Short term wind speed and power forecasting in Indian and UK wind power farms

Ankita Singh, K. Gurtej, Gourav Jain, Faraz Nayyar, M M Tripathi
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引用次数: 10

Abstract

Wind power can be defined as the power produced by using wind as resource. This has a non-negligible impact which brings a lot of appreciable perks to the power supply and generation industry. An accurate forecast about the available wind energy production for the forthcoming hours is very crucial, so that exact planning and scheduling of the power generation from conventional units can be performed. The change in wind speed is based on the values of the metrological parameters which are variable in nature, such as humidity, temperature, atmospheric pressure, rainfall, moisture content etc. The values of these parameters/ variables can be obtained from the area weather stations. This paper presents two neural network models for forecasting wind speed and wind power on the data obtained from Indian agriculture and research institute (IARI), India and National renewable energy laboratory (NREL), UK. The results indicate that these models are able to forecast wind power with great accuracy in Indian as well as UK wind power plant.
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印度和英国风力发电场的短期风速和功率预测
风能可以定义为利用风能作为资源产生的电力。这带来了不可忽视的影响,给电力供应和发电行业带来了许多可观的好处。准确预测未来几小时的可用风能产量是非常重要的,这样才能对传统发电机组的发电进行精确的规划和调度。风速的变化是基于计量参数的值,这些参数在本质上是可变的,如湿度、温度、大气压、降雨量、含水量等。这些参数/变量的数值可从地区气象站获得。本文利用印度农业研究所(IARI)和英国国家可再生能源实验室(NREL)的数据,提出了两种预测风速和风力的神经网络模型。结果表明,这些模型能够较准确地预测印度和英国风力发电厂的风力发电量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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