Replication Data for Chen, V.L., Delmas, M.A., Locke S., Singh, A. 2017. Information Strategies for Energy Conservation: A Field Experiment in India. Energy Economics.

The data presented in this article are related to the research article entitled: “Information Strategies for Energy Conservation: A Field Experiment in India” (Victor L. Chen, Magali A. Delmas, Stephen L. Locke, Amarjeet Singh, 2017).The availability of high-resolution electricity data offers benefits to both utilities and consumers to understand the dynamics of energy consumption for example, between billing periods or times of peak demand. However, few public datasets with high-temporal resolution have been available to researchers on electricity use, especially at the appliance-level. In this article, we describe data collected in a residential field experiment for 19 apartments at an Indian faculty housing complex during the period from August 1, 2013 to May 12, 2014. The dataset includes detailed information about electricity consumption. It also includes information on apartment characteristics and hourly weather variation to enable further studies of energy performance. These data can be used by researchers as training datasets to evaluate electricity usage consumption.

本文所呈现的数据，关联于题为《节能信息策略：印度实地实验》（Victor L. Chen、Magali A. Delmas、Stephen L. Locke、Amarjeet Singh，2017）的研究论文。
高分辨率电力数据（high-resolution electricity data）的可获取性，能够为电力公用事业企业与电力消费者赋能，使其得以深入洞悉能源消耗的动态变化——例如计费周期内或峰值需求时段的能耗波动。然而，目前面向研究者公开的高时间分辨率（high-temporal resolution）电力使用数据集仍较为匮乏，尤其是设备级别（appliance-level）的电力使用数据集。
本文中，我们介绍了2013年8月1日至2014年5月12日期间，在印度某教职工公寓园区针对19套住宅开展的实地实验所采集的数据。
本数据集包含详尽的电力消耗相关信息，同时涵盖住宅公寓的属性特征与逐小时气象变化数据，可为后续能源绩效（energy performance）相关研究提供有力支撑。
研究者可将该数据集用作评估电力使用情况的训练数据集（training datasets）。