入力データセット：時間帯別料金下での系統連系型太陽光・風力・蓄電池システムの価格シグナル縮退と炭素配慮型ディスパッチ
Input dataset: Price-signal degeneracy and carbon-aware dispatch of grid-connected photovoltaic, wind and battery systems under time-of-use tariffs (原題)
Ilyes Tegani, Hamza Afghoul, Salah S. Alharbi, Saleh Alharbi, Salem Tegani
🤖 gxceed AI 要約
日本語
系統連系型ハイブリッド再生可能エネルギーシステム（太陽光50kW、風力60kW、蓄電池100kWh）の炭素配慮型確率予測ディスパッチの研究用入力データセットを提供する。時間帯別料金下で輸出報酬とオフピーク輸入料金が同額（0.08 EUR/kWh）のため、コスト最小化制御では炭素強度が2倍異なる運用方針間で無差別となり、年間排出量が10.6%変動し得る。炭素シャドープライス0.02 EUR/kgを導入することで無差別性が解消され、排出量10.6%削減と運用コスト2.7%削減を同時達成する。データセットは再現可能な生成器と全結果ファイルを含む。
English
This deposit provides a complete input dataset and reproducible generator for a study of carbon-aware stochastic predictive dispatch in a grid-connected hybrid renewable plant (50 kW PV, 60 kW wind, 100 kWh battery) under a time-of-use tariff. The study identifies a price-signal degeneracy: export remuneration and off-peak import tariff are both 0.08 EUR/kWh, making cost-minimizing controllers indifferent between policies with 10.6% difference in annual emissions. Introducing a carbon shadow price of 0.02 EUR/kg resolves the indifference, cutting emissions by 10.6% and operating cost by 2.7% simultaneously. The dataset includes all exogenous inputs, results, and figures, with synthetic profiles spanning three weather regimes.
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
日本の再生可能エネルギー導入拡大と蓄電池活用が進む中、時間帯別料金や炭素価格の設計が重要。本研究成果は、日本のFIT制度や卸電力市場における価格シグナルの設計に示唆を与え、SSBJ開示における炭素会計の精緻化にも貢献し得る。
In the global GX context
This study offers a novel perspective on carbon-aware dispatch in hybrid renewable systems, highlighting how price signals can create degeneracy that undermines emissions reduction. It provides a reproducible dataset and methodology that can inform global discussions on carbon pricing, grid integration, and the design of time-of-use tariffs. The findings are relevant for ISSB-aligned disclosure and transition finance, as they demonstrate the importance of carbon shadow pricing in operational decisions.
👥 読者別の含意
🔬研究者:Provides a reproducible dataset and methodology for studying carbon-aware dispatch, with insights into price-signal degeneracy and the role of carbon shadow pricing.
🏢実務担当者:Offers a practical approach to integrating carbon costs into dispatch decisions for hybrid renewable systems, potentially reducing emissions and operating costs.
🏛政策担当者:Highlights the need for careful tariff design to avoid price degeneracies that can lead to suboptimal carbon outcomes, informing energy policy and carbon pricing mechanisms.
📄 Abstract（原文）
This deposit contains the complete input dataset and a reproducible generator for a study of carbon-aware risk-constrained stochastic predictive dispatch in a grid-connected hybrid renewable plant comprising a 50 kW photovoltaic array, a 60 kW wind turbine and a 100 kWh lithium-ion battery operating under a four-period time-of-use tariff. The associated study identifies a degeneracy in the price signal. Export remuneration and the off-peak import tariff are both 0.08 EUR/kWh, so charging the battery from local surplus and charging it from the overnight grid carry identical cost while differing by a factor of two in carbon intensity. A cost-minimising controller is therefore indifferent across a set of dispatch policies whose annual emissions differ by 10.6 percent. Admitting a carbon shadow price of 0.02 EUR/kg resolves the indifference and lowers annual emissions by 10.6 percent and annual operating cost by 2.7 percent at the same time. The coincidence of the two prices is a property of the deposited tariff rather than an oversight, and it is the object of the study. The generator, HRES_Dataset_Generator.m, regenerates every exogenous input: the ground-truth photovoltaic, wind and demand profiles for three weather regimes; the tariff with its period index; the export price; the diurnal grid carbon intensity; and the Monte Carlo forecast uncertainty ensembles. The profiles reproduce bit-for-bit under the seeding protocol documented in the README. It requires base MATLAB R2024a with no toolboxes. The deposit also contains the numerical results underlying every table and figure of the associated article and its supplementary file: ten comma-separated result files covering comparative performance, paired significance tests, annualised techno-economics, scenario reduction fidelity, forecast-error stress response, non-anticipativity ablation, carbon accounting under two conventions, the cost-carbon frontier, risk-measure degeneracy and the lifecycle carbon assessment; the per-seed campaign record over 30 independent realisations in each of three regimes; and thirty-four vector figures, seventeen of which appear in the article and seventeen in the supplementary file. All profiles are synthetic. They are constructed to span surplus-dominated, deficit-dominated and volatility-dominated operation rather than to reproduce any specific location, and the grid carbon intensity is an average-factor model.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.21874938first seen 2026-08-31 04:53:27
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