• Energy Research

This paper presents a novel methodology for site selection of Offshore Renewable Energy (ORE) systems, addressing the growing global energy demand and the need for sustainable solutions to climate change. Focusing on the wave energy, a relatively untapped renewable energy source, this research focuses on optimizing the Wave Energy Converter (WEC) deployment amidst the uncertainties of the offshore environment. The study involves a comprehensive evaluation of potential sites, considering key factors like power generation capacity, mooring system fatigue life, and tether response to extreme loads. Initial wave data analysis for various locations is followed by numerical simulations of a point absorber WEC under different environmental conditions. A Bayesian Network (BN) model is then employed to integrate uncertainties into a multi-criteria decision-making (MCDM), enhancing the robustness of site selection. This approach facilitates the calculation of utility values for various sites, leading to the identification of the optimal decision alternative based on maximum expected utility. This work provides a detailed framework for renewable energy stakeholders, helping in the assessment of both profitability and survivability of WECs in chosen locations. It significantly contributes to minimizing economic and performance risks associated with ORE system installations, promoting efficient and sustainable energy production from ocean resources.

Green hydrogen is a key element that has the potential to play a critical role in the global pursuit of a resilient and sustainable future. However, like other energy production methods, hydrogen comes with challenges, including high costs and safety concerns across its entire value chain. To overcome these, low-cost productions are required along with a promised market. Offshore renewables have an enormous potential to facilitate green hydrogen production on a large scale. Their plummeting cost, technological advances, and rising cost of carbon pave a pathway where green hydrogen can be cost-competitive against fossil-fuel-based hydrogen. Offshore industries, including oil and gas, aquaculture, and shipping, are looking for cleaner energy solutions to decarbonize their systems/operations and can serve as a substantial market. Offshore industrial nexus, moreover, can assist the production, storage, and transmission of green hydrogen through infrastructure sharing and logistical support. The development of offshore green hydrogen production facilities is in its infancy and requires a deeper insight into the key elements that govern decision-making during their life-cycle. This includes the parameters that reflect the performance of hydrogen technology with technical, socio-political, financial, and environmental considerations. Therefore, this study provides critical insight into the influential factors discovered through a comprehensive analysis that governs the development of an offshore green hydrogen system. Insights are also fed into the requirements for modelling and analysis of these factors, considering the synergy of hydrogen production with the offshore industries, coastal hydrogen hub and onshore energy demand. The results of this critical review will assist the researchers and developers in establishing and executing an effective framework for offshore site selection in largely uncertain and hazardous ocean environments. Overall, the study will facilitate the stakeholders and researchers in developing ...

Abstract Deepwater drilling is one of the high-risk operations in the oil and gas sector due to large uncertainties and extreme operating conditions. In the last few decades Managed Pressure Drilling Operations (MPD) and Underbalanced Drilling (UBD) have become increasingly used as alternatives to conventional drilling operations such as Overbalanced Drilling (OVD) technology. These newer techniques provide several advantages however the blowout risk during these operations is still not fully understood. Blowout is regarded as one of the most catastrophic events in offshore drilling operations; therefore implementation and maintenance of safety measures is essential to maintain risk below the acceptance criteria. This study is aimed at applying the Bayesian Network (BN) to conduct a dynamic safety analysis of deepwater MPD and UBD operations. It investigates different risk factors associated with MPD and UBD technologies, which could lead to a blowout accident. Blowout accident scenarios are investigated and the BNs are developed for MPD and UBD technologies in order to predict the probability of blowout occurrence. The main objective of this paper is to understand MPD and UBD technologies, to identify hazardous events during MPD and UBD operations, to perform failure analysis (modelling) of blowout events and to evaluate plus compare risk. Importance factor analysis in drilling operations is performed to assess contribution of each root cause to the potential accident; the results show that UBD has a higher occurrence probability of kick and blowout compared to MPD technology. The Rotating Control Devices (RCD) failure in MPD technology and increase in flow-through annulus in UBD technology are the most critical situations for kick and blowout.

The move towards incorporating more-electric solutions in the transportation sector has gained increased momentum during the last decade. Cost of fossil fuels and environmental impacts of emissions are the main driving factors behind this growing trend. Nevertheless, advancements in battery technologies are the key enablers for the wide- spread application of electric alternatives in a more realistic manner. This paper looks into this trend from electric ferries perspective and presents a technical and economic feasibility assessment. The technical study includes sizing of the battery storage system based on Depth-of- Discharge (DOD) and maximum load scenario. The proposed sizing is validated against the measured load profile. The economic study includes initial investment, operational cost and maintenance cost of a battery powered electric ferry. The economic analysis considered the payback period (PBP) and battery lifecycles as assessment factors. The technical assessment results revealed that the proposed battery system can efficiently power the ferry within the stipulated DOD range. The maximum DOD achieved is 70 %, which provided a reasonable lifetime of 10.7 years. The economic analysis revealed that the battery's DOD has significant effects on the investment cost of the system and the PBP. The PBP is found to be 6.7 years which is 37 % less than the lifetime of the battery. Overall, the battery-powered ferry is found to be feasible with 51.3% operational costs saving compared to the diesel-electric alternative.

