• Journal of Wind Energy
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• v.15 no.2
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• pp.10-22
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• 2024

This research is a comprehensive analysis of wind power prediction sensitivity using a Long Short-Term Memory (LSTM) deep learning neural network model, accounting for the inherent uncertainties in wind speed estimation. Utilizing a year's worth of operational data from an operational wind farm, the study forecasts the power output of both individual wind turbines and the farm collectively. Predictions were made daily at intervals of 10 minutes and 1 hour over a span of three months. The model's forecast accuracy was evaluated by comparing the root mean square error (RMSE), normalized RMSE (NRMSE), and correlation coefficients with actual power output data. Moreover, the research investigated how inaccuracies in wind speed inputs affect the power prediction sensitivity of the model. By simulating wind speed errors within a normal distribution range of 1% to 15%, the study analyzed their influence on the accuracy of power predictions. This investigation provided insights into the required wind speed prediction error rate to achieve an 8% power prediction error threshold, meeting the incentive standards for forecasting systems in renewable energy generation.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.320-328
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• 2016

The introduction of renewable energy sources into the AC grid can change and weaken the strength of the grid, which will in turn affect the stability and robustness of the doubly-fed induction generator (DFIG) wind farm. When integrated with weak grids, the DFIG wind turbine with vector power control often suffers from poor performance and robustness, while the DFIG wind turbine with synchronized control provides better stability. This paper investigates the critical short circuit ratios of DFIG wind turbine with vector power control and synchronized control, to analyze the stability boundary of the DFIG wind turbine. Frequency domain methods based on sensitivity and complementary sensitivity of transfer matrix are used to investigate the stability boundary conditions. The critical capacity of DFIG wind farm with conventional vector power control at a certain point of common coupling (PCC) is obtained and is further increased by employing synchronized control properly. The stability boundary is validated by electromagnetic transient simulation of an offshore wind farm connected to a real regional grid.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.3
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• pp.72-77
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• 2014

The cross-section area of cable in the Offshore Wind Farm (OWF) is smaller than that in the onshore wind farm. Because the power loss in OWF is large relatively, the power loss is a key element for the economic evaluation of OWF design. The availability of wind turbine in OWF and the size of OWF are larger than those of onshore wind farm. If the economic evaluation of OWF ignores the availability of wind turbines, the power loss cost of OWF is overpriced. Since there are so many wind turbines, also, the calculation of power loss should be more accurate. In this paper, a method to calculate power loss is proposed for the design of big and complex inner-grid in OWF. The 99.5MW OWF is used for case study to see what effect the proposed method have on the power loss cost.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.28-37
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• 2015

Owing to the variability of large-scaled wind power system, the development of wind farm management technologies and related compensation methods have been receiving attention. To provide an accurate and reliable output power, certain wind farm adopts a specified management system including a wind prediction model and grid expectation solutions for considering grid condition. Those technologies are focused on improving the reliability and stability issues of wind farms, which can affect not only nearby system devices but also a voltage condition of utility grid. Therefore, to adapt the develop management system, an expectation process about voltage condition of Point of Common Coupling should be integrated in operating system for responding system requirements in real-time basis. This paper introduce a grid imposing method for a real-time based wind farm management system. The expected power can be transferred to the power flow section and the required quantity about reactive power can be calculated through the proposed system. For the verification process, the gauss-seidel method is introduced in the Matlab/Simulink for analysing power flow condition. The entire simulation process was designed to interwork with PSCAD for verifying real power system condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.1946-1953
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• 2008

Power system of Jeju is interconnected to the mainland using HVDC and that is also interconnected to three wind farms. It will be difficult to control of Jeju power system if HVDC is disconnected or HVDC is overhauled under large scale wind farms interconnected. We measured and analysed the power quality of two substation and two wind farms to assess that wind farms have an effect on Jeju system during the HVDC overhaul last May. We concentrated on the power quality like frequency, voltage variation, voltage harmonics, current harmonics, flicker. We can found that the frequency of Jeju system is very unstable during overhaul, so the frequency of Jeju system can be variated easily by wind farm's rapid output power variation. There are some benefits and weak points in power quality between two wind farms because each wind farm is consist of different wind turbines.

