考虑预测误差的风电场储能配置优化方法

发布时间：2018-03-10 06:04

本文选题：储能配置　切入点：预测误差　出处：《电网技术》2017年02期 　论文类型：期刊论文

【摘要】：利用储能降低风电预测误差能够降低风电出力不确定性,从而减少弃风,储能的容量和功率配置则直接影响到补偿预测误差的效果和经济性。基于T location-scale(TLS)分布建立了风电预测误差概率分布模型,使用几何分布描述风电误差持续性,并利用粒子群算法对模型中的参数进行了极大似然估计。以风电场收益最大为优化目标,将补偿风电预测误差的置信度以机会约束的形式加入储能配置优化模型,并在模型中考虑了对风电预测出力曲线的修正。仿真计算结果表明,所提方法能够很好地拟合预测误差的概率密度函数和误差持续时间,储能配置的经济性优于不考虑误差持续时间和出力修正的模型,验证了所提方法能够提高储能配置的准确性和经济性。
[Abstract]:Using energy storage to reduce the prediction error of wind power can reduce the uncertainty of wind power output and thus reduce the abandonment of wind. The capacity and power allocation of energy storage directly affect the effect and economy of compensating prediction error. Based on the Tlocation-scaleTLS) distribution, the probability distribution model of wind power prediction error is established, and the geometric distribution is used to describe the persistence of wind power error. Using particle swarm optimization algorithm, the parameters in the model are estimated with maximum likelihood. The confidence degree of compensating wind power prediction error is added to the optimization model of energy storage configuration in the form of chance constraint, aiming at the maximum return of wind farm. The simulation results show that the proposed method can well fit the probability density function and the error duration of the prediction error. The economy of energy storage configuration is better than that of the model without error duration and force correction. It is verified that the proposed method can improve the accuracy and economy of energy storage configuration.
【作者单位】：电力系统国家重点实验室(清华大学电机系);中国电力科学研究院;
【基金】：国家863高技术基金项目(2012AA050207) 国家重点研发计划项目(2016YFB0900105)~~
【分类号】：TM614

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