{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T11:29:25Z","timestamp":1784978965862,"version":"3.55.0"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Doctoral Researcher fellowship from the Fonds de la Recherche Scientifique"},{"name":"research fellow of the Belgian American Educational Foundation (BAEF)."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Smart Grid"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1109\/tsg.2025.3639887","type":"journal-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T18:42:50Z","timestamp":1764787370000},"page":"1875-1888","source":"Crossref","is-referenced-by-count":3,"title":["Decision-Focused Learning for Neural Network-Constrained HVAC Scheduling"],"prefix":"10.1109","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0782-4494","authenticated-orcid":false,"given":"Pietro","family":"Favaro","sequence":"first","affiliation":[{"name":"University of Mons, Mons, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9853-2694","authenticated-orcid":false,"given":"Jean-Fran\u00e7ois","family":"Toubeau","sequence":"additional","affiliation":[{"name":"University of Mons, Mons, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2409-2128","authenticated-orcid":false,"given":"Fran\u00e7ois","family":"Vall\u00e9e","sequence":"additional","affiliation":[{"name":"University of Mons, Mons, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yury","family":"Dvorkin","sequence":"additional","affiliation":[{"name":"Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Buildings-Energy System","year":"2023"},{"key":"ref2","volume-title":"Energy Consumption in Households","year":"2024"},{"issue":"4","key":"ref3","doi-asserted-by":"crossref","first-page":"3667","DOI":"10.1109\/TPWRS.2013.2245687","article-title":"Decentralized participation of flexible demand in electricity markets\u2014Part II: Application with electric vehicles and heat pump systems","volume":"28","author":"Papadaskalopoulos","year":"2013","journal-title":"IEEE Trans. Power Syst."},{"issue":"4","key":"ref4","doi-asserted-by":"crossref","first-page":"1852","DOI":"10.1109\/TSG.2015.2414490","article-title":"Estimation of residential heat pump consumption for flexibility market applications","volume":"6","author":"Kouzelis","year":"2015","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/PESGM.2016.7741966"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2021.3136464"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2971530"},{"issue":"4","key":"ref8","doi-asserted-by":"crossref","first-page":"3090","DOI":"10.1109\/TPWRS.2015.2472497","article-title":"Experimental study of grid frequency regulation ancillary service of a variable speed heat pump","volume":"31","author":"Kim","year":"2016","journal-title":"IEEE Trans. Power Syst."},{"key":"ref9","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.apenergy.2011.12.005","article-title":"Online voltage security assessment considering comfort-constrained demand response control of distributed heat pump systems","volume":"96","author":"Wang","year":"2012","journal-title":"Appl. Energy"},{"key":"ref10","volume-title":"The Current Electricity Market Design in Europe","year":"2015"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.arcontrol.2020.09.001","article-title":"All you need to know about model predictive control for buildings","volume":"50","author":"Drgo\u0148a","year":"2020","journal-title":"Annu. Rev. Control"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-7788(00)00114-6"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2017.10.044"},{"issue":"5","key":"ref14","doi-asserted-by":"crossref","first-page":"2947","DOI":"10.3390\/su14052947","article-title":"Experimental study on the performance decay of thermal insulation and related influence on heating energy consumption in buildings","volume":"14","author":"D\u2019Agostino","year":"2022","journal-title":"Sustainability"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.enbuild.2015.09.053","article-title":"On the lumped capacitance approximation accuracy in RC network building models","volume":"108","author":"Kircher","year":"2015","journal-title":"Energy Buildings"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SST.2016.7765626"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.enbuild.2015.08.041","article-title":"An improved office building cooling load prediction model based on multivariable linear regression","volume":"107","author":"Qiang","year":"2015","journal-title":"Energy Buildings"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2020.2986539"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3110960"},{"key":"ref20","doi-asserted-by":"crossref","DOI":"10.1016\/j.enbuild.2021.110992","article-title":"Physics-constrained deep learning of multi-zone building thermal dynamics","volume":"243","author":"Drgo\u0148a","year":"2021","journal-title":"Energy Buildings"},{"issue":"20","key":"ref21","first-page":"22150","article-title":"Active reinforcement learning for robust building control","volume-title":"Proc. AAAI Conf. Artif. Intell.","volume":"38","author":"Jang"},{"key":"ref22","article-title":"DC3: A learning method for optimization with hard constraints","author":"Donti","year":"2021","journal-title":"arXiv:2104.12225"},{"key":"ref23","article-title":"Learning to optimize for mixed-integer non-linear programming with feasibility guarantees","author":"Tang","year":"2024","journal-title":"arXiv:2410.11061"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25520"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5403"},{"key":"ref26","article-title":"Neural networks for encoding dynamic