刘威, 吴越剑, 白茂金, 段忠峰, 朱春萍, 董晓明. 基于Vasicek模型的新能源发电误差分析及储能配置决策方法[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0283
引用本文: 刘威, 吴越剑, 白茂金, 段忠峰, 朱春萍, 董晓明. 基于Vasicek模型的新能源发电误差分析及储能配置决策方法[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0283
LIU Wei, WU Yuejian, BAI Maojin, DUAN Zhongfeng, ZHU Chunping, DONG Xiaoming. Error Analysis on Renewable Generations and Decision Making Method for Energy Storage Allocation Based on Vasicek Model[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0283
Citation: LIU Wei, WU Yuejian, BAI Maojin, DUAN Zhongfeng, ZHU Chunping, DONG Xiaoming. Error Analysis on Renewable Generations and Decision Making Method for Energy Storage Allocation Based on Vasicek Model[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0283

基于Vasicek模型的新能源发电误差分析及储能配置决策方法

Error Analysis on Renewable Generations and Decision Making Method for Energy Storage Allocation Based on Vasicek Model

  • 摘要: 新能源机组出力预测误差的概率特性分析,对系统备用决策具有重要意义。常规的基于特定解析形式的分析模型,对于新能源实际出力分布规律的描述不够灵活且存在误差,为平抑不确定性的影响,集中式新能源通常需配置足够容量的储能应用,从而影响经济效益。因此,从随机过程的角度,依据一种特殊的随机微分方程—Vasicek模型,给出新能源出力模型的参数估计方法,避免概率分布的具体解析表达,并依托该模型提出一种改进的储能配置方法。算例分析表明,所提算法具有较好的短期预测性能,以此为依据决策储能容量配置更加精确和经济。

     

    Abstract: The probabilistic analysis on the output prediction error of renewable generations is of great significance to reserve energy decision making of the power system. Regular probabilistic analysis of renewable generations is usually based on specific analytical forms. It is not only inflexible but also prone to errors. To compensate for the influence of randomness, centralized renewable generations are typically equipped with sufficient energy storage, which may have impacts on their economic benefits. In view of this, from the perspective of stochastic process, according to a unique stochastic differential equation, that is, Vasicek model, we put forward a method for estimating the parameters of the renewable generation output model. This method can avoid analytical expression of the probability distributions. Later, an improved configuration method for the capacity of energy storage system is put forward. Case studies indicate that our method has good performance in terms of short term prediction, and the energy storage allocation decision made based on our method is more precise and economic.

     

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