Offshore aquaculture industries face significant challenges in securing reliable and environmentally friendly energy sources. Among the possible solutions, wave energy converters (WECs) show a promising solution to transfer the technology for creating sustainable operations for remotely accessible fish farms. However, ideally integrating them into the aquaculture floating vessels necessitates a careful and thorough design approach. This paper presents a comprehensive framework for evaluating the performance of the AquaPower platform (APP) concept vessel in supporting offshore fish farm operations. Drawing inspiration from established WEC principles, this concept merges a floating platform with a tensioned mooring lines integrated with power take off systems connected to a moored vessel. The framework addresses crucial aspects, including power generation, structural resilience, and mitigation of mooring fatigue-induced deterioration, which are essential for optimizing the APP's performance. To enhance evaluation the reliability of the structure, the framework introduces a robust surrogate model based on Bayesian data analysis. This enables the assessment of mooring asset reliability and projected lifespan for real-time monitoring. The practical demonstration of this framework investigated through a case study for designing and evaluating the APP, effectively highlighting its potential as a feasible wave energy solution for the progress of offshore aquaculture towards blue economy technology. This paper's primary aim is to contribute to affirming the feasibility and viability of the APP concept as an effective and sustainable wave energy remedy for offshore aquaculture. The results of this study can be applied to other contexts, demonstrating the framework's ability to enhance the dependability of various offshore energy structures, including floating wind turbines, and extend their operational lifespan.

Comprehensive scrutiny is necessary to achieve an optimised set of operating conditions for a pyrolysis reactor to attain the maximum amount of the desired product. To reach this goal, a computational fluid dynamic (CFD) model is developed for biomass fast pyrolysis process and then validated using the experiment of a standard lab-scale bubbling fluidised bed reactor. This is followed by a detailed CFD parametric study. Key influencing parameters investigated are operating temperature, biomass flow rate, biomass and sand particle sizes, carrier gas velocity, biomass injector location, and pre-treatment temperature. Machine learning algorithms (MLAs) are then employed to predict the optimised conditions that lead to the maximum bio-oil yield. For this purpose, support vector regression with particle swarm optimisation algorithm (SVR-PSO) is developed and applied to the CFD datasets to predict the optimum values of parameters. The maximum bio-oil yield is then computed using the optimum values of the parameters. The CFD simulation is also performed using the optimum parameters obtained by the SVR-PSO. The CFD results and the values predicted by the MLA for the product yields are finally compared where a good agreement is achieved.

Abstract This study develops a novel and robust multi-criteria decision-making (MCDM) framework to determine the optimal offshore location for producing green hydrogen and a series of infrastructure planning measures. A range of factors, including technical, economic, environmental and safety, that govern the life cycle of offshore hydrogen facilities are incorporated into the model. An offshore wind-powered hydrogen system in the Bass Strait region of Australia has been considered as a case study to show the application of the developed framework along with the synergic benefits to nearby offshore industries. A GIS spatial analysis tool is utilized to rule out the unfeasible/constrained areas in compliance with national and international guidelines. TOPSIS MCDM technique is applied to weigh the criteria and rank the alternative locations. Based on hydrogen production capacity, cost and availability, various locations are ranked, illustrating their suitability. The developed framework demonstrated its high effectiveness in terms of extensive applicability and ease of usage. The outcomes of this investigation will assist the researchers and infrastructure developers in establishing and executing effective planning for offshore site selection in the largely uncertain and harsh ocean environment.

The Stirling cycle is useful in the marine environment because it can be driven by any heat source, such as solar, in times of direct sunlight or flared gas, when sunlight is inadequate. The ability to be powered from exhaust or flared gas makes it especially suited for offshore production facilities. In this work, a small 150 Watt solar powered gamma configuration Stirling engine was designed and constructed. Special care was taken when selecting construction materials. Solar power is provided by using a parabolic mirror to focus the sun's radiation onto the engine. Experimental testing was performed to determine the engine's power and torque characteristics, as well as solar performance. The engine was found to produce a maximum power output of 88 Watts at 245 RPM with a displacer temperature of 514°C. Comparisons of numerical and experimental results showed that the engine had a maximum mechanical efficiency of 90%.

This study investigated particle and gaseous emission factors from a large cargo vessel for her whole voyage including at berth, manoeuvring and cruising. Quantification of these factors assists in minimising the uncertainty in the current methods of exhaust gas emission factor estimation. Engine performance and emissions from the main marine engine were measured on-board while the ship was manoeuvring and cruising at sea. Emissions of an auxiliary engine working at 55% of maximum continuous rating (MCR) were measured when the ship was at actual harbour stopovers. Gaseous and particle emission factors in this study are presented in g kWh-1 or # kWh-1, and compared with previous studies. Results showed that the SO2 emission factor is higher than that of previous studies due to the high sulphur content of the fuel used. The particle number size distributions showed only one mode for different operating conditions of the ship, with a peak at around 40-50 nm, which was dominated by ultrafine particles. Emission factors of CO, HC, PM and PN observed during ship manoeuvring were much higher than that of those recorded at cruising condition. These findings highlight the importance of quantification and monitoring ship emissions in close proximity to port areas, as they can have the highest impact on population exposure.