Optimized design method for storage systems in photovoltaic plants with delivery limitation. (1st March 2019)

• Record Type: Journal Article
• Authors: Colmenar-Santos, Antonio; Monteagudo-Mencucci, Mario; Rosales-Asensio, Enrique; de Simón-Martín, Miguel; Pérez-Molina, Clara
• Is Part Of: Solar energy. Volume 180(2019)
• Page Start: 468
• Page End: 488
• Publication Date: 2019-03-01
• Subjects: Renewable energy storage -- Photovoltaic solar energy -- System optimization -- Battery capacity; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2019.01.046
• Languages: English
• ISSNs: 0038-092X

Abstract

Graphical abstract: Highlights: Restrictions on Photovoltaic PV plant delivery power reduces performance ratio. The limited power can be recovered via battery energy storage systems. An optimized capacity design method is provided using mathematical expressions. The results obtained will be simulated using Simulink applying the method. 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.