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Inftech."],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The transformation of energy systems driven by the increasing integration of renewable energy sources is leading to a\u00a0growing flexibility demand. Flexibility options such as battery electric storage systems or power-to-gas can play a\u00a0key role in addressing this challenge. However, questions remain regarding the optimal siting and deployment of such technologies. This paper presents a\u00a0novel methodology for optimizing flexibilities in spatially resolved energy system models. Flexibility deployment is based on two different strategies\u2014market-driven and peak-shaving\u2014while flexibility siting is done through a\u00a0combination of residual load analysis and linear programming. The methodology is applied to a\u00a0use case representing a\u00a0climate-neutral Austria in 2040. Based on the Integrated Austrian Network Infrastructure Plan, a\u00a0model of the very-high-voltage and high-voltage power system in Austria is developed and the siting and deployment of flexibilities is optimized within this framework. The two deployment strategies are then assessed by simulating hourly power flows and thus evaluating their impact on grid utilization. Assuming flexibility expansion according to the Integrated Austrian Network Infrastructure Plan, both strategies lead to a\u00a0significant decrease in grid utilization. This is especially interesting for the market-driven strategy: While peak-shaving deployment depends on forecasting and covering local flexibility demands, market-driven deployment is based on aggregated spot market price and thus presents a\u00a0comparatively realizable strategy. This paper shows that, given an optimal siting, even a\u00a0purely market-driven deployment can contribute to supporting the power grid.<\/jats:p>","DOI":"10.1007\/s00502-025-01344-y","type":"journal-article","created":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T09:12:13Z","timestamp":1760087533000},"page":"470-483","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Locating and dispatching flexibility in spatially resolved energy system models: a\u00a0case study of Austria","Standortwahl und Einsatzplanung f\u00fcr Flexibilit\u00e4tsoptionen in r\u00e4umlich aufgel\u00f6sten Energiesystemmodellen: eine Fallstudie f\u00fcr \u00d6sterreich"],"prefix":"10.1007","volume":"142","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0535-1622","authenticated-orcid":false,"given":"Stefan","family":"Wallner","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4902-5010","authenticated-orcid":false,"given":"Thomas","family":"Vouk","sequence":"additional","affiliation":[]},{"given":"David","family":"Siebenhofer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1297-0808","authenticated-orcid":false,"given":"Thomas","family":"Kienberger","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,10]]},"reference":[{"key":"1344_CR1","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1016\/j.rser.2015.01.057","volume":"45","author":"PD Lund","year":"2015","unstructured":"Lund PD, Lindgren J, Mikkola J, Salpakari J (2015) Review of energy system flexibility measures to enable high levels of variable renewable electricity. 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