doi:10.1093/jcde/qwaa016engLujano-Rojas, J.M.Zubi, G.Dufo-Lopez, R.Bernal-Agustin, J.L.Atencio-Guerra, J.L.Catalao, J.P.S.Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systemsART-2020-117615This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required.2020http://zaguan.unizar.es/record/8958710.1093/jcde/qwaa016http://zaguan.unizar.es/record/89587oai:zaguan.unizar.es:89587Journal of computational design and engineering 7, 2 (2020), 177-194byhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccess