• 풍력에너지저널
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• 제5권2호
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• pp.45-50
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• 2014

Reviewing the capacity and timing of Southwest sea offshore wind farms, additional farms developing, and potential farms, we devised the long-term plan of domestic offshore wind farms development. In order to rank many wind farms, we determined evaluation indicators and weights of priority. We applied economic and preliminary factors such as wind grade, depth of water, distance from substations, farms scale, MOU signed, and feasibility studies. After deciding the ranking of wind farms by the scores, we planed domestic long-term scenarios of offshore wind farms development to meet national energy policy objectives.

• 전기학회논문지
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• 제57권11호
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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.

• 풍력에너지저널
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• 제14권3호
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• pp.61-68
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• 2023

This paper aims to perform optimal operation and maintenance with an integrated monitoring system for offshore wind platforms. Based on the wind direction and wind speed data of existing wind farms, a monitoring system was established along with weather and weather data to maximize the operational efficiency of wind farms. Compared to wind power on land, offshore wind power is difficult to maintain due to weather, logistics and geographical limitations. Therefore, economic analysis of actual operation and maintenance is essential for large-scale offshore wind farms. In this paper, the availability of offshore wind farms was analyzed by using personnel resources, parts inventory, Crew Transfer Vessel (CTV) and Specialized service Operation Vessel (SOV) etc. before the actual operation and maintenance of wind farms. A comparative analysis was conducted to determine the optimum operating efficiency and economical maintenance costs.

• 동력기계공학회지
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• 제18권5호
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• pp.137-143
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• 2014

An investigation on lightning characteristics and damage to wind turbines was performed on Jeju and Gangwon regions. The lightning data from January 2010 to September 2013 detected by IMPACT ESP were collected and analyzed in detail. Hangyeong and Seongsan wind farms of Jeju province and Taebaek, Changjuk, Taegisan and Gangwon wind farms of Gangwon province were selected for this study. Lightning rates and lightning damage events at the six wind farms were compared with each other. Lightning maps for the two regions were drawn using lightning frequency data. As a result, lightning frequency of Gangwon region was higher than that of Jeju region, while lightning strength of Gangwon was weaker than that of Jeju. Lightning rates were assessed to be good for all of the six wind farms. No lightning damage to wind turbines occurred at the two wind farms of Jeju, while some lightning damage to wind turbines took place at the four wind farms of Gangwon.

• 한국태양에너지학회 논문집
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• 제33권5호
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• pp.60-68
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• 2013

This paper presents the characteristics of lightning over established and scheduled wind farms of Jeju island as well as over specific range of entire Jeju Island. The lightning data for 5 years from 2008 to 2012 was obtained from IMPACT ESP which detects lightning. Lightning frequency, lightning strength and regional lightning events were analyzed in detail, and then the lightning maps of Jeju Island were created. The evaluation of lightning rate was made for all the wind farms of this study. Damage to wind turbines by lightning was found in the existing wind farms. As a result, the eastern part of Jeju Island had more lightning frequency than the western part of the Island. Also, the evaluation of lightning rate was good for all established and scheduled wind farms of Jeju Island. Hankyung is the best place for lightning safety, while precaution should be taken against lightning damage in Kimnyung. Lightning damage to wind turbines occurred in Samdal and Haengwon wind farms, which had the first and the second highest lightning rate of the five existing wind farms.

• 전기학회논문지
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• 제60권12호
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• pp.2183-2189
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• 2011

Since main portion of the required electric power in Jeju Island is provided from the mainland through two HVDC lines, Jeju HVDC has a most significant impact on Jeju power system. Average wind speed of Jeju Island is the highest among several candidates in South Korea. So, Jeju Island has been a suitable site for the construction of wind farms where several wind farms are now operating and several others to be sited. Since the large-scale wind generation could have adverse impacts on the stable operation of Jeju power system, wind power is also important for the stability of Jeju power system. Therefore, accurate modeling of Jeju HVDC and wind farms is required for stability analysis of Jeju power system. In this paper, PSS/E-based dynamic modeling of Jeju HVDC and DFIG wind farms is proposed. Model-writing technique of PSS/E is used to develop USRAUX model and USRMDL model for controlling the frequency of HVDC and imposing an operation limit of wind power, respectively. Dynamic characteristics of Jeju HVDC and DFIG wind farms are analyzed through the dynamic simulations. The simulation results show the effectiveness of the developed models for Jeju power system.

