Levelised Cost of Energy assessment for offshore wind farms - an examination of different methodologies, input variables and uncertainty

Levelised Cost of Energy (LCoE) is the most common metric used in renewable energy assessments. However, this can be a very complex calculation with numerous methodologies depending on the perspective taken. Inputs including costs, energy production are generally forecasts and predictions based on publicly available information; therefore they are key areas of uncertainty. Elements of the calculation are site or region specific such as the tax rate or inclusion of grid connection costs. The business case and financial assumptions applied will be very project specific e.g. the discount rate applied. These numerous variables and uncertainties must be fully understood in order to effectively apply the metric or review and compare LCoEs. Therefore, this paper provides a comprehensive set of LCoE methodologies that provide a reference basis for researchers. A case study demonstrates the application of these methods and the variation in results illustrates the importance of correctly selecting the discount rate and cash flow based on the perspective and motivation of the user. Sensitivity studies further investigates the potential impact of key variables and areas of uncertainty on results. Analysis indicates that the energy production and discount rate applied will have the most significant impact on LCoE, followed by CAPEX costs. While the key areas of uncertainties cannot necessarily be solved, this paper promotes consistency in the application and understanding of the metric, which can help overcome its limitations

Investigating Key Decision Problems to Optimize the Operation and Maintenance Strategy of Offshore Wind Farms

This paper investigates three decision problems with potential to optimize operation and maintenance and logistics strategies for offshore wind farms: the timing of pre-determined jack-up vessel campaigns; selection of crew transfer vessel fleet; and timing of annual services. These problems are compared both in terms of potential cost reduction and the stochastic variability and associated uncertainty of the outcome. Pre-determined jack-up vessel campaigns appear to have a high cost reduction potential but also a higher stochastic variability than the other decision problems. The paper also demonstrates the benefits and difficulties of considering problems together rather than solving them in isolation

A lifecycle financial analysis model for offshore wind farms

Simulation and modelling allow a range of offshore wind farm stakeholders to test and improve a project's viability in a cost-effective and safe manner. This paper presents a model developed to conduct detailed financial analysis of an offshore wind farm. It extends the current state of the art by employing stochastic time-series simulation modules performing in-depth analysis of the technologies, strategies and procedures applied during the installation, operation and maintenance, and decommissioning phases of a wind farm lifecycle. The model was designed for versatility and can consider both fixed and floating technologies, a wide variety of strategies, and any site specified by the user. Results include energy production, costs and the duration of activities at each stage. These populate financial spreadsheets, which calculate key performance indicators including the Levelised Cost of Energy. The model has been successfully validated against real-life case-studies where possible; published data; and uses sensitivity analysis to ensure the model is working as expected. Through a case-study, the paper demonstrates how 1) the model enables the identification of key cost and time drivers, facilitating scenario optimisation; 2) the stochastic nature of the model considers the impact of uncertain variables on results such as weather conditions and wind turbine failure rates; 3) the model can be used to assess different business models and financing structures. This comprehensive range of abilities means that the model is suited to a variety of end-users and meets the demands of a growing industry, striving to achieve further cost-reductions across a range of site conditions, technologies and markets.A lifecycle financial analysis model for offshore wind farmsacceptedVersio

Life cycle assessment of a lift-based wave energy converter

Evaluating the overall advantages of a new configuration of wave energy technologies goes beyond techno-economic performance and reliability. As the marine renewable energy sector expands, it is important to ensure that the technologies prove to be environmentally friendly alternatives. A cradle-to-grave life cycle assessment was conducted on a novel energy converter (LiftWEC) to evaluate its potential cumulative impacts. The global warming potential was characterized, indicating that the configuration could be a potential low-carbon alternative compared with many wave energy devices and conventional forms of energy production. The carbon and energy payback time were also analysed to estimate the time required to offset the carbon emission and demanded energy. This assessment highlighted the impact of the characteristic energy mix profile and energy production potential of the deployment region on the results obtained. The study also analysed alternative scenarios of materials, deployment locations, and end-of-life strategies to identify potential improvement opportunities to reduce the environmental impacts

Applications of robotics in floating offshore wind farm operations and maintenance: Literature review and trends

Marine operations required to transfer technicians and equipment represent a significant proportion of the total cost of offshore wind. The profile of sites being considered for floating offshore wind farms (FOWFs), e.g., further from the shore and in harsher environments, indicates that these costs need to be assessed by taking into account the maintenance requirements and restricted weather windows. There is an immediate need to investigate the potential use of robotic systems in the wind farm's operations and maintenance (O&M) activities, to reduce the need for costly manned visits. The use of robotic systems can be critical, not only to replace repetitive activities and bring down the levelised cost of energy but also to reduce the health and safety risks by supporting human operators in performing the desired inspections. This paper provides a review of the state of the art in the applications of robotics for O&M of FOWFs. Emerging technology trends and associated challenges and opportunities are highlighted, followed by an outline of the agenda for future research in this domain. </p

The LEANWIND suite of logistics optimisation and full lifecycle simulation models for offshore wind farms

The offshore wind sector has achieved significant cost reductions in recent years. However, there is still work to be done to maintain and surpass these savings across current and future farms. There is increased competition to reduce costs within the industry itself. Additional challenges are foreseen at future sites located further from shore, in harsher conditions and deeper waters. Larger turbines and projects also mean new equipment, logistics and maintenance requirements. Moreover, farms are approaching the decommissioning phase where there is little experience. Modelling is a safe and cost-effective way to evaluate and optimise operations. However, there is a lack of comprehensive decision-support tools, detailed enough to provide insight into the effects of technological innovations and novel strategies. To address the gap, the EU FP7 LEANWIND project developed a suite of state-of-the-art logistics optimisation and financial simulation models. They can assess a farm scenario in detail at every stage of the project lifecycle and supply-chain, identifying potential cost reductions and more efficient strategies. This paper introduces the models including: an overview of their scope and capabilities; how they can be applied; and the potential end users