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![Figure 2. Graphical representation of some maintenance strategies [3].](profile/Giovanni-Rinaldi-4/publication/308169554/figure/fig2/AS:406943828070402@1474034377903/Graphical-representation-of-some-maintenance-strategies-3_Q320.jpg)
Operation and Maintenance (O&M) of offshore farms have been highlighted as one of the major contributors to the final cost of energy. Therefore, lower the costs related to such aspect is vital in order to speed up their access into the market. Several decision-making tools have been developed to provide assistance in this area. Unfortunately, many...
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... even a solution that maximizes the availability of the farm may not be the most cost effective if the maintenance efforts, then the expenses related to these, are too high. Under these circumstances, an optimal solution, that increases the availability of the device while lowering the maintenance costs, as exemplified in Figure 1, should be pursued. The obtainment of this strategy is not an easy task though, since it is given by a careful combination of instructions and choices weighted on several variables, and that must be able to predict future production and related costs. ...
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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 fa...
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... The category of operation and maintenance technology is shown in Fig. 6, which can be divided into preventive maintenance, corrective maintenance and hybrid maintenance [66,67]. The main objective of the operation and maintenance process of the wind farm is to reduce the operation and maintenance cost and improve the availability of the wind farm [68]. For offshore wind farms, the harsh climate and marine environment make the equipment failure rate higher than that of onshore wind farms. ...
During the past decade, wind power generation has been rapidly developed. As a key component of feasibility analysis, the cost modelling and economic analysis directly affect the construction of wind power projects. This review attempts to explain the whole life cycle composition, economic analysis method and cost modelling process of wind power from a macro perspective, and summarizes the differences in cost composition and modelling among different types of wind farms and the applicability of different economic analysis methods and evaluation indicators. During this process, the relationship between life cycle and investment is explored, as well as the potential ways to improve the accuracy and reliability of life cycle economic assessment from the aspects of uncertainty analysis and prediction algorithm application. On this basis, some discussions are made on the prospect and potential improvements of whole life cycle cost modelling and economic analysis of wind power under the development trend of large-scale units, high-altitude and deep-sea construction. Furthermore, comparisons are made in terms of the modelling methods, evaluation indicators, uncertainty analysis methods and prediction methods, which could guide the selection of relevant methods and indicators in the process of economic analysis of wind power projects. Finally, some suggestions on achieving accurate and reliable economic evaluation of wind power in different regions and environments are given, providing reference value for improving economic efficiency of wind farms.
... The tool used in the Rinaldi model was developed in 2016 for the proactive management of offshore wind farms [26]. Since then, the tool has been adapted for other offshore technologies, including wave and tidal energy converters. ...
This paper presents the key operations & maintenance (O&M) modelling inputs for fixed-bottom wind (FBW) and highlights the adaptations required for floating offshore wind (FOW) uses. The work also highlights major repair strategies such as tow to shore (T2S) and discusses the limitations and constraints which arise in an operational context. The technical and economic feasibility of such O&M strategies requires rethinking of weather risks and constraints, new vessel technologies and operational costs. The work also collates and reviews existing FBW models which have been adapted for FOW uses and analyses O&M inputs for a tow to shore operation. Findings show that there is ambiguity in literature for tug speeds and disconnection/reconnection times of the turbine system. A performed case study investigates the sensitives of both parameters through a weather window analysis of ScotWind sites. Recommendations for future practises, including additional O&M modelling considerations and inputs for FOW uses are given.
... The gaps found in literature are addressed here, in presenting and demonstrating a methodology to obtain more accurate techno-economic assessments of FLOW farms over their project lifetime. This methodology relies on a set of computational models, previously verified with ORE projects [13][14][15][16] and now specifically adapted for FLOW, to reduce the uncertainties in the estimation of the technical and economical parameters of the project. Employing advanced O&M tools within the techno-economic model enables assessing the impact of applying different O&M strategies on the overall costs. ...
