Abstract
The System Advisor Model (SAM) developed by the National Renewable Energy Laboratory with funds by the U.S. Department of Energy is a free, publicly available modeling software designed to evaluate renewable energy system design, performance, and project economics. Since the software’s launch in 2007, new versions have been released annually, adding to the collection of technologies and financing options it can accommodate. Wave and tidal energy technologies were added to SAM in 2019. SAM’s marine energy module is a standardized, user-friendly modeling platform that estimates annual energy production (AEP) and the levelized cost of energy (LCOE) for wave and tidal energy systems. In the latest SAM release, the wave energy module has new resource modeling capability with the implementation of Marine Energy (ME) ATLAS that enables a user to model a wave energy device using wave hindcast data at thousands of locations using a latitude and longitude. Additionally, when modeling a resource site, users can calculate energy production with a joint probability distribution or time series data for the selected site. The bridge between SAM and ME ATLAS offers greater selection of resource site locations and enhances energy modeling capabilities for wave energy technologies. SAM offers built-in analysis tools, data visualization, standardized reporting, and the ability to create customized macros for specific analysis objectives. Currently, SAM’s marine energy module uses the fixed-charge-rate method to calculate LCOE and has the option to calculate AEP without a financial model. Upgrades planned for the next release of SAM’s marine energy module include adding additional financial models, enhanced cost modeling capabilities, and the ability to model hybrid systems with energy storage. SAM will be used to conduct two cast studies of a wave and tidal array. Each case study will provide a step-by-step guide for performance and cost modeling of wave and tidal systems using SAM. The case studies will highlight the analysis and reporting capabilities of SAM. Additionally, the case studies can be used inspire discussion and to solicit feedback to shape future SAM tool development.