A Closed-Form Technique for the Reliability and Risk Assessment of Wind Turbine Systems

Abstract

This paper proposes a closed-form method to evaluate wind turbine system reliability and associated failure consequences. Monte Carlo simulation, a widely used approach for system reliability assessment, usually requires large numbers of computational experiments, while existing analytical methods are limited to simple system event configurations with a focus on average values of reliability metrics. By analyzing a wind turbine system and its components in a combinatorial yet computationally efficient form, the proposed approach provides an entire probability distribution of system failure that contains all possible configurations of component failure and survival events. The approach is also capable of handling unique component attributes such as downtime and repair cost needed for risk estimations, and enables sensitivity analysis for quantifying the criticality of individual components to wind turbine system reliability. Applications of the technique are illustrated by assessing the reliability of a 12-subassembly turbine system. In addition, component downtimes and repair costs of components are embedded in the formulation to compute expected annual wind turbine unavailability and repair cost probabilities, and component importance metrics useful for maintenance planning and research prioritization. Furthermore, this paper introduces a recursive solution to closed-form method and applies this to a 45-component turbine system. The proposed approach proves to be computationally efficient and yields vital reliability information that could be readily used by wind farm stakeholders for decision making and risk management.

A probabilistic framework for offshore wind turbine loss assessment

“…In general, for a system with a number ( ) of independent components, each of which has two discrete states (failure or operation), there is a finite number of permutations in the system state, where the total number of combinations of component events (leading to system events) is 2 . These combinations of operating and failure states can be summarized in a matrix [31], with elements ∈ ℤ ⋅2 , using one to indicate that the component fails or zero to indicate that it remains operational. For a generic OWT with 11 components (e.g.…”

Effect of Short-Circuit Faults in the Back-to-Back Power Electronic Converter and Rotor Terminals on the Operational Behavior of the Doubly-Fed Induction Generator Wind Energy Conversion System

“…A typical kind of fault, that has severe consequences for the DFIG-WECS (due to the directly connection between the stator and the grid) and has been investigated a lot, is the grid faults, i.e., voltage sags and swells (symmetrical and asymmetrical), short-circuit faults (phase-to-phase, phase-to-ground, three phase), etc., [3][4][5][6]. As referred in a lot of papers [1,[7][8][9][10], faults could also happen in the generator [11], in sensors [12,13] and in DFIG electrical part-the back-to-back power electronic converter and the control system. Two types of faults can occur in power switches, open-circuit and short-circuit fault.…”

Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory

“…The DEGA was stopped after producing 350 individual generations. The results obtained from DEGA were compared with the results obtained from the algorithm in [14], as listed in Table 8. Furthermore, this Table represents the comparisons in the reliability indices between algorithms represented in absolute values from a single run of the DEGA, and of the MSGA, to obtain the exact results.…”

“…It was reported that these algorithms perform better than when only the analysis methods or the MCS are used. However, such an algorithm requires a longer computation period when the population size is too large [14]. The modified simple genetic algorithm (MSGA) approach has also been proposed [15,16].…”