Alanna Joachim

Alanna Joachim


Offshore wind is an field that is quickly gaining traction in the field of renewable energy. However, the process is still new and not very well automated, often heavily dependent on the politics and logistics of the bidding process. My goal for this project was to create a product that could help automate and streamline the bidding process for offshore wind projects in the United States.

Intended Users

Offshore Wind Farm Bidders

Common Problems Faced by Users

  • Uncertain environmental conditions in bidding locations
  • Budgetary constraints and competitive, fast paced bidding environment
  • Lack of local community acceptance for most projects
  • Overwhelming amount of information to consider for each site, with many sites up for bid

Need you’re trying to provide a solution or support for

  • More automated bidding process
  • Flexibility and accessibility to optimization and exploration of tradeoffs rather than having to hire outside consultants

How will this product help solve these problems and fulfill these needs?

  • Helps to determine optimal placement of offshore wind turbines
  • Evaluates the advantages of different locations and sizes for wind farm turbines based on a variety of factors


Design Variables:

  • Wind turbine height (ft)
  • Turbine radius (ft)
  • Wind farm grid - # of points in X direction
  • Wind farm grid - # of points in Y direction
    • Make a grid of wind turbine placement points
    • Place a turbine on each of these points
  • Soil Quality
  • Average Wind Speed
  • User budget / bid amount
  • Service life (usually between 15-25 years on average)


  • Labor cost ($/ distance from shore in miles)
  • Competitive Bid price ($/MWh)
  • Operations cost ($ / MW of capacity)
  • Energy capacity (MW /turbine height)
  • Capital investment ($/MWh)
  • Electricity Selling price ($/MW)

Underlying logic of the model you’ll implement

This model will determine the choice of dimensions for wind turbines and the size of the wind farm size (a UV grid). The application will calculate the costs associated with the wind farm as well as the amount of energy this size wind farm can generate in total. The acceptance of the local community will be measured by how far the closest point in the UV grid is away from the shore. Based on these inputs, a competitive bid price will be calculated to help the bidder gauge if they have a good chance of winning the bid for this project and if it is within their budget.

The goal of this tool is to act as a Configurator, and it will use different rules to calculate the financial outputs as well as size the wind farm based off of the user inputs.


  • Total Cost of Labor and Operations for the wind farm ($)
  • Energy Generation for the wind farm (MW) and of a singular turbine
  • Local community acceptance (custom evaluation for a numerical metric that designates how accepting the local community would be to this design)
  • Probability of getting the bid
  • Calculation of financial risk
  • Total cost to procure and begin using energy
  • Initial return on investment
  • Total revenue of the windfarm
  • Levelized Cost of Energy (LCOE)