Abstract
To obtain a maximum power output and minimized capital and operational costs, the layout of wave energy parks needs to be optimally designed. An economical model for large-scale wave energy systems is built and merged into an evolutionary optimization routine for arrays of point-absorbing energy converters. The model includes all the parameters that affect the total system revenue such as electrical cable lengths, distance from grid connection point, number of substations and hydrodynamic interaction among the devices, with the goal to find the optimal layout which minimizes the levelized cost of electricity. Converters inside the park are grouped in clusters via a k-means clustering algorithm, which allows to minimize the intra-array cable length under the input of real wave climates. The results show that the hydrodynamical interaction has a large impact on the optimal design of wave energy parks, and that the length of the intra-array cable does not play a significant role in the economical layout optimization routine for the studied wave energy park system.
Highlights
The optimization of wave energy converter (WEC) arrays is one of the key factor for a successful commercialization of wave energy devices
If we consider the different wave directions studied, the results show that shadowed WECs have the highest levelized cost of energy (LCOE) and lowest net present value (NPV), while the line of WECs facing the incoming waves (y-waves, magenta lines) has significantly improved results, with a difference among them of up to 38% for 100 WECs rated 100 kW
A new model for the economical optimization of wave power systems has been presented. It is based on a genetic algorithm optimization routine coupled with an economical model used as evaluation function
Summary
The optimization of wave energy converter (WEC) arrays is one of the key factor for a successful commercialization of wave energy devices. The optimization proposed in this paper is performed using the genetic algorithm introduced by Giassi and Göteman [14] for the optimization of a single point-absorbing WEC, and subsequently extended for multiple WECs in Giassi and Göteman [15] and Giassi et al [16]. These studies focused on finding the best distribution of WEC units in a park, primarily considering power take-off characteristics and the geometrical layout of the array: a systematic search of the layout with the highest power production was implemented. The profitability of a wave energy park depends on economical aspects which cannot be neglected
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