多时空尺度的风力发电预测方法综述
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摘要
风能是目前世界上装机量较大的可再生能源之一,风力发电预测的精度直接影响电网的调度与安全运营.由于电网的调度策略存在多个时间点,并与涉及的地域范围有关,本文从多种时间和空间尺度的角度,综述风力发电预测方法.风力发电预测一般针对特定的空间范围和时间尺度,并在有限信息资源的条件下完成,故本文从上述三个方面综述已有研究成果.本文首先根据风力发电空间范围,从单台风力发电机、单一风电场以及风电场群三个空间尺度对研究成果进行梳理.其次在每个空间尺度上,根据风电预测是否使用气象信息将研究成果分类,并根据预测时间尺度将研究成果再次分类.最后在每个时间尺度上,根据风电预测存在的挑战,将已有的研究成果归类.通过上述梳理,本文希望可以帮助研究人员找到适合不同风电预测任务场景的方法.
Wind power is one of the most installed renewable energy resources in the world, and the accuracy of wind power forecasting method directly affects dispatching and operation safety of the power grid. Since scheduling strategy of the power grid has multiple points and is relative to the geographical scope, this paper summarizes wind power forecasting methods from multi-temporal and multi-spatial perspective. Wind power forecasting usually focuses on specific spatial scale and temporal scale, and is finished with limited information, so this paper classifies researches from three aspects above. Firstly, this paper separates existing wind power forecasting methods into three spatial scales, namely a single wind turbine, a wind farm and a group of wind farms. In each spatial scale, we classify methods by whether using meteorological information, and afterwards by temporal scales. Lastly, in each temporal scale, we also summarize the challenges and achievements. This paper wishes researchers would find suitable methodology when dealing with different wind power forecasting tasks.
Wind power is one of the most installed renewable energy resources in the world, and the accuracy of wind power forecasting method directly affects dispatching and operation safety of the power grid. Since scheduling strategy of the power grid has multiple points and is relative to the geographical scope, this paper summarizes wind power forecasting methods from multi-temporal and multi-spatial perspective. Wind power forecasting usually focuses on specific spatial scale and temporal scale, and is finished with limited information, so this paper classifies researches from three aspects above. Firstly, this paper separates existing wind power forecasting methods into three spatial scales, namely a single wind turbine, a wind farm and a group of wind farms. In each spatial scale, we classify methods by whether using meteorological information, and afterwards by temporal scales. Lastly, in each temporal scale, we also summarize the challenges and achievements. This paper wishes researchers would find suitable methodology when dealing with different wind power forecasting tasks.
引文
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