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This paper presents the modeling of insulated-gate bipolar transistor (IGBT) in electromagnetic transients program (EMTP) simulation for the reliable calculation of switching and conduction losses. The conventional approach considering the physical property of switching devices requires many attribute parameters and large computation efforts. In contrast, the proposed method uses the curve fitting and interpolation techniques based on typical switching waveforms and a userdefined component with variable resistances to capture the dynamic characteristics of IGBTs. Therefore, the simulation time can be efficiently reduced without losing the accuracy while avoiding the extremely small time step, which is required in simulation by the conventional method. The EMTP based simulation includes turn-on and turn-off transients of IGBT, saturation state, forward voltage of free-wheeling diode, and reverse recovery characteristics, etc. The effectiveness of proposed modeling for the EMTP simulation is verified by the comparison with experimental results obtained from practical implementation in hardware.

This paper proposes the enhanced application of superconducting magnetic energy storage (SMES) for the effective compensation of power fluctuations based on the interleaving technique. With increases in demand for renewable energy based photovoltaic (PV) generation system, the output power fluctuations from PV generation system due to sudden changes in environmental conditions can cause serious problems such as grid voltage and frequency variations. To solve this problem, the SMES system is applied with its superior characteristics with respect to high power density, fast response for charge and discharge operations, system efficiency, etc. In particular, the compensation capability is effectively improved by the proposed interleaving technique based on its parallel structure. The dynamic performance of the system designed using the proposed method is evaluated with several case studies through time-domain simulations.

This paper proposes the new energy management method based on the photovoltaic (PV) hybrid power conditioning system of 4 kW with an energy storage device (ESD). The use of the ESD such as a lithium-ion battery improves the energy efficiency of the overall system depending on time and weather conditions. In addition, the proposed system provides the new function for energy management in real time without weather forecasting while it considers the power generations from the PV system, residential load variations, and electricity price. In other words, the proposed energy management system (EMS) can reduce the electricity price by charging the energy of nighttime electric power. In addition, it can suppress the grid voltage variations caused by the large amount of PV generations during daytime with respect to relatively less load demand. The performances of the proposed EMS system based on the 4-kW PV HPCS with a lithium-ion battery are evaluated by time-domain simulation. Thereafter, the experimental prototype is implemented in hardware to verify the usefulness of the proposed system.

This paper proposes the new method based on the availability of three points measurement and convexity of photovoltaic (PV) curve characteristic at the maximum power point (MPP). In general, the MPP tracking (MPPT) function is the important part of all PV systems due to their power- voltage (P-V) characteristics related with weather conditions. Then, the analog-to-digital converter (ADC) and low pass filter (LPF) are required to measure the voltage and current for MPPT by the digital controller, which is used to implement the PV power conditioning system (PCS). The measurement and quantization error due to rounding or truncation in ADC and the delay of LPF might degrade the reliability of MPPT. To overcome this limitation, the proposed method is proposed while improving the performances in both steady-state and dynamic responses based on the detailed investigation of its properties for availability and convexity. The performances of proposed method are evaluated with the several case studies by the PSCAD/EMTDC ® simulation. Then, the experimental results are given to verify its feasibility in real-time.

This paper proposes an energy management strategy and adaptive control for superconducting magnetic energy storage (SMES) in a distribution power system with a grid- connected photovoltaic (PV) farm. Application of the SMES system can decrease the output power fluctuations of PV system effectively. Also, it can control the real and reactive powers corresponding to the scheduled reference values with adequate converter capacity, which are required at a steady-state operating point. Therefore, the adaptive control strategy for SMES plays a key role in improving the system stability when the PV generation causes uncertain variations due to weather conditions. The performance of proposed energy management strategy and control method for the SMES is then evaluated with several case studies based on the PSCAD/ EMTDC ® simulation.

