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RAMP FORECASTING PERFORMANCE FROM IMPROVED SHORT-TERM WIND POWER FORECASTING

机译:改进的短期风电功率预测性能

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摘要

The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.
机译:风力发电的可变性和不确定性给电力系统运营商带来了新的关注。与将大量风能集成到电网中相关的最大问题之一是处理风能输出中的大坡度的能力。大的坡道会严重影响系统的经济性和可靠性,而电力系统运营商则将重点放在这方面。进行了风能预报改进项目(WFIP),以改进风能预报并确定这些改进对电网运营商的价值。本文评估了改进的短期风电斜率预测的性能。通过将实验性WFIP预测与当前的短期风能预测(STWPF)进行比较,该研究是由德克萨斯州电力可靠性委员会(ERCOT)进行的。这项研究采用了四种类型的重要风力发电坡道。这些基于功率变化幅度,方向和持续时间。采用旋转门算法从实际和预测的风力时间序列中提取斜坡事件。结果表明,实验性短期风能预报提高了风能斜率预报的准确性,尤其是在夏季。

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