security-constrained optimal power flow","author":"Murzakhanov","year":"2020","journal-title":"arXiv:2003.07939"},{"key":"ref27","article-title":"Decision-oriented learning for future power system decision-making under uncertainty","author":"Li","year":"2024","journal-title":"arXiv:2401.03680"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.15320"},{"key":"ref29","first-page":"889","article-title":"Directed regression","volume-title":"Proc. Neural Inf. Process. Syst.","volume":"22","author":"Kao"},{"key":"ref30","first-page":"5484","article-title":"Task-based end-to-end model learning in stochastic optimization","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","volume":"30","author":"Donti"},{"key":"ref31","first-page":"361","article-title":"Learning convex optimization control policies","volume-title":"Proc. 2nd Conf. Learn. Dyn. Control","author":"Agrawal"},{"key":"ref32","first-page":"136","article-title":"OptNet: Differentiable optimization as a layer in neural networks","volume-title":"Proc. Intl. Conf. Mach. Learn.","author":"Amos"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3360322.3360849"},{"issue":"1","key":"ref34","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1109\/TSG.2024.3445574","article-title":"Decision-oriented modeling of thermal dynamics within buildings","volume":"16","author":"Cui","year":"2025","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref35","doi-asserted-by":"crossref","DOI":"10.1016\/j.epsr.2023.109384","article-title":"More than accuracy: End-to-end wind power forecasting that optimises the energy system","volume":"221","author":"Wahdany","year":"2023","journal-title":"Electr. Power Syst. Res."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2024.110660"},{"issue":"2","key":"ref37","first-page":"1504","article-title":"MIPaaL: Mixed integer program as a layer","volume-title":"Proc. AAAI Conf. Artif. Intell.","volume":"34","author":"Ferber"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s12532-024-00255-x"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.19498"},{"key":"ref40","article-title":"OMLT: Optimization & machine learning toolkit","author":"Ceccon","year":"2022","journal-title":"arXiv:2202.02414"},{"key":"ref41","doi-asserted-by":"crossref","DOI":"10.1016\/j.compchemeng.2024.108684","article-title":"Augmenting optimization-based molecular design with graph neural networks","volume":"186","author":"Zhang","year":"2024","journal-title":"Comput. Chem. Eng."},{"issue":"132","key":"ref42","first-page":"1","article-title":"Monte Carlo gradient estimation in machine learning","volume":"21","author":"Mohamed","year":"2019","journal-title":"J. Mach. Learn. Res."},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.123.170602"},{"key":"ref44","first-page":"315","article-title":"Deep sparse rectifier neural networks","volume":"15","author":"Glorot","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2020.3042100"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/s0167-5060(08)70342-x"},{"key":"ref47","first-page":"4790","article-title":"A unified view of piecewise linear neural network verification","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Bunel"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-020-01474-5"},{"key":"ref49","first-page":"3068","article-title":"Partition-based formulations for mixed-integer optimization of trained ReLU neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Tsay"},{"key":"ref50","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120895","article-title":"A neural network-based distributional constraint learning methodology for mixed-integer stochastic optimization","volume":"232","author":"Alc\u00e1ntara","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"ref51","doi-asserted-by":"crossref","first-page":"1841","DOI":"10.1016\/B978-0-443-15274-0.50292-4","article-title":"A novel neural network bounds-tightening procedure for multiparametric programming and control","volume":"52","author":"Kenefake","year":"2023","journal-title":"Comput. Aided Chem. Eng."},{"key":"ref52","doi-asserted-by":"crossref","DOI":"10.1016\/j.energy.2023.128218","article-title":"Integrating machine learning and mathematical programming for efficient optimization of operating conditions in organic Rankine cycle (ORC) based combined systems","volume":"281","author":"Zhou","year":"2023","journal-title":"Energy"},{"key":"ref53","doi-asserted-by":"crossref","DOI":"10.1016\/j.energy.2023.129999","article-title":"Neural network informed day-ahead scheduling of pumped hydro energy storage","volume":"289","author":"Favaro","year":"2024","journal-title":"Energy"},{"key":"ref54","article-title":"Evaluating robustness of neural networks with mixed integer programming","author":"Tjeng","year":"2017","journal-title":"arXiv:1711.07356"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898717716"},{"key":"ref56","volume-title":"Commercial Prototype Building Models","year":"2023"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1145\/3679240.3734584"}],"container-title":["IEEE Transactions on Smart Grid"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5165411\/11493583\/11275968.pdf?arnumber=11275968","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T19:59:48Z","timestamp":1776974388000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11275968\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":57,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tsg.2025.3639887","relation":{},"ISSN":["1949-3053","1949-3061"],"issn-type":[{"value":"1949-3053","type":"print"},{"value":"1949-3061","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5]]}}}