Supplementary data for "Low-Carbon Operation of EV-Integrated Renewable Energy Systems via Dynamic Pricing and Ladder-Type Carbon Trading"
動的価格設定とラダー型カーボン取引によるEV統合再生可能エネルギーシステムの低炭素運用の補足データ (AI 翻訳)
Cheng Qian, Xiangxing Yao, Minghao Guo, Moucun Yang
🤖 gxceed AI 要約
日本語
本データセットは、動的価格設定とラダー型カーボン取引を用いたEV統合再生可能エネルギーシステムの低炭素運用を扱う論文の補足資料です。24時間の負荷データ、風力・太陽光発電予測、モデルパラメータ、シナリオ比較結果が含まれ、再現性を担保します。
English
This dataset supports a manuscript on low-carbon operation of EV-integrated renewable energy systems using dynamic pricing and ladder-type carbon trading. It includes 24-hour load data, renewable forecasts, model parameters, and scenario comparison results to ensure reproducibility.
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
本論文は、動的価格設定とラダー型カーボン取引を組み合わせたEV統合エネルギーシステムの最適運用モデルを提供し、日本の電力部門脱炭素化とEV普及に示唆を与えます。
In the global GX context
This work contributes to global literature on carbon trading mechanisms in renewable energy systems, introducing a ladder-type carbon trading approach applicable to countries with carbon pricing and EV integration policies.
👥 読者別の含意
🔬研究者:Provides a modeling framework integrating dynamic pricing and ladder-type carbon trading for EV-renewable systems optimization.
🏢実務担当者:Offers insights for optimizing EV charging and renewable integration using carbon pricing mechanisms.
🏛政策担当者:Highlights the design of ladder-type carbon trading as a policy instrument for energy transition.
📄 Abstract（原文）
This dataset contains the supplementary materials supporting the manuscript entitled “Low-Carbon Operation of EV-Integrated Renewable Energy Systems via Dynamic Pricing and Ladder-Type Carbon Trading”. The archive includes: (1) 24-hour input data for the transition-season case study, including electric, heat, and cooling loads, wind power forecast, photovoltaic power forecast, and time-of-use electricity prices; (2) principal model parameters for the integrated energy system, including device capacities, storage parameters, carbon-emission and carbon-quota parameters, electric vehicle parameters, demand response parameters, and particle swarm optimization settings; (3) reported scenario-comparison results corresponding to the tables and figures presented in the manuscript. These materials are provided to support transparency and reproducibility of the reported simulation results.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.21354210first seen 2026-07-16 05:14:23 · last seen 2026-07-16 05:14:24
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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。