Maintenance Alternatives Related to Costs of Wind Turbines Using Finite State Markov Model

The cumulative costs for O&M may represent as
much as 65%-90% of the turbine's investment cost. Nowadays the
cost effectiveness concept becomes a decision-making and
technology evaluation metric. The cost of energy metric accounts for
the effect replacement cost and unscheduled maintenance cost
parameters. One key of the proposed approach is the idea of
maintaining the WTs which can be captured via use of a finite state
Markov chain. Such a model can be embedded within a probabilistic
operation and maintenance simulation reflecting the action to be
done. In this paper, an approach of estimating the cost of O&M is
presented. The finite state Markov model is used for decision
problems with number of determined periods (life cycle) to predict
the cost according to various options of maintenance.




References:
[1] Forecasting of Maintenance and Repair Costs of Wind Energy Plants:
www.powergenu.com.
[2] B. Kerres, K. Fischer, R. Madlener: Economic Evaluation of
Maintenance Strategies for Wind turbines: A Stochastic Analysis IET
Renewable Energy. 2014/
[3] C. A. Walford: Wind Turbine Reliability: Understanding and
Minimizing Wind Turbine Operation and Maintenance Cost
SAND2006-1100.
[4] I. EL-Thalji, I. Alsyouf, G. Ronsten: ‘‘A Model for Assessing Operation
and Maintenance Cost adapted to wind farms in Cold Climate
Environment Based on Onshore and Offshore Case Studies’’ European
Offshore Wind Conference Proceeding 14-16 sep. 2009 Stockholm
Sweden.
[5] E. Byon, L. Ntaimo, Y. Ding: ‘‘Optimal Maintenance Strategies for
Wind Turbine Systems under Stochastic Weather Conditions’’, IEEE
Transactions on Reliability.
[6] G. M. J. Herbert, S. Iniyan, R. Goic: ‘‘Performance, Reliability and
Failure Analysis of Wind Farm in a Developing Country, Renewable
Energy’’ 35 (2010) 2739-2751.
[7] Thomas M. Welte, Jørn Vatn, Jørn Heggset, ‘‘Markov State Model for
Optimization of Maintenance and Renewal of Hydro Power
Components’’ 9th International Conference on Probalistic Methods
Applied to Power Systems KTH, Stockholm, Sweden – 11-15 June,
2006.
[8] R. Minovski, Jovanoski D, ‘‘Application of Finite Stage Markov
Decision Process in Policy of Determination for Employees
Motivation’’, 8 International Conference Advanced Manufacturing
operations.