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Very short-term solar PV generation forecast using SARIMA model: A case study

机译:使用SARIMA模型的非常短期太阳能光伏发电预测:案例研究

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The increase of interests in low carbon energy resources has promoted the deployment of solar photovoltaic (PV) systems. However, the grid integration of solar PV generation has few technical challenges due to its intermittency and non-dispatchability. An accurate (very) short-term solar PV generation forecast is critical to ensure secure and economic operation as well as for grid energy management. In this paper, the Seasonal Autoregressive Integrated Moving Average (SARIMA) model has been adopted for the multi-step ahead forecast (20 minute resolution) of solar PV generation. The roof-top solar PV systems installed at academic blocks and student hostels at IIT Gandhinagar campus are used as a case study to implement and validate the forecast model. The developed model is compared with the persistence model.
机译:对低碳能源的兴趣的增加促进了太阳能光伏(PV)系统的部署。但是,由于其间歇性和不可调度性,太阳能光伏发电的并网集成几乎没有技术挑战。准确(非常)的短期太阳能光伏发电预测对于确保安全,经济的运营以及电网能源管理至关重要。本文将季节性自回归综合移动平均线(SARIMA)模型用于太阳能光伏发电的多步超前预报(20分钟分辨率)。在IIT Gandhinagar校园的学术大楼和学生宿舍中安装的屋顶太阳能光伏系统将作为案例研究来实施和验证预测模型。将开发的模型与持久性模型进行比较。

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