Market Power and Platform Design in Decentralized Electricity Trading

2026-03-20

AI Summary

This study investigates how the design of decentralized electricity trading platforms influences prosumers’ strategic behavior and market efficiency. By formulating a finite-horizon dynamic game model integrated with a multi-agent differentiable clearing framework, perfect conditional ε-equilibrium analysis, and Cournot-style market power modeling, the paper quantifies strategic interactions among prosumers under varying pricing mechanisms, information disclosure policies, and energy storage ownership structures, and their impacts on grid settlement costs and user welfare. Results show that strategic behavior in the baseline scenario increases settlement costs by approximately 6%, whereas optimized platform design or decentralized storage ownership substantially mitigates strategic supply distortions. Despite such strategic actions, the platform still reduces electricity bills for passive users by about 40%, with only an 8% erosion of these gains, demonstrating the mechanism’s effectiveness in enhancing both efficiency and equity.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Distributed Search

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

This paper studies how platform design shapes strategic behavior in decentralized electricity trading. We develop a finite-horizon dynamic game in which photovoltaic- and battery-equipped players ("prosumers") trade on a platform that maps aggregate imports and exports into internal buy and sell prices. We establish existence of a perfect conditional epsilon-equilibrium and characterize a Cournot-like market-power mechanism in an observable-types benchmark of the game: because the producer price is decreasing in aggregate exports, strategic prosumers withhold supply and underutilize storage relative to the price-taking benchmark. To quantify these effects, we use a multi-agent computational framework that exploits the differentiable structure of the platform's clearing rule to compare planner, price-taking, and strategic outcomes under alternative pricing mechanisms. In our baseline calibration, strategic play raises grid settlement cost by about 6 percent relative to price-taking. The magnitude of the distortion depends strongly on platform design: some designs can largely eliminate strategic incentives, while increased competition in storage ownership sharply reduces withholding, with most of the distortion disappearing once storage is split across more than three owners. We also find that information disclosure can improve competitive coordination but also increase the market power effects. Despite these distortions, the platform remains highly valuable overall, reducing a passive consumer's annual electricity bill by roughly 40 percent relative to exclusive grid settlement, with strategic behavior clawing back only about 8 percent of that saving. The results show that pricing rules, information disclosure, and ownership structure determine how much of the gains from decentralized electricity trading are realized.

Problem

• market power
• decentralized electricity trading
• platform design
• strategic behavior
• prosumers

Innovation

• decentralized electricity trading
• dynamic game
• differentiable clearing rule
• multi-agent computation
• market power