A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations

Fallahi, Farnaz; Bakir, Ilke; Yildirim, Murat; Ye, Z.

doi:10.1016/j.rser.2022.112789

Cited by 16 publications

(3 citation statements)

References 57 publications

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“…Specifically, we assume that the RUL of the unit i running from time t 0 i to the moment t is R t 0 i i (t). For each unit i in the twin scenario φ , we introduce the notion of failure time periods [54], denoted as τ i φ , which can be calculated by Monte Carlo sampling according to RUL.…”

Section: Rxm Implementation For Twin Systemmentioning

confidence: 99%

Prescriptive maintenance for complex products with digital twin considering production planning and resource constraints

Mao

Liu

Qiu

et al. 2023

Meas. Sci. Technol.

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Maintenance is a critical aspect of complex products through entire life cycle, often requiring coordination of production planning and available resources, while previous studies appear to have rarely addressed. With this in mind, this paper presents a prescriptive maintenance framework based on digital twins for reducing operational risk and maintenance costs of complex equipment clusters. Virtual entities are firstly constructed for each single asset in multiple dimensions, which use real-time or historical sensing data collected from the physical entities to predict the corresponding remaining useful life (RUL). Then such RUL information is incorporated into a stochastic programming model with chance constraints to enable dynamic decision making. In particular, a risk-based optimization model is formulated to take full account of the physical distances between facilities and production gaps. Further, a dual-sense pyramidal transformer model is proposed to sense important details of data in both time and space while capturing temporal dependencies at different scales. We have demonstrated through a maintenance case of turbofan engines that the proposed scheme significantly lowers total maintenance costs while reducing frequent visits from maintenance personnel.

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Section: Rxm Implementation For Twin Systemmentioning

confidence: 99%

Prescriptive maintenance for complex products with digital twin considering production planning and resource constraints

Mao

Liu

Qiu

et al. 2023

Meas. Sci. Technol.

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“…The second step, S2, is less straightforward. Here, we make use of the S-N curves, which relate the observed stress level to the number of cycles to failure, N , as expressed in (4).…”

Section: B Time Transformation Modelmentioning

confidence: 99%

Seizing Opportunity: Maintenance Optimization in Offshore Wind Farms Considering Accessibility, Production, and Crew Dispatch

Papadopoulos

Coit

Azizezzat

2022

IEEE Trans. Sustain. Energy

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Operations and Maintenance (O&M) constitute a major contributor to offshore wind's cost of energy. Due to the harsh and remote environment in which offshore turbines operate, there has been a growing interest in opportunistic maintenance scheduling for offshore wind farms, wherein grouping maintenance tasks is incentivized at times of opportunity. Our survey of the literature, however, reveals that there is no unified consensus on what constitutes an "opportunity" for offshore maintenance. We therefore propose an opportunistic maintenance scheduling approach which defines an opportunity as either dispatch-based (initiated by a maintenance crew already dispatched to a neighboring turbine), production-based (initiated by projected low production levels), or access-based (initiated by a provisionally open window of turbine access). We formulate the problem as a rolling-horizon mixed integer linear program, and propose an iterative solution algorithm to identify the optimal hourly maintenance schedule, which is found to be drastically different, yet substantially better, than those obtained using offshore-insensitive strategies. Extensive evaluations on actual wind, wave, and power data demonstrate substantial margins of improvement achieved by our proposed approach, across a wide variety of key O&M metrics.

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“…Related research has already shown positive results, for example, increased availability of wind farms [11] and even further optimization models for predictive maintenance of wind farms [12]. However, predictive maintenance is mostly investigated from an engineering perspective, focusing on the design of technical components such as sensors and architectures, e.g., [13], [14], or improved machine learning methods and algorithms, e.g., [15], [16].…”

Section: Introductionmentioning

confidence: 99%

Predictive Maintenance on the Energy Distribution Grid–Design and Evaluation of a Digital Industrial Platform in the Context of a Smart Service System

Heiden,

Priefer,

Beverungen

2024

IEEE Trans. Eng. Manage.

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The energy turnaround and the shift towards sustainable mobility threaten the stability of European energy distribution grids due to substantially increasing load fluctuations and power demand. These challenges can critically impact assets in the distribution grid--e.g., switchgears--intensifying the need to plan, conduct, and manage the maintenance of such assets. Predictive maintenance strategies that analyze assets' current and historical condition data have been discussed as promising approaches toward that end. However, the extant research focuses on designing and improving analytical algorithms or information technology (IT) artifacts while not considering how a maintenance service is co-created by companies with IT. This research article posits that IT and service must be aligned closely, presenting an ensemble artifact comprising a digital industrial platform and a smart service system for predictive maintenance on the distribution grid. The artifact is evaluated by conducting a willingness-to-pay analysis with asset operators, documenting their demand for condition monitoring and predictive maintenance as an integrated solution, although they still struggle with even getting the condition data of their assets. Building on these results, we formalize the knowledge in the form of design principles and implications for managing the maintenance of critical assets in the distribution grid.

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A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations

Cited by 16 publications

References 57 publications

Prescriptive maintenance for complex products with digital twin considering production planning and resource constraints

Prescriptive maintenance for complex products with digital twin considering production planning and resource constraints

Seizing Opportunity: Maintenance Optimization in Offshore Wind Farms Considering Accessibility, Production, and Crew Dispatch

Predictive Maintenance on the Energy Distribution Grid–Design and Evaluation of a Digital Industrial Platform in the Context of a Smart Service System

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