论文标题
风速和风力预测技术的评论
A Review of Wind Speed and Wind Power Forecasting Techniques
论文作者
论文摘要
预测特定变量可以取决于时间或空间量表。表示随时间变化的时间变化，反映了变量中存在的随机性。空间变化通常在气候和气象学中占主导地位。可以根据时间序列对变量的时间尺度进行建模。时间序列是数值数据点的连续有序序列，并且可以随时间变化而进行。风速预测应用主要在于电力市场清算，经济负载调度和调度方面的领域，有时提供辅助支持。因此，基于预测范围的正确分类，即预测持续时间对于各种传输系统运营商很重要。
Forecasting a particular variable can depend upon temporal or spatial scale. Temporal variations that indicate variations with time, reflect the stochasticity present in the variable. Spatial variation usually are dominant in climatology and meteorology. Temporal scale for a variable can be modeled in terms of time-series. A time series is a successively ordered sequence of numerical data points, and can be taken on any variable changing with time. Wind speed forecasting applications lie majorly in the area of electricity market clearing, economic load dispatch and scheduling, and sometimes to provide ancillary support. Thus, a proper classification based on the prediction horizon i.e. the duration of prediction becomes important for various transmission system operators.
