IEEE PVSC 49
Search
SPLTRAK Abstract Submission
Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions
Christian N. Pilot, Robin B. Bedilion, Daniel J. Fregosi, Sean Hackett, Michael L. Bolen, Joseph W. Stekli
Electric Power Research Institute (EPRI), Palo Alto, CA, United States

A variety of novel photovoltaic (PV) technologies are being developed with the intent of reducing the cost of solar electricity. However, the developmental focus is often on component-level optimization and may not fully consider the broader system-level impact to the PV plant. A detailed cost and performance analysis of how these individual components could integrate and optimize the plant at a system level has been relatively uninvestigated. This follow-on paper describes a techno-economic analysis examining the cost and performance of future PV plant components and designs with a focus on large-scale PV plants. Technologies explored include bifacial and tandem modules, increased plant voltage architectures above 1500 Vdc, and module-level power electronics. Integration of these innovative PV components into new PV plant designs and comparison with current PV technologies are evaluated based on levelized cost of electricity (LCOE) analysis. Baseline models for three irradiance profiles are developed within the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) and validated against actual PV plant performance data. Cost and performance data of future PV technologies, informed by a comprehensive literature review and informational interviews, are then incorporated into these models. A machine learning algorithm is implemented to determine an optimal PV plant configuration and technology combination for each location based on expected performance and cost of these new technologies. Utility-scale PV plant LCOE results for these technologies are presented, identifying plant-level configurations that may have the greatest impact on future plant cost and performance and discussing development opportunities for future technology and cost improvements.