A Fair, Flexible, Zero-Waste Digital Electricity Market: A First-Principles Approach Combining Automatic Market Making, Holarchic Architectures and Shapley Theory

2025-12-15

AI Summary

Existing electricity markets struggle to achieve robust Nash equilibria under uncertainty, relying heavily on price caps, subsidies, and administrative interventions for stability. This paper proposes a physics-constrained, online event-driven market architecture that unifies wholesale and balancing layers into a hierarchical scarcity propagation system, using grid physical tightness as the pricing anchor to enable dynamic, node-to-system-level pricing and equitable rationing. We introduce the first full-stack hierarchical automated market maker (AMM) mechanism, treating uniform nodal/zonal pricing as a special case of scarcity propagation and integrating Shapley value allocation for fair cost sharing and quantification of flexibility value. Large-scale simulations demonstrate bounded-input–bounded-output stability, controllable procurement costs, zero structural waste, and significant improvements in allocation fairness and climate resilience.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Data transparency and provenance

Abstract

This thesis presents a fundamental rethink of electricity market design at the wholesale and balancing layers. Rather than treating markets as static spot clearing mechanisms, it reframes them as a continuously online, event driven dynamical control system: a two sided marketplace operating directly on grid physics. Existing energy only, capacity augmented, and zonal market designs are shown to admit no shock robust Nash equilibrium under realistic uncertainty, instead relying on price caps, uplift, and regulatory intervention to preserve solvency and security. In response, the thesis develops a holarchic Automatic Market Maker (AMM) in which prices are bounded, exogenous control signals derived from physical tightness rather than emergent equilibrium outcomes. The AMM generalises nodal and zonal pricing through nested scarcity layers, from node to cluster to zone to region to system, such that participant facing prices inherit from the tightest binding constraint. Nodal and zonal pricing therefore emerge as special cases of a unified scarcity propagation rule. Beyond pricing, the AMM functions as a scarcity aware control system and a digitally enforceable rulebook for fair access and proportional allocation under shortage. Fuel costs are recovered through pay as bid energy dispatch consistent with merit order, while non fuel operating and capital costs are allocated according to adequacy, flexibility, and locational contribution. Large scale simulations demonstrate bounded input bounded output stability, controllable procurement costs, zero structural waste, and improved distributional outcomes. The architecture is climate aligned and policy configurable, but requires a managed transition and new operational tools for system operators and market participants.

Problem

• Existing electricity markets lack shock-robust equilibrium under uncertainty
• Current designs rely on price caps and regulatory interventions for stability
• Market mechanisms fail to integrate physical grid constraints with fair allocation

Innovation

• Holarchic Automatic Market Maker for dynamic pricing
• Nested scarcity layers from node to system
• Pay-as-bid dispatch with Shapley-based cost allocation