Due to the options provided by the current wind reports, the requirements for an economic calculation of ballast have increased enormously. Contrary to the possibilities that somehow allowed the manual calculation of ballast in the past, the level of complexity has risen to such an allthat yit that it is simply no longer possible today.

We reacted to this and in December We mr. Dr. Raphael Wigoutschnigg (Univ.-Ass Dipl.Ing.an the University of Klagenfurt) employed by us and entrusted him with the topic of linear optimization. After 12 months of development work today, we can say that we are delivering optimal and unique results in this area.

What does linear optimization mean when calculating ballast?

Target functions to be achieved:

• Minimum costs
• Optimum load distribution
• Different methods of ballasting
  (stones, tubs, fixers)

Constraints that must be met:

• Consideration of displacement
• Securing against lift-off
• Consideration of load reserves
• Consideration of the different types of ballast
• Observance of the values for “Activated Modules”

Input:

• Module plan (automatic)
• Lifting and shifting forces per module (parameters, calculations)
• Stone types (manual/automatic)
• Types of tubs (manual/automatic)
• Stand: yes/no (manual selection)
• Properties Stand (parameters, calculations)
• Debug parameters
• Various options (manual selection, e.g.> “Is in California – connection to Attica)

Processing:

• Creation variables
• Creation target function
• Production of constraints
• Solution of the program
• Extraction of the solution

Expenditure:

• Tubs per element/stand
• Stones per element/stand
• Screws per stand

Linear programming (detail)

For the solution of the mathematical problem described above, the so-called integer linear programming (ILP) [8] is chosen.

The algorithm is characterized by its comparatively easy adaptability to specific questions and enjoys universal acceptance in professional circles. The limitation to linear relationships was accepted because the advantages (e.g. optimal distribution of weights to neighbouring PV modules) clearly outweigh the disadvantages (difficulties in generating aesthetic solutions).

A linear program consists of a linear target function, which is to be minimized or maximized and several linear constraints that must not be broken under any circumstances. The basis is variables that are either discrete (e.g. Bool’s variable or 0-1 variables, integer variables) and continuous variables (as an approximate representation of any real numbers).

Conclusion:

Planning remains simple and secure. A pre-assignment of the values can be made, then the planning remains correspondingly fast.

To further optimize the result, the user can make changes to the shared frame parameters at any time until the result of the ballast meets their wishes. Although the calculation of the program very quickly results in high double-digit possibilities in the millions range, there is no loss of performance, as the calculations take place in the appropriately equipped Levasoft cloud.