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首页> 外文期刊>Electric Power Components and Systems >A Hybrid bVAR-NARX Wind Power Forecasting Model Based on Wind and Load Demand Correlation: A Case Study of ERCOT's System from an ISO's Perspective
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A Hybrid bVAR-NARX Wind Power Forecasting Model Based on Wind and Load Demand Correlation: A Case Study of ERCOT's System from an ISO's Perspective

机译：基于风能和负荷需求相关性的混合bVAR-NARX风能预测模型：以ISO视角为例的ERCOT系统

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摘要

Wind power forecasting tools are as crucial for independent system operators (ISO) as it is for individual wind farm owners. ISO integrate wind power forecasting tools into power system operations for a number of applications and processes such as balancing energy, regulation and energy reserve services. To deal with the challenges that have surfaced in implementing wind power forecasting tools from an ISO's perspective, a hybrid model is proposed which is based on the correlation between wind power and load demand. The proposed model has used a bi-sectional vector auto-regressive model in conjunction with a nonlinear auto-regressive with exogenous output model forming a hybrid model that gives better results on real-world data sets as well. The case study taken for validating the model is the Electric Reliability Council of Texas system that has seen tremendous increase in the installed capacity of wind power generation sources in the recent past.
机译：风电预测工具对于独立系统运营商（ISO）至关重要，对于单个风电场业主而言也是如此。 ISO将风能预测工具集成到电力系统运营中，以实现多种应用和流程，例如平衡能源，调节和储能服务。为了从ISO的角度应对在实施风电预测工具时出现的挑战，提出了一种基于风电和负荷需求之间相关性的混合模型。所提出的模型结合了双向矢量自回归模型和非线性自回归模型，并与外生输出模型结合使用，形成了混合模型，该模型在真实数据集上也能提供更好的结果。验证该模型的案例研究是德克萨斯州电力可靠性委员会的系统，该系统在最近的几年中见证了风力发电源的装机容量的巨大增加。

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