sUncover: Estimating the Hidden Behind-the-meter Solar Rooftop and Battery Capacities in Grids

Venkata Ramakrishna Padullaparthi, V. Sarangan, A. Sivasubramaniam
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引用次数: 4

Abstract

As the technology costs of solar rooftops decline, small scale rooftops continue to become viable and grow without formal subsidies from the utility companies. Many new installations will continue to exist behind-the-meter (remain invisible), which poses challenges to the operating utilities for infrastructure and operations planning. This paper presents an approach to estimate the behind-the-meter solar PV size and the battery capacities. The proposed approach is based on energy balancing in buildings, and relies on data that is commonly available with utilities. The proposed approach is validated using a real-world dataset of 716 residential customers from a developed economy. The approach is compared with two baselines used by the studied Utility company. Results from the case study show that in 85% of the cases, the proposed approach has an accuracy of 98% in estimating the rooftop PV capacity (accuracies of baselines were in range 0%-30%). In estimating the battery capacity, the approach's estimates had less than 20% error in 70% of the cases (versus 35% error for baselines). The approach is also capable of discovering battery (dis)charging schedules, which is an additional useful information for utilities.
sUncover:估计电网中隐藏的太阳能屋顶和电池容量
随着太阳能屋顶技术成本的下降,小型屋顶继续变得可行,并且在没有公用事业公司正式补贴的情况下不断发展。许多新装置将继续存在于仪表后面(不可见),这对运营公用事业公司的基础设施和运营规划提出了挑战。本文提出了一种估算太阳能光伏发电规模和电池容量的方法。所提出的方法是基于建筑物的能量平衡,并依赖于公用事业公司通常提供的数据。所提出的方法使用来自发达经济体的716个住宅客户的真实数据集进行了验证。该方法与所研究的公用事业公司使用的两条基线进行了比较。案例研究的结果表明,在85%的案例中,所提出的方法在估算屋顶光伏容量方面的准确率为98%(基线的准确率在0%-30%之间)。在估计电池容量时,在70%的情况下,该方法的估计误差小于20%(而基线的误差为35%)。该方法还能够发现电池(不充电)时间表,这对公用事业公司来说是一个额外的有用信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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