Predictive maintenance logistics for offshore wind farms

This report contains a summary of state-of-the-art for maritime logistics planning of maintenance activities at offshore wind farms within mathematical programming and simulation. It presents a description of a shift from a preventive and corrective maintenance paradigm to a predictive planning regime and its effect on the modelling approaches for maritime logistics planning. A planned innovation in NorthWind: SmartMOW is presented where the plan is to integrate information on degradation of components from digital twins. This report has been prepared as part of NorthWind (Norwegian Research Centre on Wind Energy) co-financed by the Research Council of Norway, industry and research partners. Read more at www.northwindresearch.no.publishedVersio

Vessel Fleet Optimization for Maintenance Operations at Offshore Wind Farms under Uncertainty

In this paper we consider the problem of determining the optimal fleet size and mix of vessels to support maintenance activities at offshore wind farms. A two-stage stochastic programming model is proposed where uncertainty in demand and weather conditions are taken into account. The model aims to consider the whole life span of an offshore wind farm, and should at the same time remain solvable for realistically sized problem instances. The results from a computational study based on realistic data is provided.publishedVersio

A model for optimal fleet composition of vessels for offshore wind farm maintenance

We present a discrete optimisation model that chooses an optimal fleet of vessels to support maintenance operations at Offshore Wind Farms (OFWs). The model is presented as a bi-level problem. On the first (tactical) level, decisions are made on the fleet composition for a certain time horizon. On the second (operational) level, the fleet is used to optimise the schedule of operations needed at the OWF, given events of failures and weather conditions

Improving global accessibility to offshore wind power through decreased operations and maintenance costs: a hydrodynamic analysis

Improved access to renewable energy in developing economies will be a major factor in future global efforts to reduce CO2 emissions, while simultaneously raising living conditions in areas presently without or with only limited access to electricity. Coastal populations stand to benefit greatly from reduced costs of offshore wind farms, which are one of the fastest growing and most economical sources of marine renewable energy. A considerable drawback of offshore wind power is the high cost of operations and maintenance (O&M), which can account for 25-50% of total energy production costs. Present-day maintenance procedures, using crew transfer vessels, rely on the significant wave height (HS) as the limiting factor by which to decide whether or not it is safe to access the offshore turbines. In practice, HS has to be applied conservatively, thus raising the costs through increased downtime. A method is proposed here with the objective of reducing overall costs through improved analysis of the motion of the crew transfer vessels (CTVs) used to transport repair technicians onto offshore wind turbine structures. CTV motion depends on the hydrodynamic forces incident on the vessel under operating conditions and the effect that the presence of the turbine has on the flow field. A change in the hydrodynamic field caused by the turbine monopile can cause a vessel abutted against the turbine support column to lose frictional contact and slip. Using the open-source computational fluid dynamics software, OpenFOAM, and in situ experimental results, the diffracted surface elevation and a wave kinematics model for the near-wake of a turbine monopile are presented. More accurate estimates of significant wave height and wave kinematics incident on a vessel close to a turbine monopile will facilitate much improved analysis of vessel motions under operational conditions

Market orientation for sustainable performance and the inverted-U moderation of firm size: Evidence from the Greek shipping industry

Sustainability, despite being a major concern for companies, has not been studied from a market-orientation perspective. Market-oriented companies can integrate sustainability activities into their business strategies but there is a gap in our knowledge to what extend this affects firm performance This paper analyses the sustainable performance differences and provides confirmation of the market orientation to performance relationship within the transportation (shipping) sector. In an attempt to fill the literature gap we examined, by employing Stochastic DEA and hierarchical regression analysis, the moderating effects of firm size on the relationship as well as the efficiency levels of the organizations to support the sustainable use of resources. We conducted a large-scale survey of the Greek shipping industry, which directly or indirectly controls 15.42% of the total world fleet. We surveyed the total population of 2,150 shipping firms of all types (ship owning, ship management, charterers etc.) and received 703 responses from managers of 397 shipping firms, which corresponds to an 18.5% response rate. The findings show the effects of market orientation upon firm performance for shipping companies by disaggregating MO to its constituting factors, those of responsiveness, intelligence generation and dissemination. Further, we uncover the differences in the size of shipping companies on the MO-Performance (P) link. Findings indicate that there is an inverted U-shape effect of size on firm MO performance and identify where improvements are required

