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Spatial dispersion of wind speeds and its influence on the forecasting error of wind power in a wind farm

机译:风电场的风速空间分布及其对风电预测误差的影响

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Big wind farms must be integrated to power system. Wind power from big wind farms, with randomness, volatility and intermittent, will bring adverse impacts on the connected power system. High precision wind power forecasting is helpful to reduce above adverse impacts. There are two kinds of wind power forecasting. One is to forecast wind power only based on its time series data. The other is to forecast wind power based on wind speeds from weather forecast. For a big wind farm, due to its spatial scale and dynamics of wind, wind speeds at different wind turbines are obviously different, that is called wind speed spatial dispersion. Spatial dispersion of wind speeds and its influence on the wind power forecasting errors have been studied in this paper. An error evaluation framework has been established to account for the errors caused by wind speed spatial dispersion. A case study of several wind farms has demonstrated that even if the forecasting average wind speed is accurate, the error caused by wind speed spatial dispersion cannot be ignored for the wind power forecasting of a wind farm.
机译:大型风电场必须集成到电力系统中。大型风电场的风能具有随机性,波动性和间歇性,会对连接的电力系统产生不利影响。高精度风能预测有助于减少上述不利影响。风能预测有两种。一种是仅根据其时间序列数据预测风能。另一种是根据天气预报中的风速来预测风能。对于一个大型风电场,由于其空间规模和风的动态性,不同风力涡轮机的风速明显不同,这称为风速空间弥散。研究了风速的空间色散及其对风电预测误差的影响。建立了一个错误评估框架,以解决由风速空间分散引起的错误。对多个风电场的案例研究表明,即使预测的平均风速是准确的,风电场的风电功率预测也不能忽略由风速空间分散引起的误差。

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