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I-BLEND a campus-scale commercial and residential buildings electrical energy dataset

机译:I-BLEND校园规模的商业和住宅建筑电能数据集

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摘要

Efficient energy consumption at the building level is vital for sustainability. Providing energy efficient systems and solutions requires an understanding of how energy gets consumed. However, there is a general lack of large-scale open datasets about the energy consumption of buildings, which hinders the research. The recent emergence of smart energy meters makes it possible to collect such data, which can then be used for analysis. In this paper, we release I-BLEND, 52 months of electrical energy dataset at a one-minute sampling rate from commercial and residential buildings of an academic institute campus in an emerging economy, India. Also, we provide occupancy datasets at a 10-minute sampling rate for each of the campus buildings. To the best of our knowledge, this is the first such dataset from India. Public availability of such fine-granular data will allow users to perform different research tasks such as analyzing the impact of weather or occupancy schedule on energy consumption, detecting anomalies, and developing algorithms for predictive maintenance.
机译:建筑层面的高效能耗对于可持续发展至关重要。提供节能系统和解决方案需要了解如何消耗能源。然而,普遍缺乏关于建筑物能耗的大规模开放数据集,这阻碍了研究。智能电表的最新出现使得收集此类数据成为可能,然后可以将其用于分析。在本文中,我们发布了I-BLEND,这是一个52个月的电能数据集,以一分钟的采样率从印度新兴经济体的一所大学校园的商业和住宅楼中提取。此外,我们为每个校园建筑物提供了10分钟采样率的占用数据集。据我们所知,这是来自印度的第一个此类数据集。此类细粒度数据的公开可用性将使用户能够执行不同的研究任务,例如分析天气或占用时间表对能源消耗的影响,检测异常情况以及开发用于预测性维护的算法。

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