A Multi-Objective Real-Coded Genetic Algorithm Method for Wave Energy Converter Array Optimization Available to Purchase

For consumers residing near a coastline, and especially for those living or working in remote coastal areas, ocean energy is a promising source of electricity that has the potential to serve as a primary energy source. Over the last decade, many wave energy converter (WEC) designs have been developed for extracting energy from the ocean waves, and with the progression of these devices’ ocean deployment, the industry is looking ahead to the integration of arrays of devices into the grid. Due to the many factors that can potentially influence the configuration of an array (such as device interaction and system cost) optimal positioning of WECs in an array has yet to be well understood. This paper presents the results of a novel real-coded genetic algorithm created to determine ideal array configurations in a non-discretized space such that both power and cost are included in the objective. Power is calculated such that the wave interactions between devices are considered and cost is calculated using an analytical model derived from Sandia National Laboratory’s Reference Model Project. The resulting layouts are compared against previous array optimization results, using the same constraints as previous work to facilitate algorithm comparison. With the development of an algorithm that dictates device placement in a continuous space so that optimal array configurations are achieved, the results presented in this paper demonstrate progression towards an open-source method that the wave energy industry can use to more efficiently extract energy from the ocean’s vast supply through the creation of array designs that consider the many elements of a WEC array.