doi:10.1016/j.renene.2019.11.048engPinto Maquilón, Edwin SamirSerra, Luis M.Lázaro, AnaEvaluation of methods to select representative days for the optimization of polygeneration systemsART-2020-114567The optimization of polygeneration systems considering hourly periods throughout one year is a computationally demanding task, and, therefore, methods for the selection of representative days are employed to reproduce reasonably the entire year. However, the suitability of a method strongly depends on the variability of the time series involved in the system. This work compares the methods Averaging, k-Medoids and OPT for the selection of representative days by carrying out the optimization of grid-connected and standalone polygeneration systems for a building in two different locations. The suitability of the representative days obtained with each method were assessed regarding the optimization of the polygeneration systems. Sizing errors under 5% were achieved by using 14 representative days, and the computational time, with respect to the entire year data, was reduced from hours to a few seconds. The results demonstrated that the Averaging method is suitable when there is low variability in the time series data; but, when the time series presents high stochastic variability (e.g., consideration of wind energy), the OPT method presented better performance. Also, a new method has been developed for the selection of representative days by combining the k-Medoids and OPT methods, although its implementation requires additional computational effort.2020http://zaguan.unizar.es/record/9608610.1016/j.renene.2019.11.048http://zaguan.unizar.es/record/96086oai:zaguan.unizar.es:96086info:eu-repo/grantAgreement/ES/DGA/T55-17Rinfo:eu-repo/grantAgreement/ES/MINECO/ENE2017-87711-RRenewable Energy 151 (2020), 488-502by-nc-ndhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccess