000110756 001__ 110756
000110756 005__ 20220223124038.0
000110756 0247_ $$2doi$$a10.1016/j.apenergy.2016.07.018
000110756 0248_ $$2sideral$$a96149
000110756 037__ $$aART-2016-96149
000110756 041__ $$aeng
000110756 100__ $$aLujano-Rojas, J.
000110756 245__ $$aOperating conditions of lead-acid batteries in the optimization of hybrid energy systems and microgrids
000110756 260__ $$c2016
000110756 5060_ $$aAccess copy available to the general public$$fUnrestricted
000110756 5203_ $$aThe promotion and deployment of storage technologies in autonomous and grid-connected systems plays a relevant part in the massive integration of renewable power sources required for the worldwide development of a sustainable society. In this regard, analyzing the behavior of electrochemical storage devices such as lead-acid batteries installed on hybrid energy systems and microgrids in terms of their lifetime and economic profitability is an important research topic. Since renewable generation is characterized by its random nature, lead-acid batteries typically work under stress conditions, which directly influence their lifetime in a negative way by increasing the net present cost. Due to the fast growing of renewable sources as a consequence of governmental policies and incentives, the number of manufacturers to be considered worldwide is becoming really high, so that optimization techniques such as genetic algorithms (GAs) are frequently used in order to consider the performance of a high number of manufacturers of wind turbines, photovoltaic panels and lead-acid batteries subject to the environmental conditions of the location under analysis to determine a cost-effective design. In this paper, GA method combined with weighted Ah ageing model is improved by including expert experiences by means of stress factors and the categorization of operating conditions, as a new contribution to earlier studies. The effectiveness of the proposed method is illustrated by analyzing a hybrid energy system to be installed in Zaragoza, Spain, resulting in a near-optimal design in a reduced computational time compared to the enumerative optimization method.
000110756 536__ $$9info:eu-repo/grantAgreement/EC/FP7/309048/EU/Smart and Sustainable Insular Electricity Grids Under Large-Scale Renewable Integration/SINGULAR$$9info:eu-repo/grantAgreement/ES/MINECO/ENE2013-48517-C2-1-R
000110756 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000110756 590__ $$a7.182$$b2016
000110756 591__ $$aENGINEERING, CHEMICAL$$b4 / 135 = 0.03$$c2016$$dQ1$$eT1
000110756 591__ $$aENERGY & FUELS$$b6 / 92 = 0.065$$c2016$$dQ1$$eT1
000110756 592__ $$a3.011$$b2016
000110756 593__ $$aBuilding and Construction$$c2016$$dQ1
000110756 593__ $$aCivil and Structural Engineering$$c2016$$dQ1
000110756 593__ $$aEnergy (miscellaneous)$$c2016$$dQ1
000110756 593__ $$aNuclear Energy and Engineering$$c2016$$dQ1
000110756 593__ $$aFuel Technology$$c2016$$dQ1
000110756 593__ $$aManagement, Monitoring, Policy and Law$$c2016$$dQ1
000110756 593__ $$aMechanical Engineering$$c2016$$dQ1
000110756 593__ $$aEnergy Engineering and Power Technology$$c2016$$dQ1
000110756 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000110756 700__ $$0(orcid)0000-0002-1490-6423$$aDufo-López, R.$$uUniversidad de Zaragoza
000110756 700__ $$aAtencio-Guerra, J.
000110756 700__ $$aRodrigues, E. M. G.
000110756 700__ $$0(orcid)0000-0003-2813-1240$$aBernal-Agustín, J. L.$$uUniversidad de Zaragoza
000110756 700__ $$aCatalão, J. P. S.
000110756 7102_ $$15009$$2535$$aUniversidad de Zaragoza$$bDpto. Ingeniería Eléctrica$$cÁrea Ingeniería Eléctrica
000110756 773__ $$g179 (2016), 590-600$$pAppl. energy$$tApplied Energy$$x0306-2619
000110756 8564_ $$s843013$$uhttps://zaguan.unizar.es/record/110756/files/texto_completo.pdf$$yPostprint
000110756 8564_ $$s2180420$$uhttps://zaguan.unizar.es/record/110756/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000110756 909CO $$ooai:zaguan.unizar.es:110756$$particulos$$pdriver
000110756 951__ $$a2022-02-23-11:07:53
000110756 980__ $$aARTICLE