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A combined forecasting method for renewable generations and loads in power systems

机译:可再生代和电力系统负载的组合预测方法

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Accurate forecasting for "net load", i.e., the difference between the renewable generations and loads, are important for economical and secure dispatch of power systems. Of course, it is significant to ensure sufficient levels of ancillary service, in particular regulation service. Previously, wind power, photovoltaic generation (PV) and loads are forecasted separately. In contrast, in this paper, a direct and adaptive combined forecasting method is proposed for wind power, PV and load which is regardless of market structure (centralized planning/dispatch vs. market outcomes). Compared with the traditional forecasting methods such as support vector machine (SVM), it can online adjust model parameters to improve the forecasting accuracy. A contrastive analysis is performed between the separate forecasting model for wind power, PV and load, the offline combined forecasting model and the proposed approach. The results show that the proposed method can be self-adaptive to the fluctuation of renewable energy and is able to make the forecasting more accurate.
机译:为“净负荷”,即准确的预测,可再生代和负荷之间的差,对于电力系统的经济性和安全调度非常重要的。当然,这是显著确保辅助服务的充足水平,特别是监管服务。先前,风力发电,太阳能发电(PV)和负载分别预测。相反,在本文中,一个直接的和自适应组合预测方法提出了一种用于风力发电,PV和负载这是无论市场结构(集中规划/调度与市场结果)。与传统的预测方法,如支持向量机(SVM)相比,可在线调整模型参数,以提高预测精度。用于风力发电,PV和负载,离线组合预测模型和所提出的方法的单独的预测模型之间进行对比分析。结果表明,该方法可以自适应可再生能源的波动,能够使预测更准确。

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