The ocean acts as a giant battery for solar energy, converting it into the kinetic energy of waves. Devices that harvest this energy (wave floats, or converters) turn oscillatory motion into electric current. Their performance hinges on three parameters: geometric shape, spatial arrangement, and tuning parameters (e.g., damping). Historically, these parameters were optimized in isolation, ignoring their complex interplay in real sea conditions sea, where wave motion is irregular and multidimensional.

The proposed model integrates hydrodynamic calculations into a unified stochastic framework. The algorithm iterates over combinations of float geometry, relative positioning, and mechanical resistance, simulating system behavior across a wide range of weather scenarios. The goal is to find a configuration that maximizes power output while keeping the installation compact. A key role here is played by entropy, understood as a measure of uncertainty or disorder in the wave field. Rather than being a nuisance, entropy becomes a tool: the algorithm uses the principle of entropy minimization to search for the optimum — a state where the system's uncertainty (and hence losses) is minimal. This mathematical technique is borrowed from aviation engineering, where similar methods were used to model turbulence in jet engines.

The theoretical foundation of co-design goes back to the work of Daniel Bernoulli and Leonhard Euler on hydrodynamics, while the mathematical description of wave motion was developed by George Gabriel Stokes.