131168 20240206154529.0 doi 10.1049/iet-rpg.2017.0777 sideral 107079 ART-2018-107079 eng Lujano-Rojas, J.M. Universidad de Zaragoza (orcid)0000-0002-5801-0602 Probabilistic methodology for estimating the optimal photovoltaic capacity in distribution systems to avoid power flow reversals 2018 The large-scale integration of photovoltaic generation (PVG) on distribution systems (DSs) preserving their technical constraints related to voltage fluctuations and active power (AP) flow is a challenging problem. Solar resources are accompanied by uncertainty regarding their estimation and intrinsically variable nature. This study presents a new probabilistic methodology based on quasi-static time-series analysis combined with the golden section search algorithm to integrate low and high levels of PVG into DSs to prevent AP flow in reverse direction. Based on the analysis of two illustrative case studies, it was concluded that the successful integration of PVG is not only related to the photovoltaic-cell manufacturing prices and conversion efficiency but also with the manufacturing prices of power electronic devices required for reactive power control. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/EC/FP7/309048/EU/Smart and Sustainable Insular Electricity Grids Under Large-Scale Renewable Integration/SINGULAR info:eu-repo/grantAgreement/ES/MINECO/ENE2013-48517-C2-1-R info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 3.605 2018 ENGINEERING, ELECTRICAL & ELECTRONIC 64 / 265 = 0.242 2018 Q1 T1 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY 14 / 35 = 0.4 2018 Q2 T2 ENERGY & FUELS 36 / 103 = 0.35 2018 Q2 T2 1.041 2018 Renewable Energy, Sustainability and the Environment 2018 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Dufo-López, R. Universidad de Zaragoza (orcid)0000-0002-1490-6423 Bernal-Agustín, J.L. Universidad de Zaragoza (orcid)0000-0003-2813-1240 Domínguez-Navarro, J.A. Universidad de Zaragoza (orcid)0000-0002-4770-0069 Catalaõ, J.P.S. 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 12, 9 (2018), 1045-1064 IET Renewable Power Generation IET Renewable Power Generation 1752-1416 586451 http://zaguan.unizar.es/record/131168/files/texto_completo.pdf Postprint 2614807 http://zaguan.unizar.es/record/131168/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:131168 articulos driver 2024-02-06-14:46:08 ARTICLE