Interdependency of human factors and turbine state in offshore wind farm operations

The effectiveness of operation and maintenance (O&amp;M) activities significantly impacts the availability of offshore wind farms (OWFs) and the total cost of energy production. When a turbine is stopped to rectify a failure of any critical equipment or to perform preventive maintenance, there is a substantial cost for repair or replacement. Simultaneously, there is a production loss associated. Humans play a critical role in every stage of the O&amp;M in the offshore wind industry. Human errors may jeopardize maintenance effectiveness, increase a system s failure rate, or cause faster degradation, which may have substantial costs to the entire operation and cause pressure on the production to compensate for the downtime. This production pressure and repair cost pressure directly impact human performance, for instance, by shortening the time available to complete required maintenance activities. The cost pressure may also affect the industry s operational budget, leading to hiring less trained and inexperienced maintenance crews or postponing training. These effects may lead to failure in different maintenance phases, including fault diagnosis and mistakes during repair tasks, further increasing human error probability (HEP). This paper proposes a causal loop diagram for the maintenance system of the offshore wind turbine, accounting for the interdependencies amongst human error likelihood, equipment health state, and associated uncertainties. By implementing various maintenance planning approaches, the dynamics of the system are modelled with more accuracy to identify the factor affecting the maintenance strategy and minimize human errors in the O&amp;M of OWFs.</p

A Novel Approach to Environmental Risk Mitigation During Construction and Installation of a Wind Farm

Offshore structures and operations significantly impact the surrounding environment, and future offshore renewable energy developments are no exception. Many Australian offshore oil and gas platforms have the potential to act as artificial reefs, creating an excellent opportunity for the growth of marine communities that are often in danger due to other human activities or environmental impacts. Decommissioning of these platforms will impose substantial risks to the existing ecosystem in those habitats. Therefore, there is a need to understand the environmental impacts of installation, operation, and maintenance (O&amp;M) and decommissioning activities in new offshore renewable energy infrastructure prior to developments. This becomes more important in the case of future offshore wind farm development in Australia, where no historical information is available. This paper proposes a game-theoretical approach to identifying the optimum risk mitigation strategies for minimizing the environmental impact of future offshore wind infrastructure and operations. As a case study, the method is applied to examine the risks imposed by constructing and installing an offshore wind farm in the Bass Strait. The governments and regulators can adopt the proposed mitigation strategies to develop policies and legislation to ensure the sustainability of marine environments.</p

Modelling error chains in offshore wind energy systems: Examining the interplay of human performance and machine state

A dynamic model of the mutual interdependency between humans and machines in offshore wind farms (OWFs) is developed in this paper. The model emphasises the importance of having early indicators to dynamically moderate human behaviour and the need to account for both human and physical subsystems and their mutual interactions for optimal asset management practices. This work simulates three distinct scenarios for: (1) examining the interconnectedness of technical and human dynamics and their implications on error and failure; (2) assessing the impact of production loss on human and organisational behaviour; and (3) evaluating human error probability as an early warning sign of production loss. The findings suggest that adopting an appropriate maintenance culture and considering human error likelihood and production rate in decision-making leads to optimising production and mitigating the risks associated with human error. The research highlights the significance of comprehending the complex interactions between human and machine factors in the operation and maintenance (O&amp;M) of offshore wind turbines (OWTs). The proposed dynamic model helps organisations identify the underlying causes of errors, allowing them to improve their maintenance strategies.</p

A system dynamics model of offshore wind farm degradation: Enabling operation and maintenance planning under foreseen asset management impacts

This paper presents a system dynamics model to for the degradation of offshore wind farms (OWFs) optimise O&amp;M planning and asset management, taking into account the effects of weather-related delays. The model predicts the future states of wind turbines, repairs, downtime expenses, failures, and production losses. Simulation results show the optimal scenario for effective intervention and the adaptability of the proposed model in controlling wind farm assets. By considering various maintenance planning approaches, the model identifies the factors affecting maintenance and minimises the impact of human response on O&amp;M activities in OWFs.</p

The Game of Guwarra: A game theory-based decision-making framework for site selection of offshore wind farms in Australia

Global concerns around climate change and the volatility of conventional fuel prices have prompted researchers and technologists to make significant efforts to identify and exploit alternative energy sources that are cleaner and more sustainable. Wind energy has seen considerable development among these alternative energy sources, mainly due to its abundance and global availability for extraction and the existing knowledge within the aviation and aerospace fields. Many nations, including European countries, already operate offshore wind farms (OWFs) and are progressively carrying out new projects and expanding on other projects. The Australian offshore environment provides unique opportunities for wind energy extraction, particularly along the southern coast of mainland Australia and the regions around Tasmania, where substantially strong winds blow most of the year. A significant challenge to establishing wind farms is the selection of site locations with optimal outputs. This can become a complex decision-making problem if there are numerous options and no information from previous projects. This paper aims to develop a decision-making framework to select the optimal location for installing OWFs while addressing financial, performance-related, and availability-related objectives. This paper adopts a game-theoretical approach to develop a decision-support tool to account for the interdependencies of influencing factors and possible conflicts amongst the parties. The game model is applied to an OWF development case study in the Bass Strait, known for its dominant and strong winds.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Wind EnergySafety and Security Scienc