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@Article{NobreSKKZMPRR:2016:PVPoCo,
               author = "Nobre, Andr{\'e} M. and Severiano J{\'u}nior, Carlos A. and 
                         Karthik, Shravan and Kubis, Marek and Zhao, Lu and Martins, 
                         Fernando Ramos and Pereira, Enio Bueno and R{\"u}ther, Ricardo 
                         and Reindl, Thomas",
          affiliation = "{National University of Singapore} and {Universidade Federal de 
                         Minas Gerais (UFMG)} and {National University of Singapore} and 
                         {National University of Singapore} and {National University of 
                         Singapore} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal de Santa Catarina (UFSC)} and {National 
                         University of Singapor}",
                title = "PV power conversion and short-term forecasting in a tropical, 
                         densely-built environment in Singapore",
              journal = "Renewable Energy",
                 year = "2016",
               volume = "94",
                pages = "496--509",
                month = "Aug.",
             keywords = "PV power conversion, PV systems, Short-term prediction, Solar 
                         irradiance forecasting, Tropical regions.",
             abstract = "With the substantial growth of solar photovoltaic installations 
                         worldwide, forecasting irradiance becomes a critical step in 
                         providing a reliable integration of solar electricity into 
                         electric power grids. In Singapore, the number of PV installation 
                         has increased with a growth rate of 70% over the past 6 years. 
                         Within the next decade, solar power could represent up to 20% of 
                         the instant power generation. Challenges for PV grid integration 
                         in Singapore arise from the high variability in cloud movements 
                         and irradiance patterns due to the tropical climate. For a 
                         thorough analysis and modeling of the impact of an increasing 
                         share of variable PV power on the electric power system, it is 
                         indispensable (i) to have an accurate conversion model from 
                         irradiance to solar power generation, and (ii) to carry out 
                         irradiance forecasting on various time scales. In this work, we 
                         demonstrate how common assumptions and simplifications in PV power 
                         conversion methods negatively affect the output estimates of PV 
                         systems power in a tropical and densely-built environment such as 
                         in Singapore. In the second part, we propose and test a novel 
                         hybrid model for short-term irradiance forecasting for short-term 
                         intervals. The hybrid model outperforms the persistence forecast 
                         and other common statistical methods.",
                  doi = "10.1016/j.renene.2016.03.075",
                  url = "http://dx.doi.org/10.1016/j.renene.2016.03.075",
                 issn = "0960-1481",
             language = "en",
           targetfile = "nobre_pv.pdf",
        urlaccessdate = "04 dez. 2020"
}


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