000168680 001__ 168680
000168680 005__ 20260213191049.0
000168680 0247_ $$2doi$$a10.3390/smartcities9020030
000168680 0248_ $$2sideral$$a148047
000168680 037__ $$aART-2026-148047
000168680 041__ $$aeng
000168680 100__ $$aFernández, Gregorio
000168680 245__ $$aGreedy-VoI Time-Mesh Design for Rolling-Horizon EMS: Optimizing Block-Variable Granularity and Horizon Under Compute Budgets
000168680 260__ $$c2026
000168680 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168680 5203_ $$aRolling-horizon energy management systems (EMSs) and model predictive control (MPC) for microgrids in smart cities face a fundamental trade-off: finer temporal discretization improves operational performance but rapidly increases the size of the optimization problem and execution time, jeopardizing real-time feasibility. Furthermore, in short-horizon operation, only the first control actions are implemented, while long-horizon decisions primarily guide feasibility and constraints. This paper proposes a computation-aware temporal mesh design layer that jointly selects a variable granularity of blocks and an optimization horizon, explicitly bounded by market-aligned settlement steps and per-cycle computation budgets. Candidate configurations are represented as pairs ⟨B, H⟩, where B is a constant-step block programme, and H is the optimization horizon, and they are uniquely tracked through an auditable mesh signature. The method first evaluates a predefined, market-consistent set of solutions ⟨B, H⟩ to establish reproducible cost and execution-time benchmarks, then applies a greedy value-of-information (Greedy-VoI) search that generates valid neighbouring meshes through local refinement, thickening, and resolution reallocation without violating the basic requirements that every solution must meet. All candidates are evaluated using the same microgrid use case and the same comparative KPIs, enabling the systematic identification of near-optimal mesh–horizon designs for practical EMS implementation.
000168680 536__ $$9info:eu-repo/grantAgreement/EC/HORIZON EUROPE/101096192 /EU/REplicable, interoperable, cross-sector solutions and Energy services for demand side FLEXibility markets
000168680 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000168680 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000168680 700__ $$0(orcid)0000-0001-7407-0608$$aSanz Osorio, J.F.$$uUniversidad de Zaragoza
000168680 700__ $$aAlarcón, Adrián
000168680 700__ $$aTorres, Miguel
000168680 700__ $$aCalavia, Alfonso
000168680 7102_ $$15009$$2535$$aUniversidad de Zaragoza$$bDpto. Ingeniería Eléctrica$$cÁrea Ingeniería Eléctrica
000168680 773__ $$g9, 2 (2026), 30 [22 pp.]$$pSmart cities (Basel)$$tSmart cities$$x2624-6511
000168680 8564_ $$s2624634$$uhttps://zaguan.unizar.es/record/168680/files/texto_completo.pdf$$yVersión publicada
000168680 8564_ $$s2338357$$uhttps://zaguan.unizar.es/record/168680/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000168680 909CO $$ooai:zaguan.unizar.es:168680$$particulos$$pdriver
000168680 951__ $$a2026-02-13-18:28:20
000168680 980__ $$aARTICLE