Prosumer Behavior: Decision Making with Bounded Horizon

TL;DR

This paper introduces a behavioral model for prosumer energy decision-making that incorporates a bounded time horizon, better fitting real-world data than traditional expected utility theory.

Contribution

It proposes a new bounded horizon model for prosumer decisions, extending expected utility theory to better reflect human decision-making in energy markets.

Findings

Bounded horizon of 4-5 days fits data better than unbounded models.

The new model captures prosumer behavior more accurately.

Traditional EUT is less effective in ongoing energy decision contexts.

Abstract

Most studies of prosumer decision making in the smart grid have focused on single, temporally discrete decisions within the framework of expected utility theory (EUT) and behavioral theories such as prospect theory. In this work, we study prosumer decision making in a more natural, ongoing market situation in which a prosumer has to decide every day whether to sell any surplus energy units generated by the solar panels on her roof or hold (store) the energy units in anticipation of a future sale at a better price. Within this context, we propose a new behavioral model that extends EUT to take into account the notion of a bounded temporal horizon over which various decision parameters are considered. Specifically, we introduce the notion of a bounded time window (the number of upcoming days over which a prosumer evaluates the probability that each possible price will be the highest) that prosumers implicitly impose on their decision making in arriving at hold or sell decisions. The new behavioral model assumes that humans make decisions that will affect their lives within a bounded time window regardless of how far into the future their units may be sold. Modeling the utility of the prosumer using parameters such as the offered price on a day, the number of energy units the prosumer has available for sale on a day, and the probabilities of the forecast prices, we fit both traditional EUT and the proposed behavioral model with bounded time windows to data collected from 57 homeowners over 68 days in a simulated energy market. Each prosumer generated surplus units of solar power and had the opportunity to sell those units to the local utility at the price set that day by the utility or hold the units for sale in the future. For most participants, a bounded horizon in the range of 4-5 days provided a much better fit to their responses than was found for the traditional (unbounded) EUT model