Multidisciplinary Optimization to Reduce Cost and Power Variation of a Wave Energy Converter

Abstract

Wave energy converters (WECs) can advance the global energy transition by producing clean power for utility grids and offshore technologies. This paper provides a multidisciplinary, dual objective optimization of the Reference Model 3 (RM3), a two-body point absorber WEC design benchmark. The simulation model employs linear hydrodynamics with force saturation and probabilistic waves. The RM3 geometry and controller parameters are optimized using sequential quadratic programming to minimize the levelized cost of energy (LCOE) and the coefficient of variation of power. The minimum-LCOE design produces a power variation of 205% and an LCOE of $0.08/kWh, a seven-fold cost reduction and 23% lower variation from the RM3 baseline of $0.75/kWh and 255% variation. Parameter sensitivities show that LCOE depends more strongly on site and economic parameters than geometric or material parameters, while power variation is largely insensitive to all parameters. A Pareto trade-offbetween cost and power variation reveals different optimal designs depending on which objective is prioritized, suggesting application-specific design heuristics. Three representative optimal designs are investigated: a minimum-LCOE design for cost-sensitive operations like utility power, a minimum-variation design for cost-insensitive installations like small offshore systems, and a balanced design for intermediate applications. Power probability distributions are shown for each.