• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.859-866
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• 2021

Agricultural Photovoltaic power generation is a new model that installs solar power generation facilities on top of farmland. Through this, it is possible to increase farm household income by producing crops and electricity at the same time. Recently, various attempts have been made to utilize agricultural solar power generation. Agricultural photovoltaic power generation has a disadvantage in that maintenance is relatively difficult because it is installed on a relatively high structure unlike conventional photovoltaic power generation. To solve these problems, intelligent and efficient operation and diagnostic functions are required. In this paper, we discuss the design and implementation of a prediction and diagnosis system to collect and store the power output of agricultural solar power generation facilities and implement an intelligent prediction model. The proposed system predicts the amount of power generation based on the amount of solar power generation and environmental sensor data, determines whether there is an abnormality in the facility, calculates the aging degree of the facility and provides it to the user.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.27-33
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• 2013

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.106-111
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• 2010

Electronic watt hour meters(WHM) for high pressure running in domestic were installed to the digital type meter and ones for low pressure are expected to complete within several years. Domestic power metering technology is being beyond a simple framework with an electronic type and is rapidly evolving to intelligent smart metering systems in conjunction with promotion of a national smart grid project. Major policy outlook of the world's major power company regarding Intelligent metering is the application of the fare structure diversification and is the improvement of level of service to customers. In addition, electric power companies should focus on the cost reduction and the improvement of management efficiency through an efficient operation of distribution facility. In this paper, we are about to make an observation of the additional services technology development trend of the overseas smart meter and to have a view of value-added services(VAS) system of smart meter suitable for the domestic environment based on the technology development of VAS utilizing electronic watt hour meter performed by recent research projects.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.

• 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.

• 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.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.229-234
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• 2008

The new millennium has started with several innovations driven by fast evolution of the technologies in energy sector. A strong impulse towards the diffusion of new economical efficient technologies regulatory incentives related to energy production from renewable source and a small scale building trigeneration and to promotion of more sustainable environmental-friendly generation solutions, the evolution of electricity markets, more and more binding local emission constraints, and the need for improving the security of supply to reduce the energy system vulnerability. The 24 percentage energy quantify of total energy consumption consumes in commercial buildings and residential houses and the 30% portion of total $CO_2$ emissions covers also in the commercial buildings and residential houses sector. To cope with efficiently this energy sinuation in building sector, Building microgrid or building tooling, heating & power(BCHP) system has been interested in recent day due to meeting thermal and electric energy requirements efficiently and with appropriate energy quality. A multi agent system is a collective of intelligent agents that communicate with each other and work cooperatively to achieve common goals. Also, it is to medicate and coordinate communication between Control Areas and Security Coordinators for teal-time control of the BCHP system and the power pid. In this new circumstance, it is very important to integrate the power and energy delivery system and the information system(communication, networks, and intelligent equipment) that controls it. Therefore, development of smart control modules with open communication protocol and seamlessly interchange the data and information between control network and data network including extranet and intranet give a great meanings. We designed and developed the TCP/IP-CAN IED agent modules and ModBus./LonTalk/(TCP/IP) IED agent ones to configure the multi-agent system based smart energy network of commercial buildings and also intelligent algorithms for inverter fault diagnostics which ran be operated in control level or agent level network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.169-174
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• 2023

Currently, overall power usage is also increasing as power demand such as homes, offices, and factories increases. The increase in power use also raised interest in standby power as a change in awareness of energy saving appeared. Home and office devices are consuming power even in standby conditions. Accordingly, there is a growing need to reduce standby power, and it aims to have standby power of 1W or less. An intelligent outlet uses a near-field wireless network to connect to a home network and cut or reduce standby power of a lamp or appliance connected to an outlet. This research aims to develop a monitoring system and an intelligent outlet that can remotely monitor the amount of electricity used in a lighting lamp or a home appliance connected to an outlet using a short-range wireless network (Zigbee). Also, The intelligent outlet and monitoring system developed makes it possible for a user to easily cut off standby power by using a portable device. Intelligent outlets will not only reduce standby power but also be applicable to fire prevention systems. Devices that cut off standby power include intelligent outlets and standby power cutoff switches, so they will prevent short circuits and fires.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.4
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• pp.425-433
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• 2012

As the demand for electric power increases rapidly and the amount of fossil fuels decreases year by year, making use of renewable resources seem very necessary. However, due to the discontinuous nature of renewable resources and the hierarchical topology of existing grids, power quality and grid stability will deteriorate as more and more distributed generations (DGs) are connected to the grids. It is a good idea to combine local utilization, local consumption, energy storage and DGs to form a grid-friendly micro grid, these micro grids can then assembled into an intelligent power system - the smart Grid. It can optimize power flow and integrate power generation and consumption effectively. Most importantly, the power quality and grid stability can be improved greatly. This paper depicts how the smart grid addresses the current issues of a power system. It also figures out the key technologies and expectations of the smart grid.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.491-497
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• 2007

As dispersed generators was driven in condition interconnecting with utility, it could cause a variety of new effects to the original distribution system that was running as considered only the one-way power flow. Therefore, the protection devices that is builted in distribution system should be designed to be able to operate with disposing of not only a fault of the generator, but also utility condition. Especially, the fault of the feeder interconnected with Dispersed Generator can cause the islanding phenomenon of open DG(Dispersed Generators). This phenomenon has many problems such as a machinery damage, electricity qualify degradation and a difficulty of the system recovery. In the fault therefore, we must separate Dispersed Generator from the system quickly. In this paper, for the fault classification of the interconnected DG and the outside feeder we judge the fault of the interconnected DG and the outside feeder in HMI through data provided by IED(Intelligent Electronic Device) on the network and decide whether it operates or not by sending the result to each relay.