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Renewable energy has experienced a significant growth on its rate of deployment as a clean and competitive alternative for conventional power sources. The reduction on the installation costs for PV systems has converted this technology into a relevant player regarding the electricity matrix. However, a larger penetration of PV systems is restricted to the availability of affordable technological options for storage. The integration of thermal energy storage to CSP systems is, on the other hand, straightforward through technologies already available in the market. Hence, the hybridization of CSP and PV systems has the potential for reducing operational and installation costs, as well as increasing significantly the capacity factor of solar power plants. The present study describes a methodology for design and sizing such hybrid plants, by implementing a transient simulation model, coupled to an evolutionary optimization algorithm, allowing to address the trade off between costs and capacity factor. The simulation model is applied to a case study considering the characteristics of a location in northern Chile. The results are presented in terms of the Pareto Frontiers that summarizes the compromise between the economic performance and the capacity factor of the plant. It is observed that the capacity factor achieves values higher that 85%, and the LCOE is lower than those observed for stand alone CSP plants. The methodology developed constitutes a useful tool for decision makers, who can assess the performance of the hybrid plant based in a detailed transient simulation and selecting the best configuration according to market constraints or its willingness for achieving certain level of capacity factor. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive analysis evaluating the impact of the dispatch strategy on the optimal design configurations of different combinations of solar power plants with storage. The analysis considers four dispatch profiles (baseload, daylight, night, and daylight and evening), and four technology combinations including a solar PV plant with batteries, a CSP plant with Thermal Storage (TES), a hybrid CSP-PV plant with TES, and a hybrid CSP-PV plant with TES and batteries. Two locations with high and moderate levels of DNI were selected and cost scenarios for 2020 and 2030 were considered. The aim is to determine the competitiveness ranges of each technology combination and establishing the least-cost technological option that allows meeting a dispatch strategy with a certain level of supply guarantee. A multi-objective optimization approach was followed to obtain the trade-off curves that minimize the LCOE and maximize the sufficiency factor in terms of the nominal size of the PV plant, solar multiple, TES size, batteries capacity, and inverter power rate. Results of this work allow determining the influence of the dispatch strategy on the competitiveness of these storage-integrated technology options, giving relevant information concerning under which conditions one technology combination is preferable over another. • The lowest LCOEs were obtained in baseload and the highest for the night dispatch. • When covering daylight and evening dispatch, the PV-BESS plant is more competitive. • The hybrid CSP-PV-TES-BESS is the most competitive option for >12 h storage. • Future 2030 cost projections have a greater impact on the LCOE reduction of the PV-BESS plant. • With DNI∼2000 kWh/m2/yr, the PV-BESS plant is the most competitive technology for all the cases. [ABSTRACT FROM AUTHOR]