• Title/Summary/Keyword: Wind power energy

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배터리 에너지저장이 결합된 계통연계 풍력발전시스템의 운전모드 개발 및 평가 (Operation Mode Development and Evaluation for Grid-Tied PMSG Wind Power System Combined with Battery Energy Storage)

  • 김현준;김도현;김경태;한병문
    • 전기학회논문지
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    • 제61권1호
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    • pp.41-49
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    • 2012
  • This paper describes the operation mode development for the grid-tied PMSG(permanent magnet synchronous generator) wind power system combined with a battery energy storage. The development of operation modes was carried out through simulations with PSCAD/EMTDC software and experiments with a 10kW hardware prototype. The detailed simulation models for PMSG wind power system and battery energy storage were developed using user-defined models programed with C-code. A 10kW hardware simulator was built and tested in connection with the local load and the utility power. The simulation and experimental results confirm that the grid-tied PMSG wind power system combined with battery energy storage can supply highly reliable power to the local load in various operation modes.

그린에너지 활용을 위한 소형풍력발전기의 효율 특성 (Generation Efficiency Characteristics of Small Wind Power for Green Energy Utilization)

  • 이유석;김재용
    • 공업화학
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    • 제26권4호
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    • pp.489-494
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    • 2015
  • 점차적으로 지구의 화석연료가 고갈됨에 따라, 효율적인 에너지 저장과 함께 그린에너지에 대한 기술과 수요가 절실히 요구된다. 풍력에너지는 현재 세계에서 가장 빠르게 확장되는 에너지원이다. 하지만 엄청난 가격의 대형풍력발전기 설치비와 정격풍속인 12 m/s 이상을 요구하는 상황에 따라 내륙에서의 풍력발전의 설치는 어려운 상황이다. 따라서 위의 문제를 해결하기 위하여, 저풍속에서도 발전가능한 소형풍력발전기를 실험하고자 하였다. 본 연구에서는 내륙에서의 풍황조건을 분석하고, 300 W와 1 kW 용량의 소형풍력발전기를 옥상에 설치한 후, 그들에 대한 발전효율 특성을 비교하였다.

타공 패널의 다공률에 따른 에너지 하베스팅에 관한 연구 (A Study on the Energy Harvesting according to the porosity of Perforated Panel)

  • 박하준;이민협;유무영
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2023년도 가을학술발표대회논문집
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    • pp.113-114
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    • 2023
  • As the available resources are gradually depleted, interest in renewable energy is increasing. Various energy harvesting technologies are emerging, and energy harvesting using solar, solar, and wind power is used in the highest range. Depending on the abnormal climate, solar heat and solar power differ in energy harvest, but the wind is fixed compared to the sun. Therefore, it was intended to maximize the effect of energy harvesting by using the venturi effect, which has a change in wind speed according to the turbine used for wind power generation and wind pressure. Therefore, in this paper, we want to see the difference in the amount of power generated by the turbine after increasing the wind speed using the venturi effect.

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Analysis of losses within SMES system for compensating output fluctuation of wind power farm

  • Park, S.I.;Kim, J.H.;Le, T.D.;Lee, D.H.;Kim, D.J.;Yoon, Y.S.;Yoon, K.Y.;Kim, H.M.
    • 한국초전도ㆍ저온공학회논문지
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    • 제16권4호
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    • pp.57-61
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    • 2014
  • Output fluctuation which is generated in wind power farm can hinder stability of total power system. The electric energy storage (EES) reduces unstable output, and superconducting magnetic energy storage (SMES) of various EESs has the proper performance for output compensation of wind power farm since it charges and discharges large scale power quickly with high efficiency. However, because of the change of current within SMES, the electromagnetic losses occur in the process of output compensation. In this paper, the thermal effect of the losses that occur in SMES system while compensating in wind power farm is analyzed. The output analysis of wind power farm is processed by numerical analysis, and the losses of SMES system is analyzed by 3D finite element analysis (FEA) simulation tool.

해상풍력 산업생태계 분석을 위한 제언: 신재생에너지산업 특수분류 기반 기업 간 거래네트워크 분석의 필요성 (A Suggestion for Offshore Wind Industry Ecosystem Analysis: The Necessity of Analyzing the Transaction Network Based on the Special Classification of the Renewable Energy Industry)

  • 이상혁;박재필
    • 풍력에너지저널
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    • 제13권4호
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    • pp.58-69
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    • 2022
  • This study reviews previous studies on the scale of offshore wind power industry ecosystems to provide basic data for a revitalization strategy for the offshore wind power industry and proposes an analysis of transaction networks based on the special classification of the renewable energy industry. First, we examine the localization rate, technology level, and price level of the offshore wind industry. Second, this research compares the methodology and estimation results of previous studies estimating the scale of the wind power industry. Third, we examine the details related to the enactment of a special classification of the renewable energy industry statistics and review the Korea Energy Agency's renewable energy industry statistics (focusing on 2019 and 2020). Finally, this study suggests the necessity of analyzing an inter-company transaction network based on special classifications of the renewable energy industry to grasp the status of each region and value chain of the offshore wind industry.

