• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.291-295
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• 2009

Economic and environmental concerns over fossil fuels encourage the development of photovoltaic(PV) energy systems. Due to the intermittent nature of solar energy. energy storage is needed in a stand-alone PV system for the purpose of ensuring continuous power flow. Grid-connected PV system that supply power in a critical load demand require to curb power fluctuation. In this case. SCB is a effectiveness in controlling power variation due to intrinsic PV system. We propose the Matlab/Simulink dynamic model and power flow characteristics of a hybrid energy system with PV and SCB.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.6
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• pp.577-586
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• 2011

This paper describes the development of hardware simulator for the operation analysis of DC microgrid. The hardware simulator consists of several distributed power sources such as a wind power generation, solar power and fuel cell, and two energy storages such as a supercapacitor and battery. The main controller which performs a role of energy management and state monitoring is connected with the local controller in each power source and storage through ethernet-based communication link. The developed hardware simulator can be utilized to analyze the performance DC microgrid with practical manner.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.