Climate-Driven Energy Demand Shifts in the Kisalföld Region: Historical Correlations, Future Projections, and Infrastructure Loss Implications
キシュアルフョルド地域における気候主導のエネルギー需要シフト：歴史的相関、将来予測、およびインフラ損失の影響 (AI 翻訳)
Zsombor Sztyehlik
🤖 gxceed AI 要約
日本語
本研究は、ハンガリーのキシュアルフョルド地域における気温と電力需要の関係を1970年から2024年までのデータで分析し、IPCC AR6シナリオに基づく将来予測を行った。温暖化により冷却度日が3倍に増加し、2035年頃までは暖房需要減少が冷房需要増加を上回るが、高排出シナリオでは2065年以降に夏期ピークへ移行する。また、送電損失が2100年までに最大100MW増加する可能性がある。
English
This study analyzes the relationship between surface temperature and electricity demand in Hungary's Kisalföld region using data from 1970-2024 and projects future demand under IPCC AR6 scenarios. Cooling degree days have tripled, and although heating savings outweigh cooling gains until 2035, under high emissions the system shifts to summer-peak around 2065. Transmission losses could add up to 100 MW of wasted capacity by 2100.
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
日本のエネルギー計画においても、気候変動による冷暖房需要の構造変化は重要課題であり、特に地域別の詳細な需要予測手法は参考になる。ただし本論文はハンガリー特有の気候・系統条件に基づくため、直接適用には調整が必要。
In the global GX context
This paper provides a granular, data-driven approach to modeling climate-induced shifts in energy demand, including infrastructure losses often omitted from projections. It is relevant for grid operators and policymakers planning for peak demand transitions in temperate regions, complementing global TCFD and ISSB scenario analysis needs.
👥 読者別の含意
🔬研究者:The methodology combining ERA5 reanalysis, XGBoost, and transmission loss modeling offers a replicable framework for regional climate-energy studies.
🏢実務担当者:Grid operators can use the projections to anticipate infrastructure stress from temperature-driven demand shifts and increased transmission losses.
🏛政策担当者:Insights into the timing of winter-to-summer peak transition and compounding infrastructure burden inform adaptation investment strategies.
📄 Abstract（原文）
Rising temperatures driven by anthropogenic climate change are expected to substantially alter patterns of energy consumption across Central Europe. This study investigates the historical relationship between surface temperature and electricity demand in the Kisalföld region of Hungary — a lowland agricultural area characterised by high summer temperature variability — and projects how this relationship evolves under IPCC AR6 warming scenarios of 1.5 ◦C, 2 ◦C, and 3 ◦C above pre-industrial levels by 2100. Using ERA5 reanalysis data spanning 1970–2024, upper-air sounding observations from WMO station 12843 (Budapest/Pestszentlőrinc), and Hungarian national grid load records from ENTSO-E (2015– 2024), we train an XGBoost demand model achieving R2 = 0.77 and RMSE = 285 MW on a held-out test set. ERA5 data reveal warming of +0.42 ◦C per decade since 1970, with cooling degree days tripling and heating degree days declining by 20%. Projections suggest that net climate-driven demand may initially fall as heating savings outpace cooling gains, but under the high-emissions scenario (SSP5-8.5) cooling demand overtakes heating savings around 2065, representing a structural transition from a winter-peak to a summer-peak energy system. Additionally, temperature-driven increases in grid transmission losses add up to 100 MW of continuously wasted generation capacity by 2100 under SSP5-8.5 — a compounding infrastructure burden that is largely absent from existing demand projections. An interactive Progressive Web Application accompanying this paper makes all projections publicly accessible.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.20230176first seen 2026-06-05 04:55:02 · last seen 2026-06-15 04:51:43
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