Floating offshore wind is rapidly gaining traction in deep water locations. As with all new technologies, to gain the confidence of developers and investors, the technical and economic feasibility of this technology must be proven and robust cost estimates are necessary. In this paper, the authors present a methodology to calculate the capital and operational indicators of a floating wind farm over its project lifetime. A set of computational models is used to reduce the uncertainties in the estimation of the technical and economical parameters. In particular, the effect of using detailed operation and maintenance models and strategies allows a better estimation of operational cost. The paper highlights the requirements and specific adjustments considered for floating offshore wind technology. The methodology is demonstrated for two case studies inspired by real floating wind installations in the United Kingdom, namely the Hywind and Kincardine projects. The related input data, gathered from publicly available sources, constitute a reference database for future studies in the floating offshore wind sector. Results are presented for the two case studies. These show that availability and energy production are in line with typical values for offshore wind projects, and highlight the substantial contribution of operational expenses to the cost of energy. Results are also compared against previous estimations for floating offshore wind projects, showing satisfactory agreement for the overall project costs but an underestimation of operation and maintenance costs in previous studies. This highlights the importance of using detailed operation and maintenance models to adequately capture operational expenses.
... Assuming this would be representative for other sites, the average annual production loss would be €24 k/MW. Therefore a suitable trade-off that allows us to keep the farm availability high while maintenance costs remain low is required [6]. To ...
Operation and maintenance constitute a substantial share of the lifecycle expenditures of an offshore renewable energy farm. A noteworthy number of methods and techniques have been developed to provide decision-making support in strategic planning and asset management. Condition monitoring instrumentation is commonly used, especially in offshore wind farms, due to the benefits it provides in terms of fault identification and performance evaluation and improvement. Incorporating technology advancements, a shift towards automation and digitalisation is taking place in the offshore maintenance sector. This paper reviews the existing literature and novel approaches in the operation and maintenance planning and the condition monitoring of offshore renewable energy farms, with an emphasis on the offshore wind sector, discussing their benefits and limitations. The state-of-the-art in industrial condition-based maintenance is reviewed, together with deterioration models and fault diagnosis and prognosis techniques. Future scenarios in robotics, artificial intelligence and data processing are investigated. The application challenges of these strategies and Industry 4.0 concepts in the offshore renewables sector are scrutinised, together with the potential implications of early-stage project integration. The identified technologies are ranked against a series of indicators, providing a reference for a range of industry stakeholders.
... The tool was built with the aim of supporting the development of wind farms' maintenance strategies. As for other O&M management tools [89,90], they have a modular structure consisting of the following core modules: (1) reliability, (2) power, (3) weather forecasting, (4) maintenance and (5) cost. The flowchart of the processes and steps of the tool are shown in Fig. 2. The inputs are weather data, cost data, reliability data, turbine specific data (power curve), wind farm layout data (distances from shore), and repair information, such as number and type of vessels, and the crew required for the restoring of the system. ...
This work presents a comprehensive review and discussion of the identification of critical components of the currently installed and next generation of offshore wind turbines. A systematic review on the reliability, availability, and maintainability data of both offshore and onshore wind turbines is initially performed, collecting the results from 24 initiatives, at system and subsystem level. Due to the scarcity of data from the offshore wind industry, the analysis is complemented with the extensive experience from onshore structures. Trends based on the deployment parameters for the influence of design characteristics and environmental conditions on the onshore wind turbines’ reliability and availability are first investigated. The estimation of the operational availability for a set of offshore wind farm scenarios allowed a comparison with the recently published performance statistics and the discussion of the integrity of the data available to date. The failure statistics of the systems deployed offshore are then discussed and compared to the onshore ones, with regard to their normalised results. The availability calculations supported the hypothesis of the negative impact of the offshore environmental conditions on the reliability figures. Nonetheless, similarities in the reliability figures of the blade adjustment system and the maintainability of the power generation and the control systems are outlined. Finally, to improve the performance prediction of future offshore projects, recommendations on the effort worth putting into research and data collection are provided.
... In order to achieve this task, a simulation model for the characterization of the key performance indicators of an offshore energy farm, with particular emphasis towards the O&M strategy planning, is used. This tool was developed by the authors, and has been applied for other O&M applications in the offshore wind, wave and tidal energy sectors (see Rinaldi et al. 2016;Rinaldi et al. 2019). The tool has also been verified for its intended use (Rinaldi et al. 2018). ...
... A simplified workflow diagram of the computational model used in this study is shown in Figure 1 ( Rinaldi et al. 2016). More details on the mechanisms and constraints regulating its functioning are discussed in . ...
... Simplified workflow Diagram of the O&M model(Rinaldi et al. 2016). ...
