Little is known about the effectiveness of information strategies on energy conservation in developing countries. In this study, we conduct a field experiment in an apartment complex in India to test how information about electricity usage impacts the electricity consumption of urban middle class households. Our results, based on fifteen-minute electricity readings over an academic year, show that nonmonetary messages that framed electricity consumption in terms of environmental and health impacts were more effective than messages emphasizing the monetary savings of reducing electricity consumption. Households in the environmental/health group accessed the online energy-monitoring dashboard more frequently and reduced their electricity usage by 18.4% relative to the control group. Households in the monetary group did not significantly alter their usage. These results about revealed preferences are contrasted with stated preferences disclosed in a survey of urban Indians who describe money, not health, as the main motivation for energy conservation. Our findings have important implications for the development non-monetary strategies for energy conservation in developing countries.

The data presented in this article are related to the research article entitled: "Information strategies for energy conservation: a field experiment in India" (Chen et al., 2017) [1]. 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. This article describes 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.

This study uses hourly appliance-level electricity consumption data for 124 apartments over 24 months to provide a better understanding of appliance-level electricity consumption behavior. We conduct our analysis in a standardized set of apartments with similar appliances, which allows us to identify behavioral differences in electricity use. The results show that households’ estimations of appliance-level consumption are inaccurate and that they overestimate lighting use by 60% and underestimate HVAC and plug-load by 40%. We find that similar households using the same major appliances exhibit substantial variation in appliance-level electricity consumption. Additionally, we show that behavior accounts for 25-58% of this variation. Lastly, we find that replacing the existing refrigerator with a more energy-efficient model leads to overall energy savings of approximately 11%, which is equivalent to results from behavioral interventions targeting all appliances but might not be as cost effective. Our findings have important implications for behavior-based energy conservation policies.