Abstract
Distributed power converters represent a technical solution to improve the performance of large or utility-scale photovoltaic (PV) plants. Unfortunately, evaluation of the yield obtained in large PV fields by using distributed converters is a difficult task because of recurring partial unavailability, inaccuracy of power analyzers, operating constraints imposed by the Power Plant Controller and so on. To overcome such issues in real operating scenarios, a new modeling strategy has been introduced and validated in terms of computational complexity and accuracy. This approach is based on the state-space averaging technique which is applied to large PV plants with multiple conversion stages by performing some elaborations in order to get a final integrated model. The new modeling strategy has been tested in MatLab Simulink environment using data coming from a 300 MW PV plant located in Brazil representing the case study of this work. In this plant, one subfield is equipped with central inverters while another is with string inverters. The proposed model, whose accuracy is in the range from 2.2 to 2.7% with respect to the measured energy, effectively supports data analysis leading to a consistent performance assessment for the distributed conversion system. Final results highlight that string inverters ensure a gain of about 2% in terms of produced energy.
Highlights
Distributed power converters in PV fields play a key role in the solar industry for new constructions and for retrofitting activities as well
This work deals with behavioral modeling of large PV plants
To evaluate the performance of distributed multi-stage converters in presence of issues caused by erroneous data, unavailability or distributed multi-stage converters in presence of issues caused by erroneous data, unavailability or external constraints, a new integrated state-space average model addressed to large or utility-scale external constraints, a new integrated state-space average model addressed to large or utility-scale
Summary
Distributed power converters in PV fields play a key role in the solar industry for new constructions and for retrofitting activities as well. In some cases there are additional operating constraints to take into account, for example thresholds set by the power plant controller (PPC) or by the inverters fixing the maximum power that a PV subfield can deliver to grid These problems can be solved by exploiting suitable models able to track the expected behavior of the PV plant in any operating conditions while filling the gaps due to faults and missing data. Under this perspective, in case of energy assessment analysis for months or years, detailed models cannot be exploited to simulate the behaviour of a large PV system having thousands of modules and hundreds of distributed converters.
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