Maintenance Optimization and Inspection Planning of Wind Energy Assets: Models, Methods and Strategies

Designing cost-effective inspection and maintenance programmes for wind energy farms is a complex task involving a high degree of uncertainty due to diversity of assets and their corresponding damage mechanisms and failure modes, weather-dependent transport conditions, unpredictable spare parts demand, insufficient space or poor accessibility for maintenance and repair, limited availability of resources in terms of equipment and skilled manpower, etc. In recent years, maintenance optimization has attracted the attention of many researchers and practitioners from various sectors of the wind energy industry, including manufacturers, component suppliers, maintenance contractors and others. In this paper, we propose a conceptual classification framework for the available literature on maintenance policy optimization and inspection planning of wind energy systems and structures (turbines, foundations, power cables and electrical substations). The developed framework addresses a wide range of theoretical and practical issues, including the models, methods, and the strategies employed to optimise maintenance decisions and inspection procedures in wind farms. The literature published to date on the subject of this article is critically reviewed and several research gaps are identified. Moreover, the available studies are systematically classified using different criteria and some research directions of potential interest to operational researchers are highlighted

Optimization in offshore supply vessel planning

This paper considers the offshore supply vessel (OSV) planning problem, which consists of determining an optimal fleet size and mix of OSVs as well as their weekly routes and schedules for servicing offshore oil and gas installations. The work originates from a project with Statoil, the leading operator on the Norwegian continental shelf. We present both a new arc-flow and a voyage-based model for solving the OSV planning problem. A decision support tool based on the voyage-based model has been used by planners in Statoil, and cost savings from this was estimated to approximately 3 million USD/year. Weather conditions at the Norwegian continental shelf can be harsh; wave heights may limit both an OSV’s sailing speed and the time to perform unloading/loading operations at the installations. Hence, we analyze the weather impact on the execution of a schedule and propose robustness approaches to obtain solutions that can better withstand delays due to rough weather. Simulations indicate that such solutions both are more robust and have lower expected costs.acceptedVersio

Vessel routing and scheduling under uncertainty in the liquefied natural gas business

Liquefied natural gas (LNG) is natural gas transformed into liquid state for the purpose of transportation mainly by specially built LNG vessels. This paper considers a real-life LNG ship routing and scheduling problem where a producer is responsible for transportation from production site to customers all over the world. The aim is to create routes and schedules for the vessel fleet that are more robust with respect to uncertainty such as in sailing times due to changing weather conditions. A solution method and several robustness strategies are proposed and tested on instances with time horizons of 3–12 months. The resulting solutions are evaluated using a simulation model with a recourse optimization procedure. The results show that there is a significant improvement potential by adding the proposed robustness approaches.submittedVersio

A genetic search-based heuristic for a fleet size and periodic routing problem with application to offshore supply planning

This paper introduces a genetic search-based heuristic to solve an offshore supply vessel planning problem (SVPP) faced by the Norwegian oil and gas company Statoil. The aim is to help the company in determining the optimal size of supply vessels to charter in and their corresponding voyages and schedules. We take inspiration from the hybrid genetic search with adaptive diversity control (HGSADC) algorithm of Vidal et al. (Oper Res 60(3):611–624, 2012), which successfully addresses a large class of vehicle routing problems, including the multi-period VRP (PVRP), and adapt it to account for some special features that are recurrent in maritime transportation but scarcely found in classical PVRPs, in particular, the possibility of having voyages spanning over multiple time periods in the planning horizon. Our computational experiments show that the proposed heuristic is scalable and stable, being able to solve industrial SVPPs of realistic size while significantly outperforming the existing approaches.acceptedVersio