow. However, due to technical or practical limitations, errors such as missing or outliers in the data occur during data collection process. Especially in the case of customer-related data, billing problems may occur, so energy companies are conducting various research to process such data. In addition, efforts are being made to create added value from data, which makes it difficult to provide such services unless reliability of data is guaranteed. In order to solve these challenges, this research analyzes prior research related to bad data processing specifically in the energy field, and propose new missing value processing methods to improve the reliability and field utilization of energy data.

• 한국초전도학회:학술대회논문집
• /
• v.12
• /
• pp.85-85
• /
• 2002

• New & Renewable Energy
• /
• v.19 no.1
• /
• pp.31-40
• /
• 2023

The expanding significance of energy storage (ES) technology is increasing the acceptability of power systems by augmenting renewable energy supply. To deploy such ES technologies, we must select the optimal technology that meets the requirements of the system and confirm the technical and economic feasibility of the business model based on it. Herein, we propose a method and tool for selecting the optimal ES technology suitable for meeting the requirements of the system, based on its performance characteristics. The method described in this study can be used to discover and apply various ES technologies and develop business models with excellent economic feasibility.

• KEPCO Journal on Electric Power and Energy
• /
• v.3 no.1
• /
• pp.57-63
• /
• 2017

This study aimed at proposing a RD&D good practice policy guidelines for energy technology innovation in electric power industry, we identified the success factors on energy RD&D through representative case analysis such as energy RD&D demonstration project and strategy plan, technology road map, etc. Based on a successful case study, we have identified the key elements needed to suggest when setting a RD&D technology innovation policy framework for technological competitiveness in the power industry sector. We have presented guidelines for energy technology innovation direction from the full cycle perspective of RD&D. The energy RD&D innovation system that we have established is meaningful in that the implications are derived and reflected through the case analysis of developed countries. The results of this study are as follows; Enhancement of R&D investment performance, commercialization of research achievements, promotion of export industrialization of electric power industry, establishment of RD&D governance system of power energy, etc.

• KIEAE Journal
• /
• v.10 no.1
• /
• pp.57-64
• /
• 2010

Electric energy is indispensible of the development of the industrial and living sector. Among the energy sectors, the building area shares 20% of the produced electric power in Korea. As we plan to supply the apartment, we need to forecast the required amount of the electric energy and supply the infrastructure to apartment for the lighting, cooling. Nonetheless, it is not easy to forecast the required amount of the electric energy, considering the management aspect, building physical aspect and social-geographic aspect. In this paper, it studied the estimation model of the electric energy, reflecting the affecting variables such as total area, number of household, geography and so on. The estimation model is proposed in 3-types which explained in central heating, individual heating and district heating, and each type have two estimation model, reflecting the affecting variable and corelation between variables to eliminate the muticolinearity. The unit of electric energy consumption per area and year is similar in three heating type and the results are as follows; the central heating is $34.446kWh/yr{\cdot}m^2$, individual type is $35.756446kWh/yr{\cdot}m^2$ and district heating is $34.285446kWh/yr{\cdot}m^2$.

• Journal of ILASS-Korea
• /
• v.29 no.1
• /
• pp.1-6
• /
• 2024

This paper is a numerical analysis study for evaluating the energy efficiency of electric vehicles. Currently, the methods for testing and evaluating the energy consumption efficiency of electric vehicles have limitations such as resources and time. Therefore, there is a need for research on developing models to predict the energy consumption efficiency of electric vehicles. In this study, a numerical analysis research is conducted to predict the energy efficiency of electric vehicles using a vehicle dynamics numerical analysis model. To validate the accuracy of the simulation model, it is compared the results of dynamometer tests with the simulation results and used the Unified Diagnostic Services (UDS) protocol to acquire internal data from the electric vehicle. It is ensured the reliability of the simulation model by comparing data such as motor speed, battery voltage, current, state of charge (SOC), regenerative braking power generation, and total driving distance of the test vehicle with dynamometer test data and simulation model results.

• Proceedings of the KIEE Conference
• /
• 1989.07a
• /
• pp.540-543
• /
• 1989