Development of a Multi-Objective Optimization Tool for Screening Designs of Taut Synthetic Mooring Systems to Minimize Mooring Component Cost and Footprint

Abstract

As the offshore wind industry develops, more lease sites in the intermediate water depth (50–85 m) are being released to developers. In these water depths floating wind turbines with chain catenary systems and fixed-bottom turbines with jacketed structures become cost prohibitive. As such, industry and researchers have shifted focus to floating turbines with taut or semi-taut synthetic rope mooring systems. In addition to reducing the cost of the mooring systems, synthetic systems can also reduce the footprint compared to a chain catenary system which frees areas around the turbine for other maritime uses such as commercial fishing. Both the mooring systems component cost and footprint are pertinent design criteria that lend themselves naturally to a multi-objective optimization routine. In this paper a new approach for efficiently screening the design space for plausible mooring systems that balance component cost and footprint using a multi-objective genetic algorithm is presented. This method uses a tiered-constraint method to avoid performing computationally expensive time domain simulations of mooring system designs that are infeasible. Performance metrics for assessing the constraints of candidate designs are performed using open-source software such as Mooring Analysis Program (MAP++), OpenFAST and MoorDyn. A case study is presented providing a Pareto-optimal design front for a taut synthetic mooring system of a 6-MW floating offshore wind turbine.