A Physics-Aware Real-Time Matching and Asynchronous Settlement Framework for Distributed Energy Storage Services

Smart grids require real-time ancillary services from large-scale distributed energy storage (DES), creating a conflict between second-scale physical response needs and the slow confirmation of trust mechanisms like blockchain. Traditional VPPs lack scalability and trust for massive participation, while decentralized approaches struggle with mismatched time scales. We propose a framework that decouples real-time dispatch from asynchronous settlement. An off-chain matcher uses a physics-aware model, including a novel “service holding time” (Tservice) constraint and power (kW) envelopes, for fast assignments. A separate on-chain proof-of-stake (PoS) layer handles incentives and penalties (slashing) asynchronously. We formulate the MILP dispatch problem and provide a fast online heuristic alongside a MINLP decomposition benchmark. Co-simulations (IEEE 33-node) show that our scheme significantly outperforms baselines in success rate and latency, is robust against non-compliant nodes due to the PoS mechanism, and thereby offers a scalable and trustworthy solution.

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Publication Details

Journal
AI
Published
2026-03-12
DOI
https://doi.org/10.3390/ai7030109
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
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article

A Physics-Aware Real-Time Matching and Asynchronous Settlement Framework for Distributed Energy Storage Services

Fan Liang, Xin Zhang
AI
Smart Grid Energy Management
article

A Physics-Aware Real-Time Matching and Asynchronous Settlement Framework for Distributed Energy Storage Services

Fan Liang, Xin Zhang
article en

Abstract

Smart grids require real-time ancillary services from large-scale distributed energy storage (DES), creating a conflict between second-scale physical response needs and the slow confirmation of trust mechanisms like blockchain. Traditional VPPs lack scalability and trust for massive participation, while decentralized approaches struggle with mismatched time scales. We propose a framework that decouples real-time dispatch from asynchronous settlement. An off-chain matcher uses a physics-aware model, including a novel “service holding time” (Tservice) constraint and power (kW) envelopes, for fast assignments. A separate on-chain proof-of-stake (PoS) layer handles incentives and penalties (slashing) asynchronously. We formulate the MILP dispatch problem and provide a fast online heuristic alongside a MINLP decomposition benchmark. Co-simulations (IEEE 33-node) show that our scheme significantly outperforms baselines in success rate and latency, is robust against non-compliant nodes due to the PoS mechanism, and thereby offers a scalable and trustworthy solution.

AIVol. 7(3)
Sam Houston State University (US), China Energy Engineering Corporation (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 26%
Smart Grid Energy Management
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