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Optimizing Electricity Sharing from Generation and Storage within District-based Renewable Energy Communities

地区ベースの再生可能エネルギーコミュニティにおける発電と貯蔵からの電力共有の最適化 (AI 翻訳)

Girona-Badia, Marc, Asensio Bosch, Jaume, Laguna, Gerard, Moreno Kübel, Pablo Alexander, Cipriano, Jordi, Luna, Alvaro

Zenodoプレプリント2026-07-23#再生可能エネルギーOrigin: EU経営インパクト: コスト削減対象セクター: power
DOI: 10.5281/zenodo.21510701
原典: https://zenodo.org/records/21510701
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🤖 gxceed AI 要約

日本語

本論文は、地区ベースの再生可能エネルギーコミュニティ(REC)内で、太陽光発電と集中バッテリー貯蔵を調整するための統合最適化フレームワークを提示する。軽量線形計画法を用いて、共有エネルギー資産の管理を最適化し、自己消費を最大化しつつ電力調達コストを削減する。実データを用いた検証により、統合最適化が発電・貯蔵資産の利用率を向上し、経済性を改善することを示す。

English

This paper presents an integrated optimization framework for coordinating photovoltaic generation and centralized battery storage within district-based Renewable Energy Communities (RECs). Using a lightweight linear programming formulation, it optimizes the management of shared energy assets to maximize self-consumption and reduce electricity procurement costs. Validation with real data from a 12-dwelling REC shows improved utilization and economic performance.

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

日本でも地域エネルギーコミュニティやエネルギーの地産地消が推進されており、本フレームワークは共有資産の効率的運用に示唆を与える。ただし、日本の電力市場や規制環境への適合には追加検討が必要。

In the global GX context

As the EU promotes Renewable Energy Communities via RED II, this framework provides a scalable, computationally efficient solution for coordinating shared generation and storage. It aligns with global trends toward decentralized energy systems and community self-consumption.

👥 読者別の含意

🔬研究者:This work offers a lightweight LP formulation for joint optimization of PV and battery in RECs, with potential extension for larger-scale or multi-community systems.

🏢実務担当者:REC operators and energy cooperatives can use the proposed framework to improve self-consumption and reduce costs by coordinating shared assets.

🏛政策担当者:The paper demonstrates how regulatory requirements for advance energy-sharing coefficients can be met with a simple optimization, informing REC policy design.

📄 Abstract(原文)

This paper presents an integrated optimisation framework for coordinating photovoltaic generation and centralised battery storage within district-based Renewable Energy Communities (RECs). Developed within the Horizon Europe DEDALUS project, the proposed approach addresses the challenge of jointly managing shared renewable generation and energy storage to maximise community self-consumption while reducing electricity procurement costs. By coordinating multiple shared assets within a single optimisation process, the framework supports more efficient and equitable operation of community energy systems. The proposed framework simultaneously determines electricity sharing factors and a preliminary battery operating strategy using a lightweight linear programming formulation. The optimisation incorporates community-wide electricity demand, photovoltaic generation, battery operating constraints and electricity market prices, while introducing an allocation constraint that distributes available renewable energy more evenly among participants. The methodology is designed to comply with regulatory frameworks requiring energy-sharing coefficients to be defined in advance, enabling practical implementation without relying on computationally intensive optimisation techniques. The approach is validated using real operational data from a Renewable Energy Community comprising twelve residential dwellings, a shared photovoltaic installation and a centralised battery system. The results demonstrate that integrated optimisation improves the utilisation of both generation and storage assets, enhances self-consumption and exploits weekly electricity price variations to increase the overall economic performance of the community. The proposed framework provides a scalable and computationally efficient solution for the coordinated management of shared energy resources in future district-scale Renewable Energy Communities.      

🔗 Provenance — このレコードを発見したソース

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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。