On the Smart Coordination of Flexibility Scheduling in Multi-carrier Integrated Energy Systems

2025-09-03

AI Summary

To address the challenges of high coordination complexity, poor privacy preservation, and limited scalability arising from the proliferation of flexible assets in multi-carrier integrated energy systems (MIES), this paper proposes a market-auction-inspired model coupling framework. The method integrates distributed optimization with an iterative price-response mechanism to enable autonomous participation, privacy-preserving operation, and large-scale coordinated scheduling of flexibility resources. Extensive multi-scale experiments demonstrate that the proposed approach achieves near-optimal economic performance and renewable energy curtailment reduction while significantly improving computational scalability. The framework has been implemented in an open-source software tool, enabling system operators and regulators to conduct mechanism design and policy simulation without sharing sensitive operational data. This work provides a practical, deployable technical foundation for the transition toward next-generation electricity markets and multi-energy synergy.

Technology Category

• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Multiagent Systems: Mechanism Design
• Search and Optimization: Distributed 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
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Coordinating the interactions between flexibility assets in multi-carrier integrated energy systems (MIES) can lead to an efficient integration of variable renewable energy resources, and a cost-efficient energy transition. However, the proliferation of flexibility assets and their participation in active demand response increases the complexity of coordinating these interactions. This paper introduces different approaches to model the coordination of flexibility scheduling in MIES. We propose a market auction-inspired model coupling approach to address the challenges of preserving the autonomy and privacy of flexibility providers, and the issue of scalability. We benchmark our approach against co-optimization and an iterative price-response method by conducting experiments with varying problem sizes and computing infrastructure. We show that our approach scales well and is suitable for modeling flexibility in large-scale energy systems in a more realistic way. From an optimality standpoint, the flexibility dispatch schedules and electricity prices are ``near-optimal". Our methodology is implemented as a new open-source software, which offers several practical applications. For example, flexibility providers and network operators can couple their models to simulate the interaction between their systems without disclosing confidential information; policy regulators can use it to investigate new market design and regulations to optimize the utilization of flexibility in MIES.

Problem

• Modeling coordination of flexibility scheduling in multi-carrier energy systems
• Addressing autonomy and privacy preservation for flexibility providers
• Solving scalability challenges in large-scale energy system coordination

Innovation

• Market auction-inspired model coupling approach
• Preserves autonomy and privacy of providers
• Scalable for large-scale energy systems