NREL upgrades SAM wave and tidal tools

Business Developments & Projects

The National Renewable Energy Laboratory (NREL) has added marine energy to the open-source System Advisor Model (SAM) toolkit to facilitate the cost and performance analysis for wave and tidal energy systems.

Illustration (Courtesy of Ian Gagnon, US Department of Energy)
Illustration (Courtesy of Ian Gagnon, US Department of Energy)
Illustration (Courtesy of Ian Gagnon, US Department of Energy)

SAM is an open-source software that combines performance and financial analysis for a suite of renewable energy technologies such as photovoltaics, wind, geothermal, marine energy, and more.

The recently released version of SAM includes modeling
capabilities for both wave and tidal energy. The model estimates annual energy
production (AEP) and the levelized cost of energy (LCOE) for wave and tidal
energy systems at a host of geographical locations.

The Marine Energy Wave Model can be applied to systems that
use a wave energy converter (WEC) to transform the energy of ocean waves into
electricity.

SAM’s two built-in libraries offer default data for both
sample systems and locations, and the model can be run with this default data,
or users can provide their own data.

The wave resource library includes data for US locations such as the California Central Coast, California Humboldt Bay, Oregon, North Carolina, and Hawaii. The device library includes power matrices for three types of WECs: heaving buoys, oscillating surge wave converters, and a backward bent duct buoy floating oscillating columns.

Alternatively, users may upload power matrices for unique devices to perform the simulation, NREL noted.

The Marine Energy Tidal Model can be applied to systems that
employ a tidal energy converter to convert the energy of ocean tides into
electricity.

Marine energy SAM can accommodate a wide range of users at varying levels of detail, too.

Cost, reporting, and comparison functionality

The tool can help early-stage technology developers to
perform quick feasibility studies and estimate system costs outside of their
research focus.

It can also be used to produce replicable cost models and
frameworks for developers at a high technology-readiness level.

Users such as the national laboratories and DOE’s Water
Power Technologies Office can enjoy streamlined internal reporting and expanded
analysis, while other marine energy stakeholders can leverage the marine energy
SAM to quickly estimate the techno-economic potential of marine energy projects
and plan for future technology options, NREL said.

Recently, NREL’s team developed three additional upgrades to
augment the functionality of the tool, including the expanded cost input pages that
allow users to employ either high-level or more granular cost inputs.

Also, marine energy SAM now boasts two new macros. The Wave Report macro will allow users to generate a report summary for the marine energy system modeled in SAM, while the Wave Compare Cases macro will allow users to compare multiple cases and produce a simple report, featuring graphs and tables to summarize the comparison.

New features ahead

Throughout 2021, the NREL team will continue to refine the SAM
for marine energy and expand upon its energy production modeling capabilities
by integrating it with the Marine and Hydrokinetic (MHK) Atlas.

This integration will allow users to download up to 30 years of time history hindcast data using latitude and longitude coordinates for marine energy resource locations in the United States.

It will enable broader energy analysis capabilities, allowing users to take a closer look at energy production over daily, weekly, and monthly intervals from a vastly expanded set of locations, according to NREL.

Additionally, the future upgrade will facilitate better comparisons of marine renewable energy with other types of renewable energy sources.

For example, users will be able to employ the tool to compare the energy production of a marine energy system to an offshore wind system over a specific time period, rather than having to view the data from solely an annual perspective.