Multi-timescale rolling optimization for micro-energy systems incorporating carbon trading and multi-type demand response
炭素取引と多種需要応答を統合したマイクロエネルギーシステムの多時間スケールローリング最適化 (AI 翻訳)
Zhonglei Jiao, Dejian Yang, Fenghe Jin
🤖 gxceed AI 要約
日本語
本論文は、炭素取引と需要応答を統合したマルチタイムスケールローリング最適化戦略を提案。ソース側にインセンティブ・ペナルティ付き段階的炭素取引メカニズム、負荷側に価格・インセンティブベース需要応答モデルを導入し、総排出量と運用コストの同時最適化を実現。ケーススタディで有効性を検証。
English
This paper proposes a multi-timescale rolling optimization strategy integrating carbon trading and multi-type demand response for low-carbon economic operation of micro-energy systems. It introduces an incentive-penalty stepped carbon trading mechanism on the supply side and a comprehensive demand response model on the demand side to simultaneously optimize total carbon emissions and operational costs. Case studies validate its effectiveness.
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
日本ではカーボンプライシング導入が進む中、本論文のように需要応答と組み合わせたエネルギーシステム最適化はGX実装において重要。提案手法は日本の地域エネルギー管理や需給調整市場への応用可能性を示唆する。
In the global GX context
As global carbon pricing mechanisms expand, integrating carbon trading with demand-side management offers a practical approach for energy system optimization. This paper's multi-timescale model is relevant for countries implementing carbon markets and smart grid demand response programs, contributing to operational low-carbon transition strategies.
👥 読者別の含意
🔬研究者:炭素市場と需要応答の統合最適化に興味のある研究者にとって、新しいマルチタイムスケールモデルを提供する。
🏢実務担当者:エネルギーシステム運用最適化の実務者は、段階的炭素取引と需要応答の組み合わせを参考に、低炭素経済運転の実装に活用できる。
🏛政策担当者:政策立案者は、炭素市場メカニズムと需要側対策の連携による排出削減効果の評価に有用な知見を得られる。
📄 Abstract（原文）
Under the background of the new energy security strategy, promoting the transformation of micro-energy systems (MES) toward low-carbon (LC) economic operation has become a crucial development direction in the energy field. Existing research has achieved certain progress in the economic optimization and LC development of MES separately. However, methods for the co-optimization of economy and LC performance still exhibit deficiencies, struggling to meet the compound requirements for LC economic operation of the system. To address this, this paper proposes a multi-timescale rolling optimization strategy that integrates multi-type demand response (DR) and an incentive-penalty stepped carbon trading mechanism (IP-SCTM). First, a source-load bilateral coordination approach is adopted. On the source side, an IP-SCTM is introduced, which employs a bidirectional stepped pricing scheme to provide two-way incentives for reducing total carbon emission (CE). On the load side, accounting for the varying response characteristics of demand-side resources across different timescales, a comprehensive multi-type DR model encompassing price-based and incentive-based DR is constructed to reduce the system's comprehensive energy consumption cost, synergistically achieving dual optimization of total CE and operational costs. Second, at the system operation level, a multi-timescale rolling optimization model is established. During the intra-day scheduling phase, a rolling horizon strategy is utilized to optimize unit output variations, comprehensively enhancing the operational economy and LC performance of the MES. Finally, the case study analysis verifies the effectiveness of the proposed method in achieving LC economic operation for the MES.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1063/5.0306156first seen 2026-05-05 22:49:11
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。