Airborne Wind Energy Scoring System
This is just a framework designed to evaluate the performance and viability of different Airborne Wind Energy (AWE) systems. The score is calculated based on five key factors: PowertoWeight ratio, Cost of the System, Setup Time, the Number of People required to set up the system, and Average Wind Speed.
The scoring equation is:
Score = α(P/W) + ε(AvgWindSpeed)  β(Cost)  γ(SetupTime)  δ(SetupCrewSize)
 P/W (Power to Weight Ratio): This measures how much power the AWE system can generate per unit of weight. A higher P/W ratio indicates a more efficient design.
 Cost: This represents the total cost of the AWE system, including the upfront cost of the equipment, installation costs, and the cost of any necessary site preparation.
 Setup Time: This represents the time it takes to set up the AWE system.
 Setup Crew Size: This represents the number of people required to set up the AWE system.
 AvgWindSpeed (Average Wind Speed): This represents the average wind speed the system operates under. A higher average wind speed generally allows for more power generation.
The weights (α, β, γ, δ, ε) in the equation would be determined based on the relative importance of each factor, as decided by experts in the field or your own requirements.
Normalization
Normalization is a process that adjusts the individual numerical values measured on different scales to a notionally common scale. In this scoring system, we normalize each parameter to a common scale, for instance, a 010 scale. This involves choosing appropriate maximum and minimum values for each parameter. For example, if the maximum cost is $50,000 and the minimum is $0, the normalized cost for a system with a cost of $10,000 would be 1  10000/50000 = 0.8.
Scoring Equation
After normalization, the scoring equation becomes:
Score = α*(P/W normalized) + ε*(AvgWindSpeed normalized)  β*(Cost normalized)  γ*(SetupTime normalized)  δ*(SetupCrewSize normalized)
Where each normalized parameter is a value between 0 and 1.
Scoring systems across different fields are designed to provide a fair and objective way to compare performances, even when the conditions or participants are not identical. They often involve normalizing or adjusting raw scores based on certain factors. Here are a few examples:

Golf Handicaps: In golf, handicaps are used to level the playing field when players of different skill levels are competing against each other. A player’s handicap is a number that approximates the number of strokes above par that the player might make over the course of an average round. This allows players of different skill levels to compete against each other on an equal footing.

Sailing Classes and Handicaps: In sailing, boats are often divided into classes based on their design, size, and other characteristics. Within each class, boats compete directly against each other. However, when boats of different classes race together, a handicap system is used. The handicap is a factor that is used to adjust each boat’s finishing time, with the aim of making the race fair regardless of the boat’s class. The most wellknown handicap system is the Portsmouth Yardstick, which provides handicap numbers for a wide range of classes.

Renewable Energy: Comparing different forms of renewable energy, like wind, solar, and geothermal, involves considering a variety of factors, including the cost of installation, the amount of energy produced, the reliability of the energy source, and the environmental impact. These factors can be combined into a scoring system to provide an overall score for each type of energy. For example, the Levelized Cost of Energy (LCOE) is a common metric used in the power industry to compare the cost of different methods of electricity generation on a consistent basis. It represents the average revenue per unit of electricity generated that would be required to recover the costs of building and operating a generating plant during an assumed financial life and duty cycle.
In all these cases, the aim of the scoring system is to provide a fair comparison between different participants or options, taking into account the relevant factors for each field. The specific factors and the way they are combined can vary widely depending on the field and the specific goals of the scoring system.