SODAR관측을 통해 분석한 도심지 상층의 풍력자원 특성 (The Characteristics of Wind Power Resource in Urban from SODAR Observation)

  • 이화운;박순영;김동혁;전원배;차영민;김현구
    • 한국신재생에너지학회:학술대회논문집
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    • 한국신재생에너지학회 2009년도 춘계학술대회 논문집
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    • pp.557-560
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    • 2009
  • When we urgently need to develop and supply an alternative energy, wind power is growing with much interest because it has relative low cost of power and area of tower. To estimate the wind power resource, it is necessary to make an observation first. Although the large wind falm and resources are near coast and mountain area, the wind energy in urban area has the strong thing of direct access to power generator. In this study, we estimate the probability of wind energy above urban area using SODAR data, which is located at the top of the tall building (140m).

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3MW 풍력발전시스템 출력 성능시험 및 불확도 분석 (Power Performance Testing and Uncertainty Analysis for a 3MW Wind Turbine)

  • 김건훈;현승건
    • 한국태양에너지학회 논문집
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    • 제30권6호
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    • pp.10-15
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    • 2010
  • The installed capacity of wind turbines in KOREA are growing and enlarging by the central government's support program. Thus, the importance of power performance verification and its uncertainty analysis are recognizing rapidly. This paper described the power testing results of a 3MW wind turbine and analysed an uncertainty level of measurements. The measured power curves are very closely coincide with the calculated one and the annual power production under the given Rayleigh wind speed distribution are estimated with the 3.6~12.7% of uncertainty but, in the dominant wind speed region as 7~8m/s, the uncertainty are stably decreased to 6.3~5.3%.

A Simple Power Management Scheme with Enhanced Stability for a Solar PV/Wind/Fuel Cell Fed Standalone Hybrid Power Supply using Embedded and Neural Network Controller

  • Thangavel, S.;Saravanan, S.
    • Journal of Electrical Engineering and Technology
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    • 제9권5호
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    • pp.1454-1470
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    • 2014
  • This paper propose a new power conditioner topology with intelligent power management controller that integrates multiple renewable energy sources such as solar energy, wind energy and fuel cell energy with battery backup to make best use of their operating characteristics and obtain better reliability than that could be obtained by single renewable energy based power supply. The proposed embedded controller is programmed for maintaining a constant voltage at PCC, maximum power point tracking for solar PV panel and WTG and power flow control by regulating the reference currents of the controller on instantaneous basis based on the power delivered by the sources and load demand. Instantaneous variation in reference currents of the controller enhances the controller response as it accommodates the effect of continuously varying solar insolation and wind speed in the power management. The power conditioner uses a battery bank with embedded controller based online SOC estimation and battery charging system to suitably sink or source the input power based on the load demand. The simulation results of the proposed power management system for a standalone solar/WTG/fuel cell fed hybrid power supply with real time solar radiation and wind velocity data collected from solar centre, KEC for a sporadically varying load demand is presented in this paper and the results are encouraging in reliability and stability perspective.

Wind states and power curve modeling: A case study for La Rumorosa I Wind Farm

  • Jesus O. Inzunza Castro;Alexis Acuna Ramirez;Marlene Zamora Machado;Magali Arellano Vazquez;Noemi Lizarraga Osuna
    • Wind and Structures
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    • 제39권3호
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    • pp.163-174
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    • 2024
  • This paper analyzes La Rumorosa I Wind Farm's wind states and their characteristics in the operation of two wind turbines over the course of one year of records. This information identifies the impact of wind states on wind power output. The study used the Gaussian Mixture Model to classify the occurrence and frequency of the dominant wind states in the generation of energy from the turbines. Results were obtained for mesoscale wind states and local scale wind states, such as cold fronts and Santa Ana winds, as well as daytime, nighttime and hot days, respectively, which were statistically analyzed to determine their relationship to power output by generating power and power coefficient curves. Between the cut-in speed and the rated speed of the wind turbines, cold fronts show higher efficiency, unlike nighttime wind states, which are the most efficient past the rated speed. In addition, cold fronts are also those that occur to the greatest extent, contributing 31.26% of the energy produced per year, compared with the Santa Ana winds, which occur to a lesser extent; however, they contribute 22.11% of the energy produced per year.

LSTM 딥러닝 신경망 모델을 이용한 풍력발전단지 풍속 오차에 따른 출력 예측 민감도 분석 (Analysis of wind farm power prediction sensitivity for wind speed error using LSTM deep learning model)

  • 강민상;손은국;이진재;강승진
    • 풍력에너지저널
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    • 제15권2호
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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.