Reliability assessment of a wind power delivery system

This paper presents a preventive maintenance policy for wind turbines considering three effects of wind speed: accelerating hazard rate, restricting maintenance implementation, and affecting downtime cost. The effect on the hazard rate is described by a proportional hazards model. The restriction on maintenance actions results in the elongation of maintenance duration. The downtime cost is evaluated based on the power output curve model. Three failure types (i.e., catastrophic failure, critical failure, and minor failure) and multiple maintenance actions (i.e., preventive and corrective replacements, preventive and corrective general repairs, and minimal repair) are integrated into the policy. The objective is to determine the optimal maintenance policy that minimizes the long-run average cost rate. The optimization problem is formulated and solved in the semi-Markov decision process (SMDP) framework. A practical example is provided to illustrate the proposed method. The comparison with other policies shows the superiority of the proposed policy as well as the significance of the three effects of wind speed in maintenance decision-making.

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“…According to Karki and Patel 49 and Wu et al, 50 the mathematical relationship between wind speed state and power is

P (\overset{j}{true}) = ({, \begin{matrix} left \\ 0, \bar{j} = 0 \\ P_{R} (A + B \bar{j} + C {\overset{j}{true}}^{2}), w_{I} \leq \bar{j} < w_{R} \\ P_{R}, w_{R} \leq \bar{j} < w_{O} \end{matrix}),

where P R is the rated power and A , B , and C are given by

\begin{matrix} lefttrue \\ A = [w_{I} (w_{I} + w_{R}) - 4 w_{I} w_{R} {((), \frac{w_{I} + w_{R}}{2 w_{R}})}^{3}] / {((), w_{I} - w_{R})}^{2}, \\ B = [4 (w_{I} + w_{R}) {((), \frac{w_{I} + w_{R}}{2 w_{R}})}^{3} - 3 w_{I} - w_{R}] / {((), w_{I} - w_{R})}^{2}, \\ C = [2 - 4 {((), \frac{w_{I} + w_{R}}{2 w_{R}})}^{3}] / {((), w_{I} - w_{R})}^{2} . \end{matrix}

…”

Section: Model Formulationmentioning

confidence: 99%

Optimal preventive maintenance for wind turbines considering the effects of wind speed

2020

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“…The relationship between wind power and wind speed depends on factors including generator efficiencies, wind rotor, inverter, gearbox and other wind turbine characteristics [49]. As shown in Figure A2, the simplified piecewise relationship can be expressed using Equation (A17).…”

Section: Distribution Of Wind Powermentioning

confidence: 99%

Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity

Guo

Ban

2018

Sustainability

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Conventional environmental-economic power dispatch methods constrain the total amount of emissions of power plants, and they succeed in reducing emissions from the power sector. However, they fail to address the mismatch between emission reductions and the resulting changes in regional air quality. This paper proposes an ecology-and security-constrained unit commitment (Eco-SCUC) model considering the differentiated impacts of generation-associated emissions on regional air quality. A Gaussian puff dispersion model is applied to capture the temporal-spatial transport of air pollutants. Additionally, an air pollutant intensity (API) index is defined for assessing the impacts of emissions on the air quality in regions with differentiated atmospheric environmental capacities. Then the API constraints are formulated based on air quality forecast and included in SCUC model. Moreover, the stochastic optimization is employed to accommodate wind power uncertainty, and the Benders decomposition technique is used to solve the formulated mixed-integer quadratic programming (MIQP) problem. Case studies demonstrate that the Eco-SCUC can cost-effectively improve air quality for densely-populated regions via shifting generation among units and can significantly reduce the person-hours exposed to severe air pollution. Furthermore, the benefits of wind power for air quality control are investigated.

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“…The novelty of the dynamic maintenance policy remains on systematically considering the operational context of the assets, dynamically recalculating the reliability thresholds' value in order to release the maintenance activities during the most suitable operational contexts. In the particular case of the wind energy case study, there are several reasons for trying to avoid the performance of PM during high wind speed periods: (a) WTs must be stopped during PM; (b) the profits of the WF are directly related to the wind speed; 41 and (c) maintenance activities should be released during low wind speed periods for workers' safety. 42 Accordingly, the dynamic maintenance policy proposed is focused on fostering the PM activities during low wind speed periods and hindering them during high wind speed periods.…”

Section: System Reliability Threshold Srt Ikjtmentioning

confidence: 99%

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

Erguido

Crespo

Castellano

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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After-sales maintenance services can be a very profitable source of incomes for original equipment manufacturers (OEM) due to the increasing interest of assets' users on performance-based contracts. However, when it concerns the product value-adding process, OEM have traditionally been more focused on improving their production processes, rather than on complementing their products by offering after-sales services; consequently leading to difficulties in offering them efficiently. Furthermore, both due to the high uncertainty of the assets' behaviour and the inherent challenges of managing the maintenance process (e.g. maintenance strategy to be followed or resources to be deployed), it is complex to make business out of the provision of after-sales services. With the aim of helping the business and maintenance decision makers at this point, this paper proposes a framework for optimising the incomes of after-sales maintenance services through: 1) implementing advanced multi-objective opportunistic maintenance strategies that sistematically consider the assets' operational context in order to perform preventive maintenance during most favourable conditions, 2) considering the specific OEMs' and users' needs, and 3) assessing both internal and external uncertainties that might condition the after-sales services' success. The developed case study for the wind energy sector demonstrates the suitability of the presented framework for optimising the after-sales services.

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Reliability assessment of a wind power delivery system

Cited by 9 publications

References 14 publications

Optimal preventive maintenance for wind turbines considering the effects of wind speed

Optimal preventive maintenance for wind turbines considering the effects of wind speed

Security-Constrained Unit Commitment Considering Differentiated Regional Air Pollutant Intensity

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

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