Abstract
A novel framework for resilience modeling of wind turbine parks is proposed in support of optimization of decisions on asset integrity management. The concept of resilience originating from natural and social sciences is adapted here to facilitate the joint optimization of decision alternatives related to design, with decision alternatives addressing organizational performance. The generic probabilistic systems representation framework by the Joint Committee on Structural Safety (JCSS) (2008) is utilized to establish a scenario-based modeling of how different types of disturbances may lead to damages and failures of systems and sub-systems of wind turbine parks, together with associated direct and indirect consequences. Special emphasis is directed on the consistent probabilistic representation of the uncertainties and the stochastic and causal dependencies within the wind turbine park system. The framework facilitates the identification of optimal asset integrity management decision alternatives that fulfill given requirements to resilience. The potentials associated with the use of the framework are highlighted by an example considering a wind turbine park with ten identical wind turbines, with each modelled as a system of mechanical, electrical, and structural sub-systems. The resilience performance characteristics of the wind turbine park, such as the expected value of generated service life benefits, the expected value of production down time, and the probability of resilience failure are modelled and quantified such as to support the ranking of decision alternatives relating to the design of the wind turbine sub-systems, the level of organizational preparedness, the percentage of the generated service life benefits to be kept to ensure sufficient economic capacity to deal with future disturbances, and the stock-keeping of essential spare parts.
Highlights
The success of wind energy as a renewable substitute for traditional fossil-based fuels is key for reduction of CO2 equivalent emissions and sustainable development in general
The suggested representation of wind turbine parks as the systems of decision alternatives for asset integrity management problems, is in general not trivial by means of sub-systems, considering the two levels of dependencies described in the foregoing, is illustrated in highly1.efficient probabilistic analysis tools
In the of an an example wind turbine park is is modelled as the basis for supporting decisions on service life asset integrity management
Summary
In the following, following, the the resilience resilience of example wind turbine park modelled and and investigated investigated as. The structural sub-systems across the wind turbine park are assumed to be exposed to natural hazards (extreme wind) with intensities LH. The corresponding capacities of the structural sub-systems, rH , are modelled by Log-normal distributed random variables, all with expected values and coefficients of variation equal to 1 and 0.3, respectively. The occurrences of natural hazards events are assumed to follow a Poisson process with an annual rate λH = 3 The intensities of these events acting on each wind turbine within the park are modelled by a random vector of intensities IH , which are assumed to be Gumbel distributed. 1.00 kg/m equal to 1.00 kg/m , while the power performance coefficient Cp , which p depends on the wind speed, is modelled in accordance with the onsite test presented in a previous reportreport [45].
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