A Reproducible Workflow for Regionalisation of European Network Expansion Scenarios
欧州ネットワーク拡張シナリオの地域化のための再現可能なワークフロー (AI 翻訳)
Eric
🤖 gxceed AI 要約
日本語
本論文は、欧州電力系統計画のためのノード別入力データを作成する再現可能な前処理ワークフローを提案する。TYNDP 2024のデータとPyPSAベースのグリッドモデルを組み合わせ、風力・太陽光の発電ポテンシャルや水力流入量をラスタから算出し、負荷や電源容量をノードに按分する。これにより、一貫性のある時系列データが生成され、感度分析や検証が容易になる。
English
This paper presents a reproducible preprocessing workflow for creating nodal input data for European power system planning. It combines TYNDP 2024 data with a PyPSA-based grid model, generating renewable potentials and hydro inflows from rasters, and disaggregating national scenario quantities to nodes using transparent allocation rules. The workflow produces consistent timeseries data supporting sensitivity analysis and validation of grid optimization studies.
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GX文脈では、本手法は再現可能で透明性の高い系統計画データ作成の参考となる。日本の長期エネルギー需給見通しや系統拡張計画においても、同様の手法を適用することで信頼性と国際比較可能性が向上する可能性がある。
In the global GX context
Globally, this workflow addresses the need for reproducible, open-source data pipelines in power system modeling. It supports transparent scenario analysis for grid expansion, aligning with best practices in energy transition planning and enabling validation of decarbonization pathways.
👥 読者別の含意
🔬研究者:Provides a reproducible method for generating consistent nodal input data for European power system optimization models.
🏢実務担当者:Grid planners and consultants can use this workflow to produce transparent, scenario-consistent datasets for network expansion studies.
📄 Abstract（原文）
<title>Abstract</title> <p> European power system planning and operation studies require spatially consistent input data that connect national scenario assumptions, weather-dependent renewable profiles, hydro inflows, and detailed grid representations. This paper presents a reproducible preprocessing workflow for deriving nodal input data for large-scale European unit commitment and optimal power flow analyses based on capacity and transmission expansion scenarios from the ten-year network development plan by ENTSO-E and ENTSO-G. The workflow combines TYNDP 2024 National Trends data with a <italic>PyPSA</italic> -based grid model, extended by selected grid expansion assumptions and maps all relevant demand, generation, storage, and flexibility data to the nodes of a reduced grid with user-specific size. The methodology covers two complementary spatial transformations. First, raster-based renewable energy potentials, capacity factors, and hydro inflow profiles are generated using an extended approach based on <italic>Atlite</italic> functionalities and aggregated to grid nodes using technology-specific availability masks. Second, national scenario quantities, including load, thermal generation, hydro capacities, other renewable and non-renewable technologies, battery storage, and demand-side response, are disaggregated to nodes using transparent allocation rules based on existing assets, population, GDP, distance, renewable potentials, load shares, and hydro shares. The resulting data pipeline produces consistent nodal timeseries, installed capacities, and technology attributes for subsequent optimisation. By separating grid reduction, geo-spatial profile generation, and technology-specific disaggregation, the workflow supports reproducible scenario construction, sensitivity analysis, and transparent validation of European power system optimisation studies. </p>
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.21203/rs.3.rs-9791175/v1first seen 2026-05-26 04:21:42 · last seen 2026-05-27 04:21:46
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