데이터 플랫폼내 풍력잠재량에 적용되는 풍력설비의 적정 용량 밀도에 대한 분석

Abstract

In response to the national policy for the reduction of CO2 gas emissions and the dissemination of renewable energy resource facilities, the disseminated capacity of wind turbines is steadily expanding in Korea. However, to facilitate more realistic national dissemination planning, a more scientific basis for domestic wind potential and actual installation capability must be established. In this regard, a number of previous studies have provided details on the key parameters associated with wind energy potential. Among the major key points regarding wind energy potential is the array power density (APD) of wind turbines. However, this may be determined under certain ambiguous conditions associated with technical uncertainties. In general, an APD value of 5 MW/km2 is applied in Korea and a number of previous studies have reported results based on the application of APDs of 3 to 5 MW/km2. Given the diverse range of factors that can potentially influence the accuracy of the APD determinations for wind turbines, it is necessary to establish a more detailed and scientific basis for the determination of APD. In this study we seek to provide such a basis. To the best of our knowledge, this is the first study to assess the scientific basis of APD based on an examination of representative wind turbines, with respect to several technical specifications relating to wind speed, wind direction and IEC class conditions. We aim to scientifically analyze the effects of the performance characteristics of wind turbines on the APD, which is also the most important factor for an assessment of wind energy potential, and will contribute to establish an accurate technical basis for determination of APDs. On the basis of the findings in this study, we quantitatively identified the effective parameters for the determination of APD, which can be applied to facilitate an accurate determination of wind energy potential. Furthermore, these parameters have potential application as key variables in renewable energy data platforms and provide a technical reference for wind energy potential work area.