000147698 001__ 147698
000147698 005__ 20250923084435.0
000147698 0247_ $$2doi$$a10.1016/j.energy.2024.134164
000147698 0248_ $$2sideral$$a141114
000147698 037__ $$aART-2024-141114
000147698 041__ $$aeng
000147698 100__ $$0(orcid)0000-0002-5801-0602$$aLujano-Rojas, Juan M.$$uUniversidad de Zaragoza
000147698 245__ $$aEfficient design of a hybrid power system incorporating resource variability
000147698 260__ $$c2024
000147698 5060_ $$aAccess copy available to the general public$$fUnrestricted
000147698 5203_ $$aThe optimal design of small-scale energy systems is a critical step in rural electrification projects, offering valuable insights for integrating renewable energy sources on a broader scale. This paper analyzes the sizing of isolated energy systems using the Genghis Khan Shark Optimizer, taking into account the variability of wind and solar resources across diverse scenario groups to enhance computational efficiency. Specifically, three scenario sets were utilized: training, validation, and testing. The training set was applied to assess the objective function across all optimization agents, while the validation set was used to independently evaluate the performance of the agent with the highest fitness score. Finally, the testing set was employed to verify the performance of the accepted solution. By selecting a limited number of scenarios for the training set and a moderate number for the validation and testing sets, we reduced the computational load associated with analyzing the entire population, allowing for greater focus on the most promising agent identified at each iteration. Results from a case study revealed that the proposed method identified an energy system configuration 8.05 % better than the configuration obtained using a genetic algorithm.
000147698 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2021-123172OB-I00$$9info:eu-repo/grantAgreement/EUR/AEI/TED2021-129801B-I00
000147698 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000147698 590__ $$a9.4$$b2024
000147698 592__ $$a2.211$$b2024
000147698 591__ $$aTHERMODYNAMICS$$b3 / 79 = 0.038$$c2024$$dQ1$$eT1
000147698 591__ $$aENERGY & FUELS$$b31 / 182 = 0.17$$c2024$$dQ1$$eT1
000147698 593__ $$aElectrical and Electronic Engineering$$c2024$$dQ1
000147698 593__ $$aEnergy (miscellaneous)$$c2024$$dQ1
000147698 593__ $$aEnergy Engineering and Power Technology$$c2024$$dQ1
000147698 593__ $$aManagement, Monitoring, Policy and Law$$c2024$$dQ1
000147698 593__ $$aCivil and Structural Engineering$$c2024$$dQ1
000147698 593__ $$aFuel Technology$$c2024$$dQ1
000147698 593__ $$aIndustrial and Manufacturing Engineering$$c2024$$dQ1
000147698 593__ $$aBuilding and Construction$$c2024$$dQ1
000147698 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000147698 700__ $$0(orcid)0000-0002-1490-6423$$aDufo-López, Rodolfo$$uUniversidad de Zaragoza
000147698 700__ $$0(orcid)0000-0001-7764-235X$$aArtal-Sevil, Jesús Sergio$$uUniversidad de Zaragoza
000147698 700__ $$aGarcía-Paricio, Eduardo
000147698 7102_ $$15009$$2535$$aUniversidad de Zaragoza$$bDpto. Ingeniería Eléctrica$$cÁrea Ingeniería Eléctrica
000147698 773__ $$g313 (2024), 134164 [18 pp.]$$pEnergy$$tEnergy$$x0360-5442
000147698 8564_ $$s8395807$$uhttps://zaguan.unizar.es/record/147698/files/texto_completo.pdf$$yVersión publicada
000147698 8564_ $$s2623432$$uhttps://zaguan.unizar.es/record/147698/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000147698 909CO $$ooai:zaguan.unizar.es:147698$$particulos$$pdriver
000147698 951__ $$a2025-09-22-14:46:05
000147698 980__ $$aARTICLE