在储能资源存在的情况下,太阳能发电的分解

C. Cheung, S. Kuppannagari, R. Kannan, V. Prasanna
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引用次数: 8

摘要

住宅屋顶光伏通常以电池的形式安装储能装置,目的是存储产生的多余能量,以便在需要额外能源时使用。最近,人们对提高太阳能的可观测性有了很大的兴趣,以获得更好的电网优化策略。然而,现有的算法只考虑没有连接到电池的独立光伏系统。电池的存在改变了从家庭记录的负载模式,因此当电池存在时,这些算法无法准确地执行分解。我们提出了一种改进的表后太阳能分解方法,该方法通过包含隐藏电池模型来考虑电池的充放电活动。我们将我们的方法与最先进的基于温度的分解负荷模型进行比较,并基于来自德克萨斯州奥斯汀的真实数据集的输入对模拟数据进行评估。我们的研究结果表明,在汇总客户数据的现有方法上,隐藏电池模型将平均绝对误差降低了28%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disaggregation of Behind-the-Meter Solar Generation in Presence of Energy Storage Resources
Residential rooftop photovoltaics are commonly installed with energy storage in the form of batteries for the purpose of storing excess energy generated for use when extra energy is needed. Recently, there has been a lot of interest in improving the observability of behind-the-meter solar for better grid optimization strategies. However, existing algorithms only consider standalone photovoltaic systems not connected to a battery. Presence of battery changes the load pattern recorded from the households, thus these algorithms are not able to perform disaggregation accurately when batteries are present. We propose an improved disaggregation method for behind-the-meter solar that takes into account the charging and discharging activity of batteries by including the hidden-battery model. We compare our methods with a state-of-the-art temperature based load model for disaggregation and evaluate the methodologies on simulated data based on inputs from a real life dataset based in Austin, Texas. Our results show that hidden-battery model reduces mean absolute error by 28% on an existing method on aggregated customer data.
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