# Alanna Joachim

Link to Student
Journal Entry For
Module 8 - Share Your Design

# OffsureWind: What you need to know to get started!

A new tool to streamline the offshore wind bidding process! This tool allows bidders to automate the bidding process, evaluate the worth of pursuing a bid on a project, and calculate their financial risk. Build your own wind farm by choosing turbine pile dimensions, size, and distance from shore. Input your bid and see how your bid compares to other competitive offers for similar sized wind farms. Using the Offsure Wind tool can help you navigate the otherwise complex process of gaining local acceptance for a project, making a competitive bid, and evaluating environmental conditions of the site without having to hire outside experts and consultants!

# Dynamo Script

Pink = relating to the Revit element geometry

Orange = relating to the shore line node and the distance of the turbines to shore

Purple = relating to the individual turbines in the wind farm

Blue = relating to the wind farm as a whole

Green = relating to the financial metrics associated with the wind farm

In the script, a grid of points are created using X and Y coordinate and spacing sliders that can be flexed by a user. Revit elements (wind turbine adaptable components from Revit City) are added onto each grid point and the distance is calculated from each point to the attractor point which is considered the “shore”. The further away these turbines are from the shoreline, the better. By counting the total number of wind turbines the total capacity of the wind farm can be calculated by using the height of each turbine, which can be flexed by the user, as well as the radius. By doing research on offshore wind turbines and financial risk and using knowledge from an undergraduate course, I created constants for different costs associated with the offshore wind turbine bidding process and used these to calculate financial costs and risks.

## Inputs, Constants, and Brief Description of Calculations:

Inputs for the tool include the height of the turbine from the base to the rotor, as well as the radius of the pile base. The wind turbines were created using a Revit family component which was imported and adapted to make the height and radius adaptable by adding dimensions as parameters. This made it easy to flex the Revit geometry in the Dynamo Player.

Outputs include different metrics that measure local community acceptance, both turbine and wind farm energy production and capacities, and a variety of financial outputs that will allow the user to measure how likely they are to acquire the project given their inputted bid, evaluate their financial risk. Local community acceptance is determined the same way as it was in Module 7 by finding the closest point in the grid and determining if the distance is over 15 miles from the shoreline point. If the lowest acceptance metric for the wind farm is over 1, the wind farm will be accepted by the local community because it is more than 15 miles from shore.

Financial risk is determined by inputted soil quality (%), with 100% being very good soil quality and 0% denoting very poor soil quality for foundations. Financial risk is determined as the capital investment * the probability that the site will not be buildable. Higher wind speeds provide a higher potential that the site will be buildable, since higher wind speeds will be able to generate a more reliable energy supply for the turbines. The wind speeds is capped at a researched typical optimal rated wind speed for offshore turbines. Other cost outputs include the cost to procure the project (bid price + capital investment), which denotes the price in millions that will need to be put down on the project before the project can begin generating profit. Revenue for the wind farm and the Levelized Cost of Energy is also calculated. The Levelized Cost of Energy (LCOE) is the cost that the electricity generated by the wind turbine farm would need to cost in order to break even on the cost of the project over its life time. A low LCOE is better for the bidder and owner of the wind farm.

All of these inputs and outputs provide the user the flexibility to explore how the size of their wind farm and the type of turbines used can affect the financial aspect of their project. The offshore wind industry and the bidding process is complex and this tool is aimed to allow bidders to easily calculate and access the financial benefits and risks of the choices they can make.

## Outputs:

### Supporting Nodes

Shoreline Nodes

Revit Geometry Nodes

Turbine Specific Nodes

Wind Farm Geometry Nodes

Financial Calculation Nodes

## References

https://www.energy.gov/eere/articles/wind-turbines-bigger-better

https://www.e-education.psu.edu/eme801/node/557