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arXiv · 2609.37600

Quantifying EnergyNet performance: a simulation-based framework for decentralized energy networks

Abstract

Power transmission and distribution infrastructure connects generation with consumers. Extreme weather, infrastructure failures, and geopolitical conflicts increasingly disrupt these connections, leaving large groups without electricity until service is restored. Local generation, storage, and controllable loads pose challenges but also enable new ways to organize energy systems. EnergyNet is a decentralized architecture of interconnected power electronic Energy Routers. Each coordinates local loads, generation, storage, and grid connections. Bidirectional Energy Links enable exchange between routers, while the Energy Protocol communicates needs and availability to coordinate transfers. EnergyNet can operate with or without the public grid. This paper develops a quantitative framework for modeling and evaluating EnergyNet. It represents topology, prioritized loads, generation, storage, grid connections, links, and component limits. Receding-horizon optimization calculates energy allocation and exchange, supporting also disturbance and reliability analysis. A three-router case illustrates energy sharing and islanded operation. The framework then models a Stanford University campus microgrid and an off-grid microgrid in Half Moon Bay. Under low-solar conditions, electric bus visits support the off-grid microgrid while preserving transport service. Finally, the paper models an EnergyNet under construction in Lund, Sweden, comprising ten buildings and 278 apartments. Full service is maintained in summer and winter and after the loss of one grid interface or Energy Link. Losing two links partitions the network; service in the island depends on local resources and repair time. Reliability screening identifies partitioning as rare but credible. Monte Carlo analysis shows full critical service in sampled summer conditions and median continuous critical service of approximately 92% in winter.

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BibTeXRIS

Max Collins, Jonas Birgersson, Marc A. Weiss, Jimmy Chen, Marc Z. Jacobson, Newsha K. Ajami, Daniel Kammen, Tomas Kåberger, Franklin Carrero-Martínez, Joakim Wernberg, Michael Menser, Henrik Ny, Lou Riordan, Jill G. Ferguson. 2026-09-29. Quantifying EnergyNet performance: a simulation-based framework for decentralized energy networks. https://arxiv.org/abs/2609.37600

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