蓄電池劣化を考慮したカーボンアウェアな仮想発電所の最適スケジューリング
Carbon-aware optimal scheduling of a virtual power plant with energy storage degradation (原題)
Tao Wang
🤖 gxceed AI 要約
日本語
分散型PV・風力・蓄電池・需要応答を統合するVPPの日前低炭素スケジューリングモデルを提案。時間変動する排出係数と蓄電池劣化コストを目的関数に組み込み、経済性と環境性のトレードオフを明示する。ケーススタディでは従来運用比でコスト31.3%減、CO2 24.2%減、再エネ利用率100%を達成。純経済最適化比ではコスト8.15%増で追加10.13%の炭素削減となる。
English
Proposes a day-ahead low-carbon scheduling model for a VPP aggregating PV, wind, battery storage and flexible loads, incorporating time-varying grid emission factors and battery degradation costs into a unified objective. A 24-h case study cuts operating cost 31.3% and CO2 24.2% versus conventional operation, reaching 100% renewable utilization. Versus purely economic scheduling, an extra 10.13% carbon reduction is achieved at 8.15% higher cost, making the economic-environmental trade-off transparent.
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
日本では再エネ大量導入に伴う出力制御や需給調整市場の設計が進み、蓄電池併設VPPの経済性評価は重要。炭素排出係数の時間変動を織り込む手法は、非化石証書や再エネ価値の可視化、SSBJのScope 2算定高度化にも示唆を与える。
In the global GX context
As ISSB/CSRD push firms toward granular Scope 2 accounting, time-matched carbon-aware dispatch models like this show how operational scheduling can be aligned with hourly emission factors. It adds an engineering-grounded perspective to the global debate on 24/7 clean energy procurement and storage-degradation-aware asset management.
👥 読者別の含意
🔬研究者:VPP運用最適化に炭素排出係数の時間変動と蓄電池劣化を同時に組み込む定式化の実証例として参照できる。
🏢実務担当者:蓄電池併設VPPの運用計画で、経済性と炭素削減のトレードオフを定量化し経営判断に使える。
🏛政策担当者:需給調整市場や再エネ大量導入下での炭素アウェアな運用インセンティブ設計の参考になる。
📄 Abstract（原文）
With the rapid penetration of distributed photovoltaic generation, wind power, battery energy storage and flexible loads on the distribution side, virtual power plants (VPPs) are becoming an important operational paradigm for aggregating heterogeneous distributed energy resources. Conventional VPP scheduling models mainly minimize electricity-purchase costs or maximize operating revenue, while the temporal variation of grid-related carbon emissions and the life-cycle impact of frequent battery cycling are often simplified. This paper proposes a day-ahead low-carbon scheduling model for a VPP considering time-varying carbon emission factors and energy-storage degradation costs. Wind power, photovoltaic generation, battery energy storage and transferable loads are coordinated under power-balance, state-ofcharge and demand-response constraints. Electricity purchasing cost, demand-response compensation, battery degradation cost and indirect carbon emissions are incorporated into a unified objective. A 24-h case study compares conventional operation, purely economic scheduling and the proposed low-carbon strategy. Compared with conventional operation, the proposed method reduces daily operating cost from CNY 22,704.35 to CNY 15,596.98 (31.30%), decreases CO2 emissions from 17.05 t to 12.92 t (24.23%), and increases renewable-energy utilization from 93.56% to 100%. Relative to purely economic scheduling, an additional carbon reduction of about 10.13% is achieved at an operating-cost increase of about 8.15%, demonstrating a transparent trade-off between economic and environmental objectives. The proposed formulation provides a compact and engineering-oriented framework for low-carbon VPP operation under high penetration of distributed renewable energy.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1117/12.3138262first seen 2026-11-04 05:53:17 · last seen 2026-11-05 06:18:38
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