In this study, we show that atraxia telangiectasia mutated kinase (ATM) activity is generally upregulated by different apoptotic stimuli, i.e. TNF-α, TRAIL, paclitaxel, or UV. Apoptotic progression is markedly attenuated by siATM-RNA through down regulation of caspase-8 and caspase-9 in parallel with decreases in FLIP-S (short form of cellular FLICE inhibitory protein) protein levels and Bid cleavage. In addition, ATM activity is upregulated through t-Cdc6 while caspase-8 and caspase-9 activities increase. Taken together, we suggest that ATM regulates caspase-8 activation by influencing levels of FLIP-S, ATM kinase activity is upregulated by t-Cdc6, and increased ATM activity plays an essential role in the amplification of apoptosis in TNF-α-stimulated HeLa cells.

The number of photovoltaic (PV) generators has been significantly increased worldwide as a main renewable energy resource. The output power of PV generators mainly depends on the solar irradiance, module temperature, and field conditions. Therefore, the maintenance of the PV system is necessary to improve the reliability in its use. In this paper, a novel method to diagnose output power lowering in a PV array is proposed to keep the good performance of its output power based on the relationships between PV module temperature, current, and voltage under maximum power point conditions. In particular, the proposed method does not require the accurate information in specification on PV module and sensors for measuring irradiation levels, which are required in conventional monitoring systems. This results in the reduction of cost. Then, it is effectively applied to a practical PV system by using the Kalman-filter algorithm. The performances of the proposed diagnosis method are evaluated and verified with the laboratory experiment and field tests as well as the PSCAD/EMTDC-based simulation test.

The photovoltaic(PV) generation system have recently become widely used to solve the environmental problems and running out of fossil fuels. However, the study on maintenance is inadequate for PV system. This paper proposes the novel diagnosis method of output power decline to maintain the normal output performance of PV array. The diagnosis method used the proportional relation of irradiation-output current(S-I) of PV array at maximum power point(MPP). And, first order polynomial using the relation is proposed to easily apply PV system. To estimate the relation in case of separation of PV array producer and diagnosis system producer. Kalman Filter algorithm is also proposed at 30.2kW grid-connected PV system. Then, the performance of diagnosis method is evaluated using the hardware tests as well as the simulation.

This paper analyzes the effect of superconducting magnetic energy storage (SMES) to improve the stability of the distribution network with a photovoltaic (PV) system and plug-in battery electric vehicles (PBEVs). The PBEVs are expected to play a major role in making the transport system. The charge of their batteries by the penetration of PBEVs results in an increase of peak demand. Also, the output power fluctuation from a large-scale PV system due to the weather conditions often causes instability of the system. To handle these problems, the SMES is applied in this paper. To analyze the effects of SMES on the system stability, several important factors such as the capacity of SMES, its regulation for grid-connection, power reserve margin, the charging scenario of battery, the output power fluctuation of the PV system, and the seasonal load demands, etc., are considered with field measurement data. The performances of the SMES are evaluated and verified with the PSCAD/EMTDC based simulation test.

This paper describes a study on the application of superconducting magnetic energy storage (SMES) and grid code compliance to a wind and photovoltaic (PV) generation system. When a grid operates under instantaneous outage or surge condition, the distributed generation systems such as wind and PV systems must remain connected to the grid during a certain period of time. Therefore, the distributed generation system should be able to operate under abnormal conditions, such as reactive power or current fluctuations, which can damage the system and critical loads. The SMES can significantly enhance the dynamic security of such distributed power systems due to its high energy density and quick response characteristics. In this paper, the SMES control strategies for a wind and PV generation system during a fault ride through condition are examined, and the dynamic performance of SMES is evaluated by a case study based on the PSCAD/EMTDC simulation.

This paper proposes a method to determine the optimal size of superconducting magnetic energy storage (SMES) to improve the stability of distribution power system with photovoltaic (PV) generation. The output power of PV system fluctuates according to changing weather conditions. Then, the system is subject to be unstable. In order to improve its stability, the SMES is applied. In general, the SMES is being considered as a strong candidate among energy storage devices in industry due to its high efficiency, fast response, and high energy density.