Behavioral Prosumers in Transactive Energy: Loss Aversion, Time Preferences, and Social Norm Feedback

As Jing et al. (2022) note, prosumers in local energy markets depart from rational benchmarks. Xie et al. (2024) model limited rationality with psychological accounts and reinforcement learning for suppliers; we adapt this to household prosumers deciding when to discharge storage or sell, embedding: (i) loss aversion over battery state-of-charge (treating discharge as a “loss” of future security; Wang, 2024), (ii) present-biased discounting of future price opportunities, and (iii) social-norm feedback about neighbors’ “green” behavior (Edirneligil & Tanhan, 2024) and sustainable promotion cues (Li, 2024). We pair a field experiment on a pilot platform with randomized defaults (auto-discharge vs auto-save), norm messages (percent neighbors participating/carbon saved), and framing (loss vs gain). Process data (latency to override defaults) inform user-level DDMs (Gopnarayan et al., 2023) that feed into training of limited-rationality RL agents. Novelty: unifies three behavioral forces in a market design and simulates macro outcomes via agent-based methods (Gomes, 2022), then validates in the field. Impact: improves market efficiency and decarbonization by aligning mechanism design with actual household psychology; provides regulators with evidence on when “green” defaults help or backfire.

References:

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