Availability Analysis of Wind Turbines and Its Sub Assemblies with Markov Analysis at Uncertain Wind

摘要

Energy is one of the major inputs for the economic development of any country. All important activities concerned with present development are depending on energy in one form or other. The power generation from wind energy is technically achievable and economically feasible and its main advantages are zero fuel cost, pollution free and environment friendly. In order to increase the life of a wind turbine, it is important to estimate the reliability level for all components in the wind turbine (WT). Unfortunately, these WTs have to contend with large failures due to the presence of complex and repairable parts. The issue of reliability becomes more critical since the complexity in mechanisms like pitch control, yaw control, hydraulic system electrical and electronics control, braking system, grid availability, sensors and other mechanical components. This paper deals with the availability analysis for the WTs located in hill and main pass having uncertainty in wind. In this paper, the concept of Markov analysis (MA) is used to model the failure characteristics of the major components for calculating probability, maintainability, reliability and availability of reaching various system states of WTs of 250 kW. Due to uncertainty in the wind in the main pass and hill area, the probability, availability and reliability of component failure is independent of the past history. Hence, Markov Analysis is considered as best mathematical tool for modeling wind turbine with complex system. In this paper, the wind turbine availability is estimated for 20 WTs by using ITEM Tool kit version 8.0.2 software, considering different states with respect to the probability of failure, failure rate and the repair rate. The availability for the WTs varies from 94.45% to 99% for three year (26304 hours) intervals during the years 1995-2010. This analysis yields some surprising results about some subassemblies, such as the rotor system and gear system are the most unreliable due to very high uncertainty in the wind.