ハイブリッドAC/DC配電網における電池健全性を考慮した動的柔軟性管理（コード・データ）
Battery Health-Aware Dynamic Flexibility Management for Hybrid AC/DC Distribution Networks (code and data) (原題)
Kamoona, Mustafa A., Mauricio, Juan Manuel
🤖 gxceed AI 要約
日本語
蓄電池の健全性（SOH）と日次劣化許容量を組み込んだ動的柔軟性管理（DFM）フレームワークを提案。CIGRE低圧ベンチマークに蓄電池・PV・風力を追加した系統で、ロールホライズンMILPにより運用制約として柔軟性エンベロープを課す。100回のモンテカルロで再エネ抑制を87.9%削減、電池劣化消費を29.7%削減、系統制約違反を70%から33%に低減した。
English
A battery health-aware Dynamic Flexibility Management framework computes a time-varying charge/discharge flexibility envelope integrating SOH, daily degradation allowance, uncertainty reserves, and AC/DC deliverability, imposed as a constraint in a rolling-horizon MILP EMS. Tested on the CIGRE low-voltage benchmark with BESS, PV and wind, it cuts renewable curtailment by 87.9%, battery health consumption by 29.7%, and constraint violations from 70% to 33% across 100 Monte Carlo runs.
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
再エネ大量導入下での系統柔軟性と蓄電池劣化の両立は、日本の出力制御対策や系統用蓄電池ビジネス、GX推進における電力システム脱炭素の実務課題に直結する。
In the global GX context
Grid flexibility with battery degradation awareness speaks to global decarbonization of power systems and the storage economics underpinning transition finance for renewables integration.
👥 読者別の含意
🔬研究者:蓄電池劣化と系統柔軟性を統合したMILP定式化と再現可能なベンチマークとして参照価値が高い。
🏢実務担当者:蓄電池運用の劣化コストと再エネ抑制削減を両立する運用設計の示唆を得られる。
🏛政策担当者:出力制御対策や蓄電池導入支援策の効果評価に資する系統運用エビデンスとなる。
📄 Abstract（原文）
Research Release — v1.0.2 This release provides the research code, numerical datasets, and figures accompanying the study "Battery Health-Aware Dynamic Flexibility Management for Hybrid AC/DC Distribution Networks." What changed in v1.0.2 This is a manuscript-title and documentation alignment update for submission to the Journal of Energy Storage . The repository title, citation metadata ( CITATION.cff , version 1.0.2), and citation instructions now use the revised study title, and the Zenodo concept DOI is listed in the README. No source code, datasets, figures, model parameters, or numerical results have changed with respect to v1.0.1. About the framework The battery health-aware Dynamic Flexibility Management (DFM) framework computes, at every supervisory interval, a time-varying charge/discharge flexibility envelope that integrates energy availability, state of health, a daily degradation allowance, directional probabilistic uncertainty reserves, and AC/DC network deliverability. The envelope is imposed as an operating constraint of a rolling-horizon mixed-integer linear programming (MILP) energy management system. The implementation is evaluated on the hybrid CIGRE low-voltage benchmark (Topology-3), extended with battery energy storage, photovoltaic generation, and wind power. Release Contents Python implementation of the DFM framework and energy management system. Simulation configurations and numerical datasets. Conventional and degradation-aware benchmark strategies. Ablation, sensitivity, and Monte Carlo analyses. Research figures and supporting visualization materials. Documentation and instructions for reproducibility. Across 100 Monte Carlo realizations, DFM reduces renewable curtailment by 87.9%, battery health consumption by 29.7%, and energy cost by 2.3% relative to the degradation-aware benchmark, while reducing the incidence of network-constraint violations from 70% to 33%. Archive Zenodo concept DOI (all versions): https://doi.org/10.5281/zenodo.24088866 Previous version v1.0.1: https://doi.org/10.5281/zenodo.24106846
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/24230772first seen 2026-11-15 04:15:52
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