Operation and maintenance are widely recognized as major areas for cost reduction in offshore wind installation. This paper explores improvements in the O&M planning capabilities for the floating off-shore wind sector. Computational tools have been developed in the last decades to support the strategic plan-ning of onshore and offshore wind O&M interventions. However, adaptations will be needed in order to cap-ture the novel operational requirements of floating devices with respect to traditional bottom-fixed turbines. In this paper, specific adjustments to computational planning tools in order to capture floating farms capabilities are identified and implemented. The effects of these amendments on the overall maintenance strategy, as well as related key performance indicators, are tested for the same case study. The comparison between bottom-fixed and floating offshore wind projects allows to quantify the impacts of using floating platforms, and pro-vides indications for future improvements in floating wind O&M planning.
As an emerging market, the telecoms sector in Nigeria has undergone a considerable increase in teledensity, internet usage and consumer base over a decade and is still on exponential growth. However, the consequence of this increase in growth has been a continuous degradation of telecom network quality of service (QoS), which has impacted subscribers’ customers’ needs, satisfaction, expectations and added value services. In exploring the quality of services (QoS) issues, the asset performance is not meeting the agreed key performance indicators (KPIs) on power availability (PA), a critical KPI which is affected by asset maintenance activities. Therefore, this paper focuses on the technical and human factors of asset management and maintenance practices. The methodology used in this paper is the quantitative and qualitative approaches with a systematic review of related literature on the research context. The primary data sources are through a structured survey questionnaire and semi-structured interviews. The secondary data source is the systematic literature review on related journal articles to the research subject matter. The paper used the statistical package for the social sciences software (SPSS 29) and Nvivo software for the data analysis. The research results and findings indicate critical maintenance strategic differences in existing asset maintenance activities and operations, cost pressure, and complex operating environments and markets that could be explained through intelligent and digitalised asset management and maintenance strategies. The systematic review results indicate the advancement of asset maintenance strategies to support maintenance planning, asset real-time monitoring and management, as the existing maintenance practice did not match the intelligent-based approach drawn from the concept of Industry 4.0R.
As an emerging market, the telecoms sector in Nigeria has undergone a considerable increase in teledensity and consumer base over a decade and is still on exponential growth. However, the consequence of this growth has been a continuous degradation of telecom operators’ network quality of service (QoS), which has impacted subscribers’ and customers’ needs, satisfaction, and expectations. Given the existing literature and research on asset management, this paper explores the roles of infrastructure and asset management activities in network service quality in the study context. Therefore, in exploring the QoS issues, the infrastructure and asset intermittent outages have been critical factors from a performance perspective. In addition, operating cost (OPEX) and risk were also factors from the management and operational domain. The paper uses a survey strategy, focusing on a single case study of Nigeria’s telecommunication operating environment, with a mixed method of quantitative and qualitative techniques and a systematic review of related literature and documents on telecommunications and asset management. The chosen participants are field operations technicians and managers from the network operators, managed service companies and regulatory agencies. Data were collected through a designed online structured questionnaire and semi-structured face-to-face interviews and analysed through gap analysis protocol. Despite significant growth in telecommunication in the study area, the results indicated an impact of infrastructure and asset outages on critical issues: QoS network performance, cost pressure, and risk. The key identified factors affecting the network’s quality from the infrastructure and assets perspective are poor diesel management with 47.50% lack of actual diesel consumption measurement and visibility, and the outages caused by poor maintenance and monitoring practices at 15.70%. Real-time fault escalation increase mean-time-to-repair (MTTR). These infrastructures and asset problems, in turn, affect the QoS, which is a critical component of network availability. Addressing the power outages caused by poor diesel management to reduce MTTR is essential in resolving the cooling system’s 15.30% failures. These findings recognised the challenges subscribers and network operators face in an emerging operating environment and markets due to deficiencies in public grid infrastructures and systematised maintenance culture. This explains why network operators should focus on deploying intelligent and predictive approaches toward managing their infrastructure and assets. Furthermore, this recommended intelligent and predictive system integrates with human-centric intervention in addressing QoS issues.
In order to accelerate the access into the energy market for ocean renewables, the operation and maintenance (O&M) costs for these technologies must be reduced. In this paper a reliability-based simulation tool for the optimization of the management of an offshore renewable energy (ORE) farm is presented. The proposed tool takes into account the reliability data of the simulated devices and estimations on the energy produced to create a series of results in terms of availability and maintainability of the farm. The information produced supports operational and strategic decision making regarding the O&M for offshore farms. A case study simulating a conceptual tidal energy project, consisting of an array of two tidal turbines located off the north coast of Scotland, is presented to show some of the results achievable with this model. The proposed methodology, although adopted for a tidal farm here, is generally applicable to other kinds of ORE farms.
