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

机译:电力系统中可再生能源发电量和负荷的组合预测方法

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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:准确预测“净负荷”,即可再生发电量和负荷之间的差异,对于经济,安全地分配电力系统至关重要。当然,重要的是要确保足够水平的辅助服务,尤其是监管服务。以前,风能,光伏发电(PV)和负荷是分开预测的。相反,在本文中,针对风电,光伏发电和负荷提出了一种直接和自适应的组合预测方法,该方法与市场结构无关(集中式计划/调度与市场结果)。与支持向量机(SVM)等传统预测方法相比,该方法可以在线调整模型参数,提高预测精度。在风电,光伏和负荷的单独预测模型,离线组合预测模型和所提出的方法之间进行了对比分析。结果表明,所提出的方法可以自适应地适应可再生能源的波动,能够使预测更加准确。

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