A Method to Synthesize Hourly Time-series of Solar Power Plants in Peru for Long-Term Planning

Plenty of works have treated the system expansion planning problem in the presence of intermittent renewable energy resources like solar. However, most of those proposals have been approached from scenarios of plenty of data, which is not the rule in developing countries, where principal investment actors have recently switched their focus. In contrast of operation problems where existing literature can be successfully applied since it requires short-term historical time-series gathered from the same studied plants, proposals for planning problems are almost impossible to apply because of a lack of information and measurement about renewable resources in places where no renewable plants have been previously installed. In order to fill this information gap, this paper presents a novel methodology to synthesize solar production time-series on an hourly time scale, taking as inputs aggregate data such as monthly average, maximum or minimum values of basic parameters like global horizontal insolation, air temperature, and surface albedo. The methodology comprises five steps, from data gathering to calculating electrical power produced by a solar photovoltaic system. Three application tests are performed for different places in Chile, Slovakia, and Peru to validate the proposed methodology. The results show that the methodology successfully synthesizes time-series of output power, correctly replicates typical solar resource behavior, and slightly underestimates the produced solar energy, having a discrepancy of 2.4% in the yearly total.