CAJ | 학술논문

为了支持风电场的开发和建设，结合最小二乘法对风切变指数这一重要参数进行了分析研究。根据风切变指数关系式和最小二乘法拟合直线算法，给出5种不同的方法分别计算风切变指数；然后根据计算得出的风切变指数与幂律公式推算已知高度的风速，再利用各自的推算结果与实测风速进行对比，分析其误差，选择较为准确的风切变指数。选用内蒙古乌兰察布市某测风塔共3个测风高度一年内完整的实测数据为例，采用上述方法计算该地区风切变指数，结果表明去除小风速后的数据利用最小二乘法拟合的计算方法和利用风廓线拟合的方法都较为准确；因此，应结合风电场的实际情况综合采用这些方法，选取误差最小的风切变指数。该研究有利于更准确地推算风机轮毂高度的风况，进而能够更加准确地估算发电量和评估风能资源。
위료지지풍전장적개발화건설，결합최소이승법대풍절변지수저일중요삼수진행료분석연구。근거풍절변지수관계식화최소이승법의합직선산법，급출5충불동적방법분별계산풍절변지수；연후근거계산득출적풍절변지수여멱률공식추산이지고도적풍속，재이용각자적추산결과여실측풍속진행대비，분석기오차，선택교위준학적풍절변지수。선용내몽고오란찰포시모측풍탑공3개측풍고도일년내완정적실측수거위례，채용상술방법계산해지구풍절변지수，결과표명거제소풍속후적수거이용최소이승법의합적계산방법화이용풍곽선의합적방법도교위준학；인차，응결합풍전장적실제정황종합채용저사방법，선취오차최소적풍절변지수。해연구유리우경준학지추산풍궤륜곡고도적풍황，진이능구경가준학지고산발전량화평고풍능자원。
In order to support the development and construction of wind farms, this paper analyzed and studied an important parameter-the wind shear exponent. Due to the influence of ground roughness, the wind shear exponents of different areas are different; in addition, because of the thermodynamic factor, the wind shear exponents are different even in the same area at different times. Therefore, to obtain an accurate value of the wind shear exponent in a certain area at a certain time, only the local wind-speed data can be used to calculate it. However, because of the complexity of the measured data, there are many methods to calculate the wind shear exponent, and the values calculated by different methods are different. So, in this paper, the methods of calculating wind shear exponent were studied. Firstly, there were five methods to calculate the wind shear exponent using different data sets, including 1) all of the data, 2) the data without wind speeds less than 3 m/s, 3) the data with the annual average wind speed, 4) the data with wind speeds between (15±0.5) m/s, 5) the wind profile. Among them, methods 1, 2, and 4 calculated wind shear exponent through the least-squares fitting. Method 3 used the annual average wind speed and the exponential formula to calculate wind shear exponent. Method 5 used wind profile fitting to calculate the wind shear exponent. The wind profile reflects the overall level of the wind conditions. Then, with the example of actual wind speed data, and within a complete year on three wind measurement heights at a mast of Wulanchabu in Inner Mongolia, five different wind shear exponents of this area were calculated by the above methods. Finally, according to the calculated wind shear exponents and the power-law formula, the wind speeds of the known height were calculated, and then by comparing the calculated value and actual value, the methods that produce smaller errors were chosen, and at last the more accurate wind shear exponent was obtained. The results showed that due to the impact of ground roughness and the topography, not only wind shear exponents were different in different areas, but they were also different when calculating by different methods even in the same area at the same time. The result of the method which used the data without wind speeds less than 3 m/s (method 2) for the least-squares fitting was more accurate than the result of the method which uses all of the data (method 1) for the least-squares fitting. The result calculated by the annual average wind speed (method 3) was close to the result calculated by using all of the data for the least-squares fitting. In the mountainous area, if it gets a negative wind shear exponent when calculated by the data with wind speeds between (15±0.5) m/s (method 4), the result will not be stable or reliable. Overall, the method of using the data without wind speeds less than 3 m/s calculated by the least-squares fitting and the method using wind profile fitting are more accurate than the other methods. Therefore, combining with the actual situation of wind farm, using these methods comprehensively to choose the smallest error wind shear exponent will provide the evaluation work with a more accurate foundation and ultimately achieve the goal of better utilization of wind resources.