• 한국신재생에너지학회:학술대회논문집
• /
• 2007.06a
• /
• pp.395-399
• /
• 2007

Renewable energy sources such as wind energy is copiously available without any limitation. Wind turbines are used to tap the potential of wind energy which is available in millions of megawatt. Reliability of wind turbine is critical to extract this maximum amount of energy from the wind. We reviewed different techniques, methodologies, and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns. To keep the wind turbine in operation, implementation of Condition Monitoring System (CMS) is paramount, and for this purpose ample knowledge of these types of system is mandatory. So, an attempt has been made in this direction to review maximum approaches related to CMS in this piece of writing.

• Smart Structures and Systems
• /
• v.24 no.6
• /
• pp.733-744
• /
• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.1319-1327
• /
• 2015

As wind power farm (WPF) installations continue to grow, monitoring and controlling large-scale WPFs presents new challenges. In this paper, a hierarchical network architecture is proposed in order to provide remote monitoring and control of large-scale WPFs. The network architecture consists of three levels, including the WPF comprised of wind turbines and meteorological towers, local control center (LCC) responsible for remote monitoring and control of wind turbines, and a central control center (CCC) that offers data collection and aggregation of many WPFs. Different scenarios are considered in order to evaluate the performance of the WPF communications network with its hierarchical architecture. The communications network within the WPF is regarded as the local area network (LAN) while the communication among the LCCs and the CCC happens through a wide area network (WAN). We develop a communications network model based on an OPNET modeler, and the network performance is evaluated with respect to the link bandwidth and the end-to-end delay measured for various applications. As a result, this work contributes to the design of communications networks for large-scale WPFs.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.1
• /
• pp.16-18
• /
• 2010

This paper presents monitoring system based on IEC61400-25 for 750kW-class DFIG wind power generation system. It consists of wind turbine PLC, Local and Remote I/O Server, human machine interface, and Web-server. Proposed System has been demonstrated in Daegi-ri, Kangwon-do, which aims to test IEC61400-25 communication capability of monitoring system and evaluate the performance of 750kW-class WTS.

• 한국신재생에너지학회:학술대회논문집
• /
• 2006.06a
• /
• pp.308-311
• /
• 2006

A vibration monitoring is performed on a 1kW class stand alone wind turbine(W/T). When a W/T model is developed, general performance under various wind condition should be verified to introduce the product in the market. Especially, vibration characteristics within operating speed range are very important in the aspect of structural stability as well as generator's electrical efficiency. This paper examines the vibration performance of a home made 1kW W/T Various data of the W/T model are acquired in real time using a remote vibration monitoring system installed in Daekwanryung test site. Vibration stability of the W/T structure is diagnosed based upon the data and the result is used to estimate the applicability of the W/T model.

• Wind and Structures
• /
• v.16 no.4
• /
• pp.393-409
• /
• 2013

This paper uses ten years of on-site monitoring data for the Confederation Bridge to derive wind loads and investigate whether the bridge has experienced its design wind force effects since its completion in 1997. The load effects derived using loads from the on-site monitoring data are compared to the load effects derived using loads from the 1994 and 2009 wind tunnel aerodynamic model tests. The research shows, for the first time, that the aerodynamic model-based methodology originally developed in 1994 is a very accurate method for deriving wind loads for structural design. The research also confirms that the bridge has not experienced its specified (i.e., unfactored) wind force effects since it was opened to traffic in 1997, even during the most severe event that has occurred during this period.

• Journal of Environmental Science International
• /
• v.18 no.9
• /
• pp.941-952
• /
• 2009

The urban microscale wind field around the air quality monitoring station was investigated in order to check how a building complex influences it. For this study as the high density areas Jwa-dong and Yeonsan-dong monitoring sites in Busan were chosen. As the direction of inflow which is perpendicular to the building of the monitoring station was expected to cause the considerable variation of the wind field, that direction was selected. The model Envi-met was used as the diagnostic numerical model for this study. It is suitable for this investigation because Envi-met has the microscale resolution. After simulating it, on the leeward side around a building complex the decrease of flow velocity and some of vortexes or circulation area were discovered. In addition, on the edge of the top at the building and at the back of the building the upward flow was developed. If the sampling hole of monitoring site were located in this upward flow, it would be under the influence of upward flow from the near street.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.05a
• /
• pp.241-245
• /
• 2005

This study introduces the wind turbine (W/T) noise evaluation procedure required in the international standard (IEC 61400-11) and monitoring system for the evaluation. Noise emission characteristics of a 750kW W/T generator is investigated. Test and evaluation are performed on J48 W/T model which is under operation in Daekwanryung Wind Test Site. With the noise signal, meteorological data and W/T operational data are monitored in real time by the integrated monitoring system using LabVIEW. From the measured noise data, acoustic power level and tonality of the W/T are estimated under the wind speeds required by the international standard.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.8
• /
• pp.75-82
• /
• 2013

We propose a fiber grating sensor system for condition monitoring of large scale wind turbine blades. For the feasibility test of the proposed sensor system, a down-scaled wind turbine has been constructed and experimented. Fiber grating sensors were attached on a blade surface for distributed strain and temperature measurements. An optical rotary joint was used to transmit optical signals between the FBG sensor array and the signal processing unit. Instead of broadband light source, we used a wavelength-swept fiber laser to obtain high output power density. A spectrometer demodulation is used to alleviate the nonlinear wavelength tuning problem of the laser source. With the proposed sensor system we could measure dynamic strain and temperature profiles at multi-positions of rotating wind turbine blades.

• Journal of Ocean Engineering and Technology
• /
• v.32 no.1
• /
• pp.62-67
• /
• 2018

A wave buoy commonly used for measurements in marine environments is very useful for measurements on the sea surface wind and waves. However, it is constantly exposed to external forces such as typhoons and the risk of accidents caused by ships. Therefore, the installation and maintenance charges are large and constant. In this study, we developed a system for monitoring the sea surface wind using marine radar to provide spatial and temporal information about sea surface waves at a small cost. The essential technology required for this system is radar signal processing. This paper also describes the analytical process of using it for monitoring the sea surface wind. Consequently, developing this system will make it possible to replace wave buoys in the near future.