Computationally efficient optimisation algorithms for WECs arrays

In this paper two derivative-free global optimization algorithms are applied for the maximisation of the energy absorbed by wave energy converter (WEC) arrays. Wave energy is a large and mostly untapped source of energy that could have a key role in the future energy mix. The collection of this resource has been largely hindered by the cost of energy (CoE) of the technical solution proposed so far. A simple way to reduce the CoE and thus make technologies market competitive is to implement arrays of WECs to share costs, increase the installed capacity and smoothen the highly fluctuating power output. Although started in the late seventies, the topic of WEC array optimisation has gathered a renovated interest mostly in the last decade, and a number of different approaches has been already used, from traditional algorithms to heuristic ones. The objective of this paper is to present a comparison between derivative-free global optimisation algorithms. In particular, evolutionary strategies (CMA-ES) and metamodel based optimisations algorithms are compared in terms of accuracy and computational time.