• Journal of the Korean Solar Energy Society
• /
• v.27 no.2
• /
• pp.37-44
• /
• 2007

As photovoltaic(PV) power generation system becomes more common, it will be necessary to investigate islanding detection method for PV systems. Islanding of PV systems can cause a variety of problems and must be prevented. However, if the real and reactive power of the load and PV system are closely matched, islanding detection by Passive methods becomes difficult. Also, most active methods lose effectiveness when there are several PV systems feeding the same island. The active frequency drift positive feedback method(AFDPF) enables islanding detection by forcing the frequency of the voltage in the island to drift up or down. In this paper the research for the minimum value of chopping fraction gain applied digital phase-locked-loop (DPLL) to AFDPF considering output power quality and islanding prevention performance are performed by simulation and experiment according to IEEE Std 929-2000 islanding test.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.4 no.3
• /
• pp.275-284
• /
• 1999

Unbalanced source voltage in the 3-phase power system is decomposed into positive, negative and zero sequence c components. Also, assuming there is no neutral path in the system, the zero sequence component is not shown on the l load side. Therefore, in the unbalanced power system without neutral path. it is possible to provide balanced voltage to t the load side by compensating negative sequence component and also to regulate the voltage amplitude by controlling t the positive sequence component. In addition, the symmetrical components due to voltage unbalance can be effectively d detected on the synchronous reference frame by using dlongleftarrowq transformation. In this paper, an algorithm not only c compensating unbalanced source voltage by canceling the negative sequence component on the synchronous reference f frame but also maintaining load voltages constantly is proposed. Also a novel method for phase angle detection s synchronized by positive sequence component under unbalanced source voltage is suggested and this detected phase a angle is used for d-q transformation. The performances and characteristics of the proposed compensating system are a analyzed by simulation and verified through experimental results.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.4
• /
• pp.238-245
• /
• 2016

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.11
• /
• pp.1545-1550
• /
• 2014

Fault detection and diagnosis (FDD) of photovoltaic (PV) power systems is one of significant techniques for reducing economic loss due to abnormality occurred in PV modules. This paper presents a new FDD method against PV power systems by using statistical comparison. This comparative approach includes deviation signals between the outputs of two neighboring PV modules. We first define a binary hypothesis testing under such deviation and make use of a generalized likelihood ratio testing (GLRT) theory to derive its FDD algorithm. Additionally, a recursive computational mechanism for our proposed FDD algorithm is presented for improving a computational effectiveness in practice. We carry out a real-time experiment to test reliability of the proposed FDD algorithm by utilizing a lab based PV test-bed system.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.54 no.4
• /
• pp.208-216
• /
• 2005

Recently, the study of islanding phenomenon, maintains its operation even when the utility grid is removed has lead to the trend of utility interactive inverters in photovoltaic generation systems. In this paper, a novel Anti-islanding method is presented. the proposed method can keep the real average power component constant by MPPT control and cause the load current frequency with only change of reactive power component under the islanding condition. its periodical change of Reactive power component can decrease the NDZ(Non-Detective zone) so that the detection of various loads will be possible. the insufficient effect if additional reactive power component to the grid is proved theoretically and the islanding detection is also confirmed from a experimental result with a inverter for 3kW photovoltaic generation system applied the proposed Anti-islanding method.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.251-253
• /
• 2004

Nowadays, power customer has increased and new power plants have been constructed for market demands. However, increasement of power plants make power system more complex and unstable. For this reason, the stability problem is one of the most important issues in power systems. In this paper, a study on implementation of out-of-step detection algorithm is performed. The structure of digital relay is analyzed for development of out-of-step detection algorithm. DFT block which is used to extract basic frequency of voltage is analyzed to design VHDL.

• Nuclear Engineering and Technology
• /
• v.52 no.12
• /
• pp.2687-2698
• /
• 2020

Most of the machine learning-based intrusion detection tools developed for Industrial Control Systems (ICS) are trained on network packet captures, and they rely on monitoring network layer traffic alone for intrusion detection. This approach produces weak intrusion detection systems, as ICS cyber-attacks have a real and significant impact on the process variables. A limited number of researchers consider integrating process measurements. However, in complex systems, process variable changes could result from different combinations of abnormal occurrences. This paper examines recent advances in intrusion detection algorithms, their limitations, challenges and the status of their application in critical infrastructures. We also introduce the discussion on the similarities and conflicts observed in the development of machine learning tools and techniques for fault diagnosis and cybersecurity in the protection of complex systems and the need to establish a clear difference between them. As a case study, we discuss special characteristics in nuclear power control systems and the factors that constraint the direct integration of security algorithms. Moreover, we discuss data reliability issues and present references and direct URL to recent open-source data repositories to aid researchers in developing data-driven ICS intrusion detection systems.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.811-825
• /
• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• KIEE International Transactions on Power Engineering
• /
• v.4A no.1
• /
• pp.42-47
• /
• 2004

This paper presents the various application programs for the Distribution Automation System (DAS) of the Korea Electric Power Corporation (KEPCO)'s distribution system. These programs are developed to allow for optimal operation in the areas of feeder automation, relay coordination, loss minimization and so on. They are single line diagram auto creation programs for the feeder, service restoration program, protection coordination program, data error detection program, and optimal network reconfiguration program. The details of these programs are presented for validity and effectiveness.

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.269-272
• /
• 2006

In this paper we describe the design of a Dual Power Controller(DPC) for Power Control System(PCS) in Nuclear Power Plant. The PCS also provides information regarding rod motion, rod position, and status of the Rod Control System. It has Hot/Stand-by type, and also has the function of fault detection for controller itself and power modules. We have implemented the various functions with the dual Power Controller. Due to the developed DPC, we are assured that the commmecial use by this controller be made before long.