Renewable wave energy potential for the sustainable offshore oil platforms in South China Sea

• Main Authors: Nizamani, Z., Na, L.L., Nakayama, A., Ali, M.O.A., Nizamani, M.A.
• Format: Article
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117137878&doi=10.1109%2fACCESS.2021.3104729&partnerID=40&md5=d6e6477b2a38c140c3f416ea46b2f459; http://eprints.utp.edu.my/29406/
• Institution: Universiti Teknologi Petronas

The Jacket platform needs gas and diesel to run its turbines, and in the end, they produce catastrophic emissions annually. The environmental concerns regarding these platforms have forced us to utilize an alternative source of energy that is sustainable and clean. In this study 51 locations, are of interest where oil and gas activities are in progress at present in the shape of a jacket platform or pipelines. The significant wave height and wave period scatter diagram data are collected from the platforms in the South China Sea. The linear wave theory is used to find the wave power. The given time period is converted into an equivalent time period first before wave energy is determined. The study shows that location no. 20 is the ideal location to deploy the wave energy converter Pelamis P2 with a potential mean wave power of 6.61 kW/m A single unit of Pelamis P2 can produce on an average electricity output of 91.37 kW/m including, the losses and machine efficiencies, whereas a wave farm can generate an average output of 62 GWh/yr. The electricity supply of 70.3 of the minimum and 14.1 of the maximum energy demand, while using only wave energy converter. If hybrid wind and wave energy system is used, then energy production will increase. The results show that the wave farm could also reduce the use of natural gas up to 17.6E06 m3/year, avoiding the emission of 12000 tonnes of CO and 54000 tonnes of NOx annually, and can save up to RM 20 billion annually with the reduction of natural gas emissions. © This work is licensed under a Creative Commons Attribution 4.0 License.