gxceed
← 論文一覧に戻る

Development of a Preliminary Renewable Energy Planning Tool with Storage and Carbon Footprint Assessment

蓄電とカーボンフットプリント評価を組み込んだ予備的な再生可能エネルギー計画ツールの開発 (AI 翻訳)

Xumiao Lin, Joana Correia, Miguel Marques, Ana Foles, José Silva, Teresa Batista, Carmen Luisa Vásquez Stanescu, Lucas Marinho, Fernando Barros

Designs📚 査読済 / ジャーナル2026-05-07#再生可能エネルギーOrigin: EU
DOI: 10.3390/designs10030048
原典: https://doi.org/10.3390/designs10030048

🤖 gxceed AI 要約

日本語

本論文は、蓄電とカーボンフットプリント評価を組み込んだ再生可能エネルギー計画のための意思決定支援システムを提案する。ポルトガルのシネス港をケーススタディとして、太陽光と風力の資源評価を検証し、既存ツールと比較して最大25%の誤差を確認した。データが少ない初期段階での投資判断に有効なツールを提供する。

English

This paper presents a decision support system for renewable energy planning that integrates energy storage and carbon footprint assessment. Validated with a case study at the Port of Sines, Portugal, solar estimates deviated up to 14% and wind estimates up to 25% compared to benchmark tools. The tool facilitates early-stage sizing and investment decisions under data scarcity.

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、港湾や工業団地での再エネ導入計画に応用可能。SSBJや有報での再エネ比率開示の裏付けとして、簡易試算ツールの重要性が高まる中、本手法は参考になる。

In the global GX context

This tool addresses a common gap in preliminary renewable energy planning, offering a validated workflow that balances complexity and practicality. It is relevant for global practitioners seeking rapid screening tools for solar and wind investments, especially in industrial or port settings.

👥 読者別の含意

🔬研究者:The validated methodology and deviation analysis provide a benchmark for similar tool development in other regions.

🏢実務担当者:The tool can be used by industrial sites or ports for initial renewable energy feasibility assessments without extensive data.

📄 Abstract（原文）

The global transition toward a low-carbon economy has accelerated the adoption of renewable energy sources. This paper presents the development of a model-based electronic Decision Support System for renewable energy planning, incorporating energy storage and carbon footprint assessment. The tool assists stakeholders in the preliminary evaluation of local wind and solar resources. To validate the model’s credibility, a comparative analysis was conducted, using the Port of Sines, Portugal, as an industrial case study. Solar energy estimations were benchmarked against PVSyst, while wind energy simulations were compared with an INEGI technical study. Results indicate consistency in solar estimates, with maximum deviations of 14% for fixed installations and 13% for vertical barriers, primarily due to terrain orography that was not yet integrated into the algorithm. Regarding wind energy, deviations reached 19% to 25%, largely resulting from the use of aggregated mean values in the reference data and generic turbine models. Overall, this work contributes to energy engineering by formalizing a validated workflow that facilitates early-stage sizing and strategic investment decisions under conditions of data scarcity. The tool proves effective for rapid screening of promising investment options while maintaining a balance between computational complexity and practical usability.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。

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。