• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.59-64
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• 2016

This paper aims at the prototype-making of the intelligent switchgear with arc fault diagnosis function required to prevent the electrical fire. The main control unit of the intelligent switchgear consists of a single-phase power management device and a arc fault diagnosis device. The prototype of the single-phase power management device and the prototype of the arc fault diagnosis device in this paper. In the device, the cooperation function with the arc fault diagnosis device is developed to transmit the cause of the electrical fire to the remote server system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.442-446
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• 2015

As electricity consumption is increasing rapidly these days, an urgent. need exists to minimize consumption through smart and intelligent ways in order to prevent a future energy crisis. For this purpose, development of an intelligent peak power management system should be required. As the number of appliances and consumer electrical devices increase, power consumption in unit business tends to grow. Generally, electricity consumption can be minimized using a peak power management system capable of. effectively controlling the load power by continuously monitoring the power. In this work, a peak power management system which consists of arduino microprocessor equipped with ethernet and Zigbee shield is presented. To verify the feasibility of the proposed scheme, laboratory-scale experiments are carried out.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.19-29
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• 2019

Recently, with the rise of environmental issues and the change of government policy (Renewable Energy 3020 Implementation Plan), a large amount of renewable energy such as solar and wind power is connected to the power system, and most of the renewable energy is concentrated in the power distribution network. This causes many problems with the voltage management and the protection coordination of the grid due to the its intermittent power generation. In order to effectively operate the distribution network, it is necessary to deploy more intelligent terminal devices in the field to measure the status of the distribution network and develop various operation functions such as visualization and big data analysis to support the power distribution system operators. In addition, the failover technology must be supported for the non-stop operation of the power distribution system. This paper proposes the system architecture of new power distribution management system to cope with high penetration of renewable energy. To verify the proposed system architecture, the functional unit test and performance measurement were performed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.365-369
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• 2015

In this paper, geographic information system(GIS) for an intelligent power distribution network was implemented with location informations acquired from automatic meter reading system, where the location informations of power line communication(PLC) modems installed at customer side were collected at data concentration units(DCUs) of headend equipment via PLC and then were transmitted to front end processor server. By displaying the connection status of the power distribution network on GIS map, operation of advanced metering infrastructure(AMI) or management of power grid system could be performed intuitionally and in real time, because the configuration state of the power grid could be easily monitored. The feasibility of the proposed system was confirmed with the especially constructed laboratory-level test bed and the verification test of the system will be carried out for a real power distribution network.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Proceedings of the KIEE Conference
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• 2006.05a
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• pp.78-82
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• 2006

The Partial Discharge Monitoring System is technology which is available to measure & analysis the partial discharge of Power equipment. This technology is in the limelight as a pre-forecast system of equipment defect but there are some problems like no protocol standard, layered network management and the limitation of physical size. This paper presents whole system structure includes engineering centers, LN(Logical Node) to apply PDMS for, base-digital substation system, ICE61850 compatible Condition Monitoring &Diagnosis (CMD), Local Unit(LU), Intelligent Electronic Device (IED) for the solution scheme of these limitations.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.17-27
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• 2022

In this paper, ED-H algorithm, an optimal real-time scheduling algorithm dealing with the characteristics of the integrated energy harvester system with a capacitor, is extended to satisfy the time constraint under the blackout state which is a deliberate power-off state by an intelligent power management unit adopted in the system. If the power supply system does not have enough energy, it temporarily shuts off the power supply to protect the circuit and capacitor and resumes the supply again when the capacitor is fully charged, which may delay the task execution during these blackout states by calculating the time according to the occurrence of the events. To mitigate the problem, even if task execution is delayed by the original ED-H algorithm, the remaining time of the subsequent time units no longer can afford to delay the execution of the task is predicted in the extended algorithm and the task is forced to be scheduled to meet the time deadline. According to the simulation results, it is confirmed that the algorithm proposed in this paper has a high scheduling performance increase of 0.4% to 7.7% depending on the characteristics of the set of tasks compared to the ED-H.

• Proceedings of the KIEE Conference
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• 2006.07e
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• pp.19-22
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• 2006

The CMD(Condition Monitoring & Diagnosis) System is used to monitor and analyze the PD(Partial Discharge), Arc, Temperature, Pressure, Gas in Oil and so on for reliability and availability of the substation. Although this system comes into the spotlight as the forecast and management of the failure and fault, there are some problems. For example, the unified standard was not defined, and the effective management of the layed communication network does not performed, limitation of physical space, etc. To resolve above problems, this paper suggests the IEC61850 compatible eCMD system architecture for monitoring and analyzing the CMD factor in substations. The suggested eCMD system consists of CMD-LU(Condition Monitoring & Diagnosis-Local Unit), IED(Intelligent Electronic Device), and engineering centers. The IEC61850 is the international standard that defines communication networks and system in substation.

• Journal of Power Electronics
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• v.13 no.2
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• pp.186-196
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• 2013

This paper presents a low voltage-stress AC-linked charge equalizing system for balancing the energy in a serially connected, valve-regulated lead acid battery string using a modular converter that consists of multiple transformers coupled together. Each converter was coupled through an AC-linked bus to increase the overall energy transfer efficiency of the system and to eliminate the problem of the unbalanced charging of batteries. Previous solutions are based on centralized and modularized topologies. A centralized topology requires a redesign of the hardware and related components. It also faces a high voltage stress when the number of batteries is expanded. Modularized solutions use low-voltage-stress, double-stage, DC-linked topologies which leads to poor energy transfer efficiency. The proposed solution uses a low-voltage stress, AC-linked, modularized topology that makes adding more batteries easier. It also has a better energy transfer efficiency. To ensure that the charge equalization system operates smoothly and safely charges batteries, a small intelligent microcontroller was used in the control section. The efficiency of this charge equalization system is 85%, which is 21% better than other low-voltage-stress DC-linked charging techniques. The validity of this approach was confirmed by experimental results.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.