The Cost Optimized Risk and Reliability Assessment Tool (CORRA) evaluates the costs and benefits of different decisions made during the life of a wind turbine blade.
Currently, CORRA is written to evaluate wind turbine blade damage, inspection, and repair. In this form, CORRA has two key components. The first component (corra.py) a techno-economic analysis that incorporates the costs of inspection and repairs with other standard costs to calculate a levelized costs of energy (LCOE). The second component (damage_tracking.py) is a probabilistic analysis that uses a set of user defined decision parameters to determine damage, inspection, and repairs across a set of wind turbine blades. Combining these two components, users can easily evaluate the LCOE of different approaches to inspecting and repairing wind turbine blades.
CORRA can be run on most computers capable of executing python scripts. It was developed using Anaconda and the Spyder IDE, as well as Pandas 1.3.4, NumPy 1.20.3, NumPy-Financial 1.0.0, and Matplotlib 3.4.3 Python libraries.
There are five files associated with CORRA. The first two files perform all calculations, while the other three contain data inputs and outputs for calculations.
- corra.py - the heart of the techno-economic analysis, performs cash flow calculations to arrive the LCOE.
- damage_tracking.py - carries out probabilistic analysis of wind turbine blade damage, inspection, and repairs.
- economic_parameters.cra - input for corra.py, contains a standard set of economic parameters needed for CORRA's cash flow calculations.
- standard_cost_inventory.cra - input for corra.py, contains a standard set of costs for land-based, fixed bottom offshore, and floating offshore wind turbines.
- matrix.cra - output of damage_tracking.py, input for corra.py, contains a matrix of average inspection and repair costs over the lifetime of a set of wind turbine blades.
To begin, the user should start by checking the three .cra files to ensure all parameters are defined as desired. The default data in the economic parameters and standard cost inventory files are based upon the National Renewable Energy Laboratory's Cost of Wind Energy Review. If users desire to change any of the default parameters in the economic parameters or the standard cost inventory, those changes should made manually within each .cra file.
For the matrix of inspection and repair costs, the matrix.cra file can either be manually altered, or generated using the damage_tracking.py code. Within the matrix.cra file, the first row is the year of operation, the fourth row is the average auunal inspection cost, and the fifth row is the average annual repair cost. The second and third rows are optional rows that can be used to track the actual and detected damage status. However, these second and third rows are not used in CORRA's calculations.
If using the damage_tracking.py code to alter the matrix.cra file, the user should review the input parameters within the damage tracking file including the blade lifetime, inspection period, repair trigger, repaired damage level, inspection cost and repair costs. Additionally, the growth probability and inspection probability can be changed based upon the type of damage and inspection being modeled.
Once the three .cra files has been properly adjusted, CORRA can be executed to evaluate the LCOE. To start, the user should run corra.py to activate the command line interface. Once the command line interface has been activated, the user should enter the "read" command to prompt different wind turbine configuration options. The user should then enter the desired configuration ("Land-Based", "Floating-Offshore", or "Fixed-Bottom-Offshore"). When the configuration is entered, CORRA will read in the standard cost inventory for that configuration. Following this step, the user has multiple options for subsequent commands.
- "solve" solves for the LCOE
- "increase" performs a sensitivity analysis on a range of parameters
- "summary" creates a summary of the techno-economic analysis
- "summary -g" creates a summary of the techno-economic analysis with graphs
- "help" provides command line assistance
CORRA is released under the Revised BSD license. See LICENSE.md for more details.
Evan Sproul, Sandia National Laboratories, [email protected]
Joshua Paquette, Sandia National Laboratories, [email protected]
Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.