Crowdsourcing Behavioral Incentives for Pervasive Demand Response

Demand response (DR) refers to a set of dynamic demand mechanisms that aim to manage electricity consumption in response to supply-side signals. DR can be used for the purpose of demand regulation (e.g. to maintain voltage and frequency within safety limits) as well as for energy balance (e.g. to shift demand to off-peak periods, to curtail demand during emergency situations, or to offset fluctuations caused by less predictable energy sources such as wind or solar). Commercial and industrial energy consumers are today’s preferred candidates for participation in DR programs; they are able to contribute large reductions in demand through direct control of thermal loads (e.g. heating or refrigerators), higher predictability, lower user discomfort and relatively low installation costs. Although the residential sector makes up 20% of total energy demand and 60% of peak load demand, it still remains a relatively untapped DR resource. In order to initiate widespread adoption of DR in the residential sector and eventually make it pervasive, future behavioral incentive mechanisms for indirect DR will need to be enticing for residential consumers, effective at promoting the desired energy consumption behavior, and able to maintain long-term consumer engagement. In this work, we present our findings from a crowdsourcing experiment aimed at discovering effective behavioral incentive mechanisms for indirect DR. The experiment was performed in November 2013 and collected 55 ideas from 27 different participants. We then analyzed and classified them according to Fogg’s Behavior Model.

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