Application of Cubic Spline Interpolation Technique in Power Systems: A Review

Prasad, Akhil; Manmohan, Atul; Shanmugam, Prabhakar Karthikeyan; Kothari, D. P.

doi:10.5772/intechopen.74853

Cited by 4 publications

(1 citation statement)

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“…Regarding the choice of

δ

, cubic basis functions (i.e.,

δ = 3

) are most popular in the literature 50 . Given the property of continuous first and second derivatives, they provide smooth interpolation when compared to linear and quadratic basis functions 51 . They also avoid some of the issues associated with higher order polynomials, for example, Runge's problem.…”

Section: Methodsmentioning

confidence: 99%

A Bayesian reliability analysis exploring the effect of scheduled maintenance on wind turbine time to failure

Anderson,

Dawid,

McMillan

et al. 2023

Wind Energy

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This article presents a Bayesian reliability modelling approach for wind turbines that incorporates the effect of time‐dependent variables. Namely, the technique is used to explore the effect of annual services on wind turbine failure intensity through time for turbines within a currently operational wind farm. In the operator's experience, turbines seemed to fail more frequently after scheduled maintenance was performed; however, this is an unexplored effect in the literature. Additionally, the effects of seasonality, year of operation and position in the array on failure intensity are explored. These features were included in a Cox‐like model formulation which allows for time‐dependent covariates. Inference was performed via Bayes rule. Results show a spike in failure intensity reaching 1.57 times the baseline in the six days directly proceeding annual servicing, after which failure intensity is reduced compared to baseline. Also observed is a significant year‐on‐year reduction of failure intensity since the introduction of the site's data management system in 2018, a clear preference for modelling time to failure via a Weibull distribution and a dependence on location in the array with respect to the prominent wind direction. Results also show the benefit of employing a Bayesian regime, which provides easily interpretable uncertainty quantification.

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“…Regarding the choice of