Layout Optimization Process to Minimize the Cost of Energy of an Offshore Floating Hybrid Wind–Wave Farm

Abstract

Offshore floating hybrid wind and wave energy is a young technology yet to be scaled up. A way to reduce the total costs of the energy production process in order to ensure competitiveness in the sustainable energy market is to maximize the farm’s efficiency. To do so, an energy generation and costs calculation model was developed with the objective of minimizing the technology’s Levelized Cost of Energy (LCOE) of the P80 hybrid wind-wave concept, designed by the company Floating Power Plant A/S. A Particle Swarm Optimization (PSO) algorithm was then implemented on top of other technical and decision-making processes, taking as decision variables the layout, the offshore substation position, and the export cable choice. The process was applied off the west coast of Ireland in a site of interest for the company, and after a quantitative and qualitative optimization process, a minimized LCOE was obtained. It was then found that lower costs of ~73% can be reached in the short-term, and the room for improvement in the structure’s design and materials was highlighted, with an LCOE reduction potential of up to 32%. The model serves usefully as a preliminary analysis. However, the uncertainty estimate of 11% indicates that further site-specific studies and measurements are essential.

Breaking-Down and Parameterising Wave Energy Converter Costs Using the CapEx and Similitude Methods

“…The expenses for location assessment, such as (i) bathymetry and seabed conditions, (ii) wave and weather climate, and (iii) energy demand infrastructures are also added. These three aspects will then help to select the most appropriate WEF design for the location of interest, which includes decisions on the number of WECs and the WEC configuration [35,48,51,53,54,70]; the installation location [61,[71][72][73], the WEF arrangement, particularly regarding park effects and wave direction impact [72]; and the selection of cables, moorings, and anchors [25,57,60,74]. (b) Construction and installation costs of the WEF for each location.…”

“…(c) Chang et al [24] amongst others [35,47,48], have estimated the cost for most of the devices investigated by Barbarit et al [49]. Furthermore, specific costs have also been provided for CorPower Ocean [50,51], Pelamis and Wavestar [52], Wave Dragon [53], Floating Power Plant A/S [54], M4 [55], and Seabased Industry AB [56], to name a few. These studies mainly used selected economic indicator-based equations such as the LCoE.…”

Control and Optimization of Multi-Agent Systems and Complex Networks for Systems Engineering

“…The rest of the papers of this Special Issue can be classified into three key areas: (i) infrastructure management [3,4]; (ii) manufacturing and industrial processes [5][6][7][8]; and (iii) energy production processes [9][10][11].…”

Strategically estimated CapEx: wave energy converter costs breakdown and parameterisation

“…These three aspects will then help in selecting the most appropriate WEF design for the location of interest, which includes decision on the number of WECs and the WEC configuration [20,33,36,38,39,54], the location of installation [46,[55][56][57], the WEF arrangement, particularly regarding park effects and wave direction impact [56], and the selection of cables, moorings, and anchors [9,42,45]. of 2.…”

“…Chang et al [8] amongst others [20,32,33], have estimated the cost for most of the devices investigated by Barbarit et al [34]. Furthermore, specific costs have also been provided for CorPower Ocean [35,36], Pelamis and Wavestar [37], Wavedragon [38], Floating Power Plant A/S [39], M4 [40], and Seabased Industry AB [41], to name a few. These studies mainly used selected economic indicator-based equations such as the LCoE.…”