Randomized trial analyzes pricing strategies in energy storage, suggesting improvement in market participation.
The increasing deployment of distributed energy storage systems (ESSs) presents new opportunities to enhance power system flexibility and enable innovative market participation models. However, many small-scale energy storage system assets remain underutilized due to fragmented ownership, uncertainty in market prices and revenue opportunities, as well as regulatory and operational constraints, and heterogeneous decision making behaviors. To address these challenges, this paper proposes an enhanced energy storage as a service (ESaaS) framework that enables distributed ESS owners to lease idle storage capacity to a centralized platform for coordinated participation in multiple grid support services. The proposed platform aggregates the distributed ESS capacity and allocates it across several value streams. Unlike conventional approaches that assume fully rational agents, this work incorporates behavioral decision making dynamics using prospect theory (PT), which captures loss aversion, asymmetric risk perception, and the subjective valuation of uncertain outcomes. The interaction between the ESaaS operator and ESS owners is formulated as a bi-level optimization problem, where the upper level determines leasing prices and operational strategies across multiple services while the lower-level models ESS owner participation decisions. Prospect theory is integrated at both decision layers to capture the behavioral preferences of the ESaaS operator and ESS owners under uncertainty. The resulting mixed-integer bi-level model is solved using a modified reformulation-and-decomposition approach that incorporates a nested column-and-constraint generation (NC&CG) method to ensure computational tractability. Numerical studies demonstrate that behavioral decision modeling significantly influences pricing strategies and the overall profitability of both the ESaaS platform and the participating energy storage system owners.
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Parvar et al. (2026) studied this question.
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