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风电场功率预测的研究进展及发展趋势OA北大核心CSTPCD

Research progress and development trend of wind farm power prediction

中文摘要英文摘要

风电场功率预测可以有效地帮助平衡系统电力供应和负荷需求,从而降低风电功率波动性和不确定性对电力系统稳定性的影响.随着风电接入电力系统比例的增加,如何准确地预测风电场发电功率成为一大难点,将影响风电场并网运行.由此,系统总结了近些年来国内外学者在风电场功率预测方面的研究进展.首先,以预测时间尺度、预测物理量、预测原理、预测特点为分类标准,对多种风电场功率预测方法进行了分类梳理,总结了各类预测方法的研究情况,阐述了其特点及应用场景,为预测模型的选择提供了参考.之后,从单点预测、概率预测、预测曲线的角度总结了预测效果的评价指标,并就评价指标的选择给出建议.最后,总结了当前风电场功率预测全过程遇到的影响预测准确性、实用性的关键因素,提出了未来风电场功率预测可能的发展趋势,为准确预测风电场功率及电网的稳定并网运行提供了参考.

Wind power prediction can effectively help balance the power supply and load demand of a system,thereby reducing the impact of wind power fluctuations and uncertainty on the stability of the power system.As the proportion of wind power connected to the power system increases,how to accu-rately predict the power generation of wind farms has become a major challenge,which will affect the grid-connected operation of wind farms.The research progress of domestic and foreign scholars in wind farm power prediction in recent years was systematically summarized.Firstly,a variety of wind power prediction methods according to the classification criteria of time scale,prediction physical quantity,prediction principle,and prediction characteristics was classified and sorted out.The research status of various prediction methods was summarized,its characteristics and application scenarios were ex-plained,and a reference for the selection of prediction models was provided.Then,the evaluation indi-cators of the prediction effect were summarized from the perspectives of single-point prediction,proba-bility prediction and prediction curve,and some suggestions were given on the selection of evaluation indicators.Finally,the key problems affecting the accuracy and practicability of wind farm power pre-diction were summarized,and the possible development trends of wind farm power prediction in the fu-ture were proposed,which provided a reference for the accurate prediction of wind farm power and the stable grid-connected operation of the power grid.

李根银;郁冶;王异成;何嘉桦;王强;罗坤;樊建人

浙江浙能国电投嵊泗海上风力发电有限公司,浙江舟山 202450国家电投集团浙江新能源有限公司,浙江杭州 310016杭州意能电力技术有限公司,浙江杭州 310027浙江大学能源高效清洁利用全国重点实验室,浙江杭州 310027浙江大学能源高效清洁利用全国重点实验室,浙江杭州 310027||浙江省清洁能源与碳中和重点实验室,浙江杭州 310027

能源与动力

风电场功率预测评价指标研究进展发展趋势

wind farmpower predictionevaluation indexresearch progressdevelopment trend

《排灌机械工程学报》 2024 (008)

778-784,817 / 8

浙江浙能国电投嵊泗海上风力发电有限公司科技项目(ZNKJ-2021-080);浙江省自然科学基金资助项目(LY24E060002)

10.3969/j.issn.1674-8530.22.0197

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