英国论文重复率要求：风电预测模型
风电预测模型需要对机组承诺进行规划。还应该对调度、对系统操作的调度等进行规划。它的作用应该是确保在可能的情况下使用电力商的目标来优化能源生产，在任何较小的时间范围内。已经广泛应用并在理论上进行了讨论的风力发电模型有WPMS、WPPT、Prediktor、ARMINES、Previento、WPFS Ver1.0等。每一种预测模型都被认为与风力发电的不同范围有关，它们也有各自的优缺点。其中一些在基于物理模型、统计模型的预测方面工作得更好，一些可能需要使用混合模型。
英国论文重复率要求 ：风电预测模型
风力是一种固有的可变形式的电源，因此使用预测系统变得至关重要。在短期预测的背景下，有可能预测的风能最多提前1小时和72小时(Nielson等，2007;Giebel等，2003)。这在过去常常受到更多的限制。然而，在当今时代，这种情况已经改善了很多。在风力发电的背景下，机组承诺和全天候调度仍然是不可能的，但也有可能有某种形式的中期预测，如3天至7天的预测。根据这些中期预测，我们会提前约72小时至1小时作出短期预测。然而，由于必须在模型中映射时间，甚至这些预测样式也经常受到挑战。
英国论文重复率要求 ：风电预测模型
The wind power forecasting model needs to plan for the unit commitments. There should also be planning for scheduling, for dispatch to system operations and more. It should work so as to ensure the use of electricity trader objectives for optimization energy production where possible, given any smaller time frame. Some of the wind power models that have been used and theoretically discussed at large are the WPMS, WPPT, Prediktor, ARMINES, Previento, WPFS Ver1.0, etc. Each of these forecasting models is seen to be associated with different ranges in wind power and they have their pros and cons as well. Some of them work better in forecasting based on the physical models, statistical models and some might require the use of hybrid models.
英国论文重复率要求 ：风电预测模型
Wind is an inherently variable form of power source, and hence the use of a forecast system becomes critical. In the context of the short term forecasts, it is possible to predict for the wind energy up to one hour and 72 hours in advance (Nielson et al, 2007; Giebel, et al, 2003). This used to be more constrained in the past. However, in current times, this situation has improved a lot more. Unit commitments and dispatch for around the clock is still not possible in the context of wind power, but it is also possible to have some form of medium term forecasts such as 3 days to 7 days’ forecasts. Based on these medium term forecasts, short term forecasts are then made for around 72 hours to an hour in advance. However, even these forecast styles are often challenged because of how time has to be mapped in the models.