Modelling of operation and optimum design of a wave power take-off system with energy storage

Markos I. Bonovas and Ioannis S. Anagnostopoulos

Renewable Energy, 2020, vol. 147, issue P1, 502-514

Abstract: Wave energy is claimed to be the most powerful source of renewable energy and at the same time an area of research with many prospects for development. The subject of the present analysis is a case study of a heaving wave energy converter harnessing and storing wave energy to an onshore hydroelectric plant through water pumping. During the first phase the system variables of wave amplitude and period are fixed as the characteristics of an Airy Theory-based model. Construction parameters are optimized by evolutionary algorithms, incorporated in EASY software with two objective functions: the total investment cost and the flow rate in the reservoir. The following dynamic analysis is performed depending on the optimum set of parameters but also is constrained by criteria of operation. A maximum capture width ratio of 45% for a standard harmonic wave is achieved, which is comparable with other WECs' performance. Sensitivity tests for the free design parameters of the mechanism are also carried out. For a more realistic scenario of sea states, a specific area's wave time series provided the yearly corresponding duration curves and a second optimization analysis is performed. The attainable average efficiency (stored energy) of the system was almost 20%, showing high sensitivity of the absorbed power on the sea state. In order to increase the annual energy absorption and storage of a single device at real sea conditions, a mechanism for real-time adjustment of the piston pump diameter to better comply with varying wave characteristics, is proposed and modelled. The design of the modified system is optimized again to demonstrate its improved performance and efficiency, which is about 30% higher than the initial design.

Keywords: Renewable energy; Wave energy converter; Energy storage; Point absorber; Optimization; Evolutionary algorithms; Real-time adjustment (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:147:y:2020:i:p1:p:502-514

DOI: 10.1016/j.renene.2019.08.101

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