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An integration of enhanced wind power interval forecasting into reactive power dispatching

机译:增强风电间隔预测的集成反应电力调度

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The variability and unpredictability of the wind power has inevitably triggered a number of issues in the operation of the electrical power system such as voltage stability, power flow distribution and economic efficiency which draw researchers' attentions on the reactive power dispatching of wind farms. A traditional wind power forecasting is one of an essential way alleviating the above issues due to its contribution on deterministic dispatching. However, because of the unreliably predictive nature of wind power, the integration of wind power requires both the improvement of forecasting accuracy and the consideration of wind power forecasting uncertainty into reactive power dispatching. In this paper, an assimilation of an enhanced wind power interval forecasting system and reactive power dispatching has been proposed. The improvement of wind power forecasting is addressed from NWP amendment model and the interval forecasting model using least square method and relevance vector machine respectively. Furthermore, the forecasting and its uncertainty results from the interval forecasting system are integrated into the reactive power dispatching under a certain confidence level. The dispatching model is established considering the lifetime of capacitor and power loss of within wind farm. To take a wind farm in northwest of China as validation, the results show that the proposed interval forecasting system outperforms GA-BP model and SVM model, while the reactive power dispatching model combining the forecasting and its uncertainty information with has advantages over the traditional counterparts in terms of risk resistance, wind farm reliability and economic efficiency.
机译:风力发电的可变性和不可避免性是不可避免地引发了电力系统的运行中的许多问题,如电压稳定性,电力流量分布和经济效率,这些问题吸引了研究人员对风电场的无功派遣的关注。传统的风力预测是由于其对确定性派遣的贡献而减轻了上述问题的重要方面。然而,由于风力的不可达到预测性质,风电的整合需要改善预测精度和风力预测不确定性的预测性能转化为无功功率调度。本文提出了增强风电间隔预测系统和无功功率调度的同化。从NWP修正模型和使用最小二乘法和相关向量机的间隔预测模型解决了风力预测的改进。此外,间隔预测系统的预测及其不确定性结果集成在一定置信水平下的无功功率调度。考虑在风电场内的电容器和功率损失的寿命建立调度模型。为了占据中国西北部的风电场作为验证,结果表明,建议的间隔预测系统优于GA-BP模型和SVM模型,而具有优于传统对应的功率调度模型及其不确定性信息的反应电力调度模型在风险,风电场可靠性和经济效率方面。

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