评估“实时”分布式光伏数据的代表性,用于升级光伏发电估算

N. Haghdadi, A. Bruce, I. MacGill
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引用次数: 7

摘要

随着光伏发电系统在澳大利亚配电网中的渗透率持续增长,将分布式光伏发电数据纳入电力系统规划和运行变得越来越重要。但是,目前这种数据的可用性非常有限。APVI实时光伏地图(Live Map)提供了澳大利亚57个不同地区近实时的分布式光伏发电估计,基于大约6000个光伏系统在线报告其发电量。这些数据具有广泛的潜在应用,包括,例如,网络规划或光伏性能评估。在本文中,我们研究了贡献给实时地图数据库的光伏系统的特征,以评估其准确性和适用性,为电力系统规划和运营目的提供分布式光伏发电总量估计。根据清洁能源监管机构(CER)的数据库,该研究将向实时地图数据库提供数据的光伏系统样本与澳大利亚的光伏系统总数进行了比较。代表性是根据光伏系统的位置、规模、年龄和逆变器制造商来评估的。通过与澳大利亚电网的历史间隔计量家庭光伏发电的单独数据库进行比较,评估了APVI实时地图对个别地区光伏发电估计的准确性。最后,给出了分布式光伏数据在电网规划中的应用实例,以突出这些光伏发电估算的潜在价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing the representativeness of ‘Live’ distributed PV data for upscaled PV generation estimates
The incorporation of distributed PV generation data into power system planning and operation is becoming increasingly important as penetrations of PV systems on Australian distribution networks continue to grow. However, the availability of such data is currently very limited. The APVI Live PV Map (Live Map) provides near real-time distributed PV generation estimates in 57 different regions across Australia based on some 6000 PV systems reporting their generation online. This data has a wide range of potential applications including, for example, network planning or PV performance assessment. In this paper we investigate the characteristics of the PV systems contributing to the Live Map database, in order to assess its accuracy and suitability for providing total distributed PV generation estimates for power system planning and operational purposes. The study compares the sample of PV systems contributing data to the Live Map database with the total set of PV systems in Australia, according to the Clean Energy Regulator's (CER's) database. Representativeness is assessed in terms of PV system location, size, age, and inverter manufacturer. The accuracy of the APVI Live Map PV generation estimates for individual regions is assessed by comparison with a separate database of historical interval metered household PV generation from the Ausgrid network. Finally, an example of the application of distributed PV data to electricity network planning is provided to highlight the potential value of these PV generation estimates.
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