Coordinated Market Operations for Multistakeholder Microgrids: A Local Sharing Framework Integrating Power, Carbon, Green Certificates, and Ancillary Services
マルチステークホルダーマイクログリッドのための協調市場運営：電力、炭素、グリーン証明書、および補助サービスを統合したローカルシェアリングフレームワーク (AI 翻訳)
Xiaohui Yang, Yujin Tao, Yawen Chen, Jiayi Lu, Xinlan Yi, Longxi Li
🤖 gxceed AI 要約
日本語
本論文は、電力・炭素排出権・グリーン証明書・補助サービスを統合したローカルシェアリングフレームワークを提案。二段階最適化とマルチエージェント深層強化学習を用い、中国大連の事例で19%のコスト削減と9.4%の排出削減を実証。協調と公平性を向上する。
English
This paper proposes a local sharing framework integrating power, carbon allowances, green certificates, and ancillary services for clustered microgrids. Using bilevel optimization and multiagent deep reinforcement learning, a Dalian case study shows 19% cost reduction and 9.4% emission reduction, improving coordination and fairness.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国の事例だが、日本でもコミュニティマイクログリッドやJ-クレジットとの統合市場設計の参考になる。特に、複数主体間の協調メカニズムは日本のエネルギー地産地消政策に示唆を与える。
In the global GX context
This paper contributes to global energy transition by proposing an integrated market framework for local energy systems. The multi-agent RL approach for strategic bidding in combined power-carbon-certificate markets is novel and applicable to regions developing distributed energy markets.
👥 読者別の含意
🔬研究者:The bilevel optimization and MADDPG methodology for multi-market coordination is a significant methodological contribution.
🏢実務担当者:The framework can guide the design of local energy markets for microgrid clusters, integrating carbon and green certificate trading.
🏛政策担当者:The results demonstrate the benefits of integrated market mechanisms for cost and emission reductions, informing local energy policy.
📄 Abstract（原文）
Clustered microgrids, capable of hosting high-penetration of renewable generation, are increasingly viewed as building blocks of an intelligent, low-carbon Energy Internet. However, their collective potential is undermined when operating in isolation. Furthermore, segregated markets for power, carbon allowances, tradable green certificates, and ancillary services (P-C-T-A) fragment price signals, causing inefficient dispatch, value loss, and weak cross-stakeholder coordination. To coordinate multistakeholder microgrid clusters in a joint P-C-T-A market, a local sharing framework embedded with the carbon responsibility sharing concept is developed, formulated as a bilevel optimization that captures strategic interactions between self-interested microgrids and the joint market center, while ensuring carbon responsibility’s fair allocation. At the lower-level market, P-C-T-A products are jointly cleared via a continuous double auction mechanism. To solve this complex equilibrium, the Multiagent Deep Deterministic Policy Gradient algorithm is employed to empower microgrids to learn optimal bidding strategies under incomplete information. Results from a case study of heterogeneous microgrids in Dalian, China, demonstrate that the proposed framework outperforms alternative market architectures and carbon responsibility allocation schemes, yielding minimum cost and emission reductions of 19.00% and 9.40%, respectively, while enhancing distributive fairness and coordination efficiency. The reliability and robustness of the framework are systematically validated via multidimensional tests targeting parameter sensitivity, structural validity, and algorithmic stability. This research provides a practical blueprint for the market design and engineering management of community- and park-level microgrids, while contributing a novel theoretical paradigm for coordinated governance in multistakeholder Energy Internet systems.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1109/tem.2026.3684943first seen 2026-05-15 17:24:11
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