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

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. INTRODUCTION The United States, in addition to countries around the world, is actively supporting avenues for expanding its energy portfolio to include sources that are renewable and locally accessible. The White House and Department of Energy (DOE) have set guidelines for reducing dependence on foreign oil and better implementing water power methods. More specifically, the U.S. is seeking to generate 80% of its energy using renewable sources by 2035 and to achieve an 80% reduction in carbon emissions by 2050 [1]. Consequently, with over 50% of the U.S. population living in close proximity to an ocean coastline [2], research and development has been ongoing in the realm of ocean energy – specifically in regards to the extracting of energy from ocean waves. The estimated global amount of energy in ocean waves is between 16,000 TWh per year and 18,500 TWh per year [3]. Quantified, one terawatt-hour of generated electricity is roughly the amount of energy that 9,000 U.S. homes use over the course of a year [4]. Furthermore, in the United States, the recoverable ocean wave resource is estimated to be approximately 1,170 TWh per year [5] which could provide the electricity needed by over one million homes. In Hawaii, Alaska, and Oregon, states with prime wave resources, wave energy could potentially supply 100%, 100%, and 57% of these states’ respective energy needs [1]. Due to the number of individuals residing near an ocean, the push to develop and implement renewable energy sources, and the quantity of energy to be extracted from the ocean, wave energy is a promising source of electricity for which there are many devices under development that are nearing the point of full-scale ocean deployment. Following ocean deployment of individual devices, developers are planning the implementation of arrays of devices to provide grid-connected power to a large consumer base with many needs. The process of developing wave energy converter (WEC) arrays involves comprehending and overcoming associated challenges such as volatile sea states and associated costs. As it is vital that the industry be well-informed regarding the potential deployment of WEC arrays to ensure survival and future competitiveness, determining optimal array configurations at this stage in research is essential.