168680 20260213191049.0 doi 10.3390/smartcities9020030 sideral 148047 ART-2026-148047 eng Fernández, Gregorio Greedy-VoI Time-Mesh Design for Rolling-Horizon EMS: Optimizing Block-Variable Granularity and Horizon Under Compute Budgets 2026 Rolling-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. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/EC/HORIZON EUROPE/101096192 /EU/REplicable, interoperable, cross-sector solutions and Energy services for demand side FLEXibility markets info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Sanz Osorio, J.F. Universidad de Zaragoza (orcid)0000-0001-7407-0608 Alarcón, Adrián Torres, Miguel Calavia, Alfonso 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 9, 2 (2026), 30 [22 pp.] Smart cities (Basel) Smart cities 2624-6511 2624634 http://zaguan.unizar.es/record/168680/files/texto_completo.pdf Versión publicada 2338357 http://zaguan.unizar.es/record/168680/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:168680 articulos driver 2026-02-13-18:28:20 ARTICLE