「独立型ハイブリッド再生可能エネルギーシステムのサイジングにおいて気象年の選択がアルゴリズム選択を上回る」のデータとコード
Data and code for "Weather-year choice outweighs algorithm choice in sizing standalone hybrid renewable energy systems" (原題)
Sahay, Shahan, Yadav, Harsh, Jaiswal, Avishkar, Sharma, Aaradhya, Gupta, Shivani, Tiwari, Ravi
🤖 gxceed AI 要約
日本語
本論文は、独立型ハイブリッド再生可能エネルギーシステムの最適サイジングに関する研究のデータ・コード公開資料である。インド12地点・2005〜2023年のPVGIS-ERA5再解析気象系列228本と、684の地点×年ブロックにわたる16万件超のベンチマーク実行記録を収録する。7種のメタヒューリスティクスとランダム探索を比較し、気象年の選択がアルゴリズム選択よりも設計結果に大きく影響することを再現可能な形で示す。
English
This is the data-and-code deposit for a study on sizing standalone hybrid renewable energy systems. It provides 228 cached PVGIS-ERA5 hourly weather series for 12 Indian sites (2005-2023) and run records from 164,160 benchmark runs across 684 site-year blocks, comparing seven metaheuristics and random search. The reproducible workflow shows that weather-year choice outweighs algorithm choice in robust system sizing.
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
日本では再エネ導入拡大と独立型・分散型電源の設計最適化が地方脱炭素計画の鍵となる。再現可能なベンチマーク手法は国内の系統制約下での電源構成検討に参考になるが、開示・政策との直接連関は弱い。
In the global GX context
For global GX practice, this contributes open, reproducible methodology for robust renewable system sizing—relevant to energy-transition planning and investment appraisal, though it sits outside TCFD/ISSB disclosure frameworks.
👥 読者別の含意
🔬研究者:再現可能なベンチマーク設計と気象年不確実性の扱いを学べる。
🏢実務担当者:独立型再エネ設備の設計・調達時の不確実性評価に活用できる。
📄 Abstract（原文）
Input data, generated results and code for the revised paper "Weather-year choice outweighs algorithm choice in sizing standalone hybrid renewable energy systems" (Results in Engineering, manuscript RINENG-D-26-21837). Version 2 accompanies the revision and replaces version 1: demand shapes are laid on Indian Standard Time, every three-variable reference design carries a branch-and-bound certificate, and the scenario, population and five-variable re-search studies of the revision are included. Contents of hres_v2_deposit.zip: raw/ : the 228 cached hourly PVGIS-ERA5 series (PVGIS 5.3, horizontal array, 14 per cent system loss) for 12 Indian sites and the years 2005 to 2023, with their request metadata. raw_tilt/ : the 228 series for a south-facing array at the PVGIS optimum inclination of each site, with the tilt angles. results/ : reference designs and run records of the main benchmark (684 site-year blocks), the budget-curve, convergence and five-variable studies. results_rev/ : branch-and-bound certificates (cert), scenario benchmarks (bench), population study (population), five-variable re-search (extcheck) and the multi-year reliability matrices of every robust-sizing scenario (robust). main_runs_ist.csv.gz : the run-level record of the 164,160 main-benchmark runs. tables/, tables_rev/, figures/, figures_rev/, export_extra/ : derived tables, figures and extra exports. hres_bench.py and the other Python scripts : simulation, dispatch, economics, the seven metaheuristics and random search, reference construction, certification and analysis; the three synthetic demand shapes are defined in hres_bench.py. manifest.json : every parameter and library version. README_IST.md and REPRODUCE.md : how to rerun the study. run_*.log : run logs. paper_scripts.zip : the scripts that produce every number, table and figure of the revised paper from the stored outputs, with the numbers ledger. Seeds are derived deterministically from the block name, the algorithm name and a fixed base seed, so any run can be reproduced from its identifiers. All weather values are reanalysis, not site measurements, and all demand profiles are synthetic.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/23915872first seen 2026-11-03 04:12:12 · last seen 2026-11-05 04:13:15
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