Abstract
Wave energy has a promising technical potential that could contribute to the future energy mix. However, costs related to the deployment of wave energy converters (WECs) are still high compared to other technologies. In order to reduce these costs, two principle options are available, a reduction in cost and an increase in productivity. This paper presents a reliability-based computational tool to identify typical decision problems and to shed light on the complexity of optimising a wave power farm. The proposed tool is used to investigate productivity and availability of a wave energy farm during 10 years of operational life. A number of optimization possibilities to improve productivity, namely vessel choice, maintenance regime, failure rate and component redundancy, are then explored in order to assess their effectiveness. The paper quantifies the yield increase and provides a practical approach to evaluate the effectiveness of strategic and operational decision options. Results, in terms of the variations in productivity and availability of the farm, are analysed and discussed. Conclusions highlight the importance of reliability-centred simulations that consider the specific decision parameters throughout the operational life to find suitable solutions that increase the productivity and reduce the running cost for offshore farms.
Highlights
During recent decades, the quest for alternative forms of producing energy has included the double aim of satisfying the increasing energy demand and lowering the pollutant emissions on the environment
Due to the high costs related to the deployment of wave energy devices, the cost of energy (CoE) associated to wave power is still too high to be competitive with that of conventional fossil fuel power plants
Among other tools, a number of computational models have been created in the last few years to simulate the lifecycle logistics of an offshore farm and assess performance
Summary
The quest for alternative forms of producing energy has included the double aim of satisfying the increasing energy demand and lowering the pollutant emissions on the environment. Both these enhancements aim to increase the productivity and reduce the running costs of wave energy converters (WECs) which, in turn, will lead to an increase in their competitiveness in the electricity market [3,4] To achieve this goal, among other tools, a number of computational models have been created in the last few years to simulate the lifecycle logistics of an offshore farm and assess performance. Martin et al [9] emphasize the importance of a sensitivity analysis in identifying the factors affecting operational costs and availability of an offshore wind farm, indicating access and repair costs as major contributors to the total O&M costs Most of these models permit the analysis of different aspects of the power plant, allowing the selection of the best combination of parameters in order to maximize the incomes of the electricity sale and minimise the expenses. Outputs are provided in the form of key performance indicators illustrating and comparing the variouss opoptitoinosnsin itnermtesrmofsreolifabrileiltiya,baivliatyil,abailvitayilanbdilimtyaianntadinambailiintytaoinf athbeiliftayrmo.fThtheese cfaormmp.reThheensde, bcoumt aprreenhoent dlim, biutetdartoe:not limited to:
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
