Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/106954
Title: Optimized design method for storage systems in photovoltaic plants with delivery limitation
Authors: Colmenar-Santos, Antonio
Monteagudo-Mencucci, Mario
Rosales Asensio, Enrique 
de Simón-Martín, Miguel
Pérez-Molina, Clara
UNESCO Clasification: 332205 Fuentes no convencionales de energía
Keywords: Renewable energy storage
Photovoltaic solar energy
System optimization
Battery capacity
Issue Date: 2019
Journal: Solar Energy 
Abstract: It results widely common for distribution network operators to impose restrictions on delivered solar photovoltaic generated power when the power plant rated power is greater than the maximum allowed due to the distribution network capacity. Thus, a feasible solution to maximize the performance of the solar power plant is the integration of battery energy storage systems. Although this configuration has been extensively studied in the existing literature, an optimal design method to determine the proper size and operation of the energy storage system needs to be developed. In this paper, a novel method to help power plants designers to determine the optimal battery energy storage capacity to integrate into any solar photovoltaic power plant is provided. The proposed algorithm minimizes the potential power curtailment and optimizes the utilization rate of the batteries storage system. The algorithm can be applied to any grid connected solar photovoltaic power plant under delivery power restrictions, regardless of power capacity and location. The algorithm has been implemented to a simulated power plant with delivery limitations based in a real case, and results with the optimal battery capacity show that the system would be able to recover up to the 83% of the curtailed energy and a yearly average capacity utilization of 56%. Moreover, the BESS operation has been validated with a scaled model run in Simulink and laboratory measurements, achieving 98% of curtailed energy recovery rate and a 57% of average capacity utilization.
URI: http://hdl.handle.net/10553/106954
ISSN: 0038-092X
DOI: 10.1016/j.solener.2019.01.046
Source: Solar Energy [ISSN 0038-092X], n. 180, p. 468-488 (marzo 2019)
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