• New & Renewable Energy
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• v.5 no.2
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• pp.39-48
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• 2009

Recently, developing the offshore wind farm in Korean peninsula is widely understood as essential to achieve the national target for the renewable energy. As part of national plan, KEPRI (Korea electric power research institute) is performing the front running project for the offshore wind farm development that is dedicated to investigate the possible resources based on the economy considering current technological status. It also includes the selection of the first sea area among candidates and optimal design of the offshore wind farm, etc. In this paper the interim results of the project are summarized that the possible capacity for the offshore wind farm can be estimated conservatively around 18 GW regarding the wind power class, sea depth and social constraint. The five western sea areas near Taean, Gunsan, Gochang, Yeonggwang, Sinan were chosen for the candidating sites. Detailed analysis for these sites will be conducted to finalize the first-going offshore wind farm in Korea.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.439-442
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• 2009

As a result of increasing environmental concern, the penetration of renewable power on power systems is now increasing. Wind energy can be considered as the most economical energy sources to generate electricity without depletion of fossil fuel. The penetration of wind energy from wind farm is getting larger and larger, so we need adequate control strategies for wind farm. To devise adequate control strategies for wind farm, time domain simulation analysis needs to be performed. This presents a Simultaneous Implicit-based time domain simulation algorithm for wind farm with DFAG (Doubly Fed Asynchronous generator) connected to the external power systems. This paper shows an illustrative example with a 5-bus test system.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1047-1053
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• 2015

A time-domain simulation tool to predict the dynamic power output of wind turbines in an offshore wind farm was developed in this study. A wind turbine model consisting of first or second order transfer functions of various wind turbine elements was combined with the Ainslie's eddy viscosity wake model to construct the simulation tool. The wind turbine model also includes an aerodynamic model that is a look up table of power and thrust coefficients with respect to the tip speed ratio and pitch angle of the wind turbine obtained by a commercial multi-body dynamics simulation tool. The wake model includes algorithms of superposition of multiple wakes and propagation based on Taylor's frozen turbulence assumption. Torque and pitch control algorithms were implemented in the simulation tool to perform max-Cp and power regulation control of the wind turbines. The simulation tool calculates wind speeds in the two-dimensional domain of the wind farm at the hub height of the wind turbines and yields power outputs from individual wind turbines. The NREL 5MW reference wind turbine was targeted as a wind turbine to obtain parameters for the simulation. To validate the simulation tool, a Danish offshore wind farm with 80 wind turbines was modelled and used to predict the power from the wind farm. A comparison of the prediction with the measured values available in literature showed that the results from the simulation program were fairly close to the measured results in literature except when the wind turbines are congruent with the wind direction.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.460-462
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• 2009

This study has analyzed the scale, location, resource potential and feasibility of offshore wind farm scientifically and systematically based on the national wind map and GIS (Geographic Information System). For long-term wind power development, this study pursues siting strategy building, selection of target area and deciding development priority as well as the presenting a basis for assessment that are necessary for policy decision making by making theme layers under GIS environment. According to the analysis after organizing technological development by stages, even if only the most suitable sites are developed among the area of offshore wind farm candidates that can be developed under the current technological standard, it has been evaluated as being able to develop about 3 times of the wind power dissemination target until 2012. It is expected that about 5% of territorial water area can be developed in a short-term future while the southern offshore area possessing relatively favorable wind resource than the western offshore has been identified as the most feasible site. While about 23% of territorial water area has been classified as potential area for offshore wind farm development in a long-term future, even Jeju Island and offshore of Ulsan possessing excellent wind resource have been analyzed as feasible sites. The feasibility assessment of offshore wind farm development established by this study is expected to assist national strategy building for accomplishing the wind power dissemination target.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.32-35
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• 2011

The economic value of a wind farm project is influenced by various risk factors such as wind power output and electricity market price. In particular, there is uncertainty in the economic evaluation of a wind farm project due to uncertain wind power outputs, which are fluctuated by weather factors such as wind speed, and volatile electricity market prices. This paper presents a systematic method to assess the economic value and payback period of a wind farm project using Least Square Monte-Carlo (LSMC) simulation. Numerical example is presented to validate the effectiveness of the proposed economic assessment method for a wind farm project.