• 대한임베디드공학회논문지
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• 제19권3호
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• pp.131-139
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• 2024

Crew Transfer Vessels (CTVs) are primarily used for the maintenance of offshore wind farms. Despite being manually operated by professional captains and crew, collisions with other ships and marine structures still occur. To prevent this, the introduction of autonomous navigation systems to CTVs is necessary. In this study, research on the obstacle avoidance system of the autonomous navigation system for CTVs was conducted. In particular, research on obstacle avoidance simulation for CTVs using deep reinforcement learning was carried out, taking into account the currents and wind loads in offshore wind farms. For this purpose, 3 degrees of freedom ship maneuvering modeling for CTVs considering the currents and wind loads in offshore wind farms was performed, and a simulation environment for offshore wind farms was implemented to train and test the deep reinforcement learning agent. Specifically, this study conducted research on obstacle avoidance maneuvers using MATD3 within deep reinforcement learning, and as a result, it was confirmed that the model, which underwent training over 10,000 episodes, could successfully avoid both static and moving obstacles. This confirms the conclusion that the application of the methods proposed in this study can successfully facilitate obstacle avoidance for autonomous navigation CTVs within offshore wind farms.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.399-405
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• 2014

For stable integration of large-scale wind farms, integration standards (Grid codes) have been proposed by the system operator. In particular, voltage control of large-scale wind farms is gradually becoming important because of the increasing size of individual wind farms. Among the various voltage control methods, Secondary Voltage Control (SVC) is a method that can control the reactive power reserve of a control area uniformly. This paper proposes hybrid SVC when a large-scale wind farm is integrated into the power grid. Using SVC, the burden of a wind turbine converter for generating reactive power can be reduced. To prove the effectiveness of the proposed strategy, a simulation study is carried out for the Jeju system. The proposed strategy can improve the voltage conditions and reactive power reserve with this hybrid SVC.

• 경영과학
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• 제30권2호
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• pp.97-106
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• 2013

Of the new and renewable energies currently being pursued domestically, wind energy, together with solar photovoltaic energy, is a new core growth driver industry of Korea. As of May 2012, 33 wind farms at a capacity of 347.8MW are in operation domestically. The purpose of this study was to compare and analyze how efficiently each operational wind farm is utilizing its power generation capacity and the weather resource of wind. For this purpose, the study proceeded in 3 phases. In phase 1, ANOVA analysis was performed for each wind farm, thereby categorizing farms according to capacity, region, generator manufacturer, and quantity of weather resources available and comparing and analyzing the differences among their operating efficiency. In phase 2, for comparative analysis of the operating efficiency of each farm, Data Envelopment Analysis (DEA) was used to calculate the efficiency index of individual farms. In the final phase, phase 3, regression analysis was used to analyze the effects of weather resources and the operating efficiency of the wind farm on the power generation per unit equipment. Results shows that for wind power generation, only a few farms had relatively high levels of operating efficiency, with most having low efficiency. Regression analysis showed that for wind farms, a 1 hour increase in wind speeds of at least 3m/s resulted in an average increase of 0.0000045MWh in power generation per 1MW generator equipment capacity, and a unit increase in the efficiency scale was found to result in approximately 0.20MWh power generation improvement per unit equipment.

• 조명전기설비학회논문지
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• 제29권7호
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• pp.80-86
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• 2015

As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is needed to estimate power outputs of wind generation resources. As a result, geographic information such as latitude and longitude plays a key role to estimate power outputs of spatially distributed wind farms. In this paper, we introduce spatial correlation analysis to estimate the power outputs produced by wind farms that are geographically distributed. We present spatial correlation analysis of empirical power output data for the JEJU Island and ERCOT ISO (Texas) wind farms and propose the Correlation Decay Distance (CoDecDist) model based on geographic correlation analysis to enhance the estimation of wind power outputs.