Playing with Peaks: A Game-Theoretic Comparison of Electricity Pricing Mechanisms

2025-11-13

AI Summary

To alleviate peak load pressure on power grids, this paper compares two mainstream demand response pricing mechanisms: Always-Peak pricing (AP) and Coincident-Peak pricing (CP). Using a non-cooperative game-theoretic framework, we conduct equilibrium analysis under both complete and incomplete information settings. Results show that CP weakly dominates AP under complete information but may exacerbate system-wide peak loads under incomplete information due to individual misestimation of coincident peaks. To address this trade-off between system-level coordination benefits and misallocation risks induced by information asymmetry, we propose a progressive demand cost structure—smoothing the price incentive gradient to enhance robustness. Theoretical analysis and numerical experiments demonstrate that our mechanism significantly improves peak-reduction robustness and overall efficiency. It offers a novel design principle for electricity markets that simultaneously satisfies incentive compatibility and practical implementability.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Planning, Routing, and Scheduling: Scheduling under Uncertainty

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

As electricity consumption grows, reducing peak demand--the maximum load on the grid--has become critical for preventing infrastructure strain and blackouts. Pricing mechanisms that incentivize consumers with flexible loads to shift consumption away from high-demand periods have emerged as effective tools, yet different mechanisms are used in practice with unclear relative performance. This work compares two widely implemented approaches: anytime peak pricing (AP), where consumers pay for their individual maximum consumption, and coincident peak pricing (CP), where consumers pay for their consumption during the system-wide peak period. To compare these mechanisms, we model the electricity market as a strategic game and characterize the peak demand in equilibrium under both AP and CP. Our main result demonstrates that with perfect information, equilibrium peak demand under CP never exceeds that under AP; on the other hand, with imperfect information, the coordination introduced by CP can backfire and induce larger equilibrium peaks than AP. These findings demonstrate that potential gains from coupling users'costs (as done in CP) must be weighed against these miscoordination risks. We conclude with preliminary results indicating that progressive demand cost structures--rather than per-unit charges--may mitigate these risks while preserving coordination benefits, achieving desirable performance in both deterministic and stochastic settings.

Problem

• Compares two electricity pricing mechanisms for reducing peak demand
• Analyzes equilibrium outcomes under perfect and imperfect information scenarios
• Investigates how progressive cost structures can mitigate coordination risks

Innovation

• Modeled electricity market as strategic game
• Compared anytime versus coincident peak pricing
• Proposed progressive demand cost mitigation structure