000164051 001__ 164051
000164051 005__ 20251121161351.0
000164051 0247_ $$2doi$$a10.1016/j.enconman.2025.120650
000164051 0248_ $$2sideral$$a146189
000164051 037__ $$aART-2026-146189
000164051 041__ $$aeng
000164051 100__ $$aDe Souza, Ronelly José
000164051 245__ $$aOptimal operation and marginal costs in a complex polygeneration system including thermal energy storage and DHCN pipelines
000164051 260__ $$c2026
000164051 5060_ $$aAccess copy available to the general public$$fUnrestricted
000164051 5203_ $$aThis paper proposes a thermoeconomic analysis to determine the hourly marginal costs of the optimal operation of a complex polygeneration system when the energy demand for a specific energy service increases at any time step, without modifying the operation mode of the system. The work analyses a case study which considers a mixed integer linear programming (MILP) model of an energy community (EC), comprising nine tertiary sector buildings and a central unit supplied by natural gas, solar energy, and electricity. The buildings exchange electricity through a local electric grid as well as heating and cooling through a district heating and cooling network (DHCN). The paper focuses on the marginal cost (MC) analysis of the electricity and heating demands regarding two of the EC buildings by evaluating representative time steps of a typical winter day. Additionally, a detailed analysis of the cost formation process for polygeneration heat production is conducted, clarifying the influence of thermal energy storage (TES) and DHCN on the marginal cost of heat production. The proposed marginal cost analysis reveals strategies for managing increased heat or electricity demands with minimal impact on the objective function. While the applied methodology offers robustness and transparency, it should be noted that the model under analysis does not include dynamic inefficiencies such as start-up/shut-down of technologies, and renewable variability is represented through deterministic time series. Thus, the mentioned optimal operation refers to the most cost-effective response to marginal demand changes within fixed operational modes. Obtained results indicate that optimal marginal paths have the potential to reduce operation costs by 26% compared to non-optimal ones.
000164051 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2020-115500RB-I00$$9info:eu-repo/grantAgreement/ES/AEI/PID2023-148958OB-C21$$9info:eu-repo/grantAgreement/ES/DGA/T55-23R
000164051 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000164051 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000164051 700__ $$0(orcid)0000-0002-5161-7209$$aSerra, Luis M.
000164051 700__ $$0(orcid)0000-0002-4411-9834$$aLozano, Miguel A.
000164051 700__ $$aReini, Mauro
000164051 773__ $$g348 (2026), 120650 [23 pp.]$$pEnergy convers. manag.$$tENERGY CONVERSION AND MANAGEMENT$$x0196-8904
000164051 8564_ $$s14688226$$uhttps://zaguan.unizar.es/record/164051/files/texto_completo.pdf$$yVersión publicada
000164051 8564_ $$s2601254$$uhttps://zaguan.unizar.es/record/164051/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000164051 909CO $$ooai:zaguan.unizar.es:164051$$particulos$$pdriver
000164051 951__ $$a2025-11-21-14:25:31
000164051 980__ $$aARTICLE