Statistical Benchmarking of Distribution System State Estimation Algorithms Across Networks and Operating States
ネットワークと動作状態にわたる配電系統状態推定アルゴリズムの統計的ベンチマーキング (AI 翻訳)
Krpelík, Dan, Pospíšil, Lukáš, Praks, Pavel, Krčál, Vít, Topolánek, David, Vysocký, Jan
🤖 gxceed AI 要約
日本語
本リポジトリは、配電系統状態推定（SE）のベンチマークデータセットと、ベンチマークユースケースの生成、SE実験の実行、統計分析を行うソフトウェアを提供する。3つのネットワーク、8つの計測配置バリエーション、128のランダム負荷・観測サンプルを含む。脱炭素化・分散化による電力網のレジリエンス向上を目的としたEUプロジェクトの成果である。
English
This repository provides a benchmark dataset and software for power distribution system state estimation (SE), covering 3 networks, 8 measurement placement variants, and 128 random load/observation samples. It supports algorithm comparison using pandapower.estimation and custom sestila software, part of EU-funded projects on grid resilience in the context of decarbonisation and decentralisation.
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
本データセットは、日本の配電系統における再生可能エネルギー大量導入時の運用最適化に資する可能性がある。ただし、直接的な日本の政策・規制との連動はなく、標準的なベンチマークとして参考情報となる。
In the global GX context
This benchmark dataset supports development of state estimation algorithms critical for managing distributed energy resources and grid resilience, aligning with global efforts to modernize distribution systems for high renewable penetration. It provides a standardized testbed for researchers advancing operational technologies for decarbonized grids.
👥 読者別の含意
🔬研究者:Provides a standardized, statistically rigorous benchmark for comparing distribution system state estimation algorithms across multiple networks and operating conditions.
🏢実務担当者:Offers ready-to-use test cases and software for evaluating and selecting state estimation methods for distribution network management.
📄 Abstract（原文）
This repository contains dataset for benchmarking power distribution system state estimation (SE) and the software used to generate benchmark use cases, execute the SE experiments, and conduct the subsequent statistical analyses. Total 3 networks with 8 different measurement placement variants with 128 randomly generated loads and observations samples are provided. All combinations were subject to state estimation using algorithms from the `pandapower.estimation` module and a from a custom software implementation `sestila` (included). Enclosed are: - constructed benchmark dataset with estimation results for individual SE algorithms - snapshot of the `sestila` software `v0.1.2`, which includes: - Benchmark data generation - State estimation execution - Statistical comparison workflows - Figure generation and reporting Details on contents and usage are available in the enclosed `ReadMe.txt` file. Current version of the `sestila` SW is available at https://code.it4i.cz/krp0017/sestila . This work was supported by: - EU funds under the project “Increasing the resilience of power grids in the context of decarbonisation, decentralisation and sustainable socioeconomic development” (CZ.02.01.01/00/23_021/0008759), through the Operational Programme Johannes Amos Comenius. - EU under the “REFRESH – Research Excellence For Region Sustainability and High-tech Industries” (project No. CZ.10.03.01/00/22\_003/0000048) via the Operational Programme Just Transition. - the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90254), providing access to supercomputing infrastructure.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/20119995first seen 2026-05-14 21:24:48 · last seen 2026-05-14 21:38:54
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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。