Constrained optimization of the shape of a wave energy collector by genetic algorithm

Wave energy extraction requires the conversion of the energy within the waves to drive the power take off system, often by means of a principal interface, or collector. This paper describes part of the development of a robust, systematic method of optimizing the collector shape to improve energy extraction using a genetic algorithm. The collector geometry uses a parametric description based upon bi-cubic B-spline surfaces, generated from a relatively small number of control points to reduce the dimensionality of the search space. The collector shapes that are optimized have one plane of symmetry and move in one degree of freedom (surge). Each candidate shape is assessed in a wave climate based upon data from a site in the North-East Atlantic Ocean. Three cost functions, distinguished by the severity of the penalty put on the size of the candidate collectors, and four constraint regimes, defined by two displacement and two power rating limits, are the governing influences on the twelve optimization procedures described. The selected collector shapes from each optimization run are appraised in terms of size, complexity and their performance compared to that of ‘benchmark’ box-shaped collectors