Reliability optimization of wind farms considering redundancy and opportunistic maintenance strategy

Abstract In this paper, a joint redundancy and imperfect block opportunistic maintenance optimization model is formulated. The objective is to determine the wind farm redundancy level and the maintenance strategy which will simultaneously minimize the wind farm loss of load probability and life cycle cost. A new opportunistic maintenance approach is developed to take advantages of the maintenance opportunities. Different reliability thresholds are introduced for imperfect maintenance of failed turbines and working turbines and preventive dispatching of maintenance teams. In addition, a simulation method is developed to evaluate the performance measures of a wind farm system considering different types of wind turbine, maintenance activation delays and durations, and limited number of maintenance teams. Sensitivity analysis is conducted to discuss the influence of the different assumption and parameters of simulation model over the wind farm performance. Pareto optimal solutions are driven based on a multi-objective particle swarm optimization algorithm. Comparative study with the commonly used maintenance policy demonstrates the advantages of the proposed opportunistic maintenance strategy in significantly reducing maintenance cost and loss of load probability.

[1]  Shahaboddin Shamshirband,et al.  Adaptive neuro-fuzzy optimization of wind farm project net profit , 2014 .

[2]  Matthias Hofmann,et al.  A Review of Decision Support Models for Offshore Wind Farms with an Emphasis on Operation and Maintenance Strategies , 2011 .

[3]  Stephen C. Mathewson,et al.  Simulation program generators , 1974 .

[4]  Gregory Levitin,et al.  Joint redundancy and maintenance optimization for multistate series–parallel systems , 1999 .

[5]  Russell C. Eberhart,et al.  Multiobjective optimization using dynamic neighborhood particle swarm optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[6]  Yao Zhang,et al.  Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel , 2015 .

[7]  Zhigang Tian,et al.  OPPORTUNISTIC MAINTENANCE OPTIMIZATION FOR WIND TURBINE SYSTEMS CONSIDERING IMPERFECT MAINTENANCE ACTIONS , 2011 .

[8]  Salman Kahrobaee,et al.  A hybrid analytical-simulation approach for maintenance optimization of deteriorating equipment: Case study of wind turbines , 2013 .

[9]  Tongdan Jin,et al.  Maintenance modeling and optimization for wind turbine systems: A review , 2013, 2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE).

[10]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[11]  Laurent Doyen,et al.  Classes of imperfect repair models based on reduction of failure intensity or virtual age , 2004, Reliab. Eng. Syst. Saf..

[12]  Qing Song,et al.  Wind farm layout optimization using genetic algorithm with different hub height wind turbines , 2013 .

[13]  Mohammad Modarres,et al.  Generalized renewal process for analysis of repairable systems with limited failure experience , 2002, Reliab. Eng. Syst. Saf..

[14]  Hui Liu,et al.  Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms , 2015 .

[15]  Eunshin Byon,et al.  Wind turbine operations and maintenance: a tractable approximation of dynamic decision making , 2013 .

[16]  Zhigang Tian,et al.  Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds , 2012 .

[17]  Iver Bakken Sperstad,et al.  NOWIcob – A Tool for Reducing the Maintenance Costs of Offshore Wind Farms , 2013 .

[18]  M. Payán,et al.  Overall design optimization of wind farms , 2011 .

[19]  Ehab F. El-Saadany,et al.  Overview of wind power intermittency impacts on power systems , 2010 .

[20]  Michael Patriksson,et al.  Preventive maintenance scheduling of multi-component systems with interval costs , 2014, Comput. Ind. Eng..

[21]  Jonathan E. Fieldsend,et al.  A Multi-Objective Algorithm based upon Particle Swarm Optimisation, an Efficient Data Structure and , 2002 .

[22]  Yuehua Huang,et al.  Short-term wind power prediction based on LSSVM–GSA model , 2015 .

[23]  Erich Hau,et al.  Wind Turbines: Fundamentals, Technologies, Application, Economics , 1999 .

[24]  Jürgen Teich,et al.  Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO) , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[25]  C. Balakrishna Moorthy,et al.  A new approach to optimise placement of wind turbines using particle swarm optimisation , 2015 .

[26]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[27]  Thomas Bäck,et al.  Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .

[28]  C.A. Coello Coello,et al.  MOPSO: a proposal for multiple objective particle swarm optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[29]  Idriss El-Thalji,et al.  On the operation and maintenance practices of wind power asset , 2012 .

[30]  Morteza Abbasi,et al.  Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups , 2016 .

[31]  K. D. Tocher,et al.  The Art of Simulation , 1967 .

[32]  Mustapha Nourelfath,et al.  Joint redundancy and imperfect preventive maintenance optimization for series-parallel multi-state degraded systems , 2012, Reliab. Eng. Syst. Saf..

[33]  M. Burgos Payán,et al.  Optimum design of transmissions systems for offshore wind farms including decision making under risk , 2013 .

[34]  Chao-Hui Huang,et al.  Optimization of preventive maintenance for a multi-state degraded system by monitoring component performance , 2016, J. Intell. Manuf..

[35]  Mohammad Rezaei Mirghaed,et al.  Site specific optimization of wind turbines energy cost: Iterative approach , 2013 .

[36]  Hong-Zhong Huang,et al.  A Joint Redundancy and Imperfect Maintenance Strategy Optimization for Multi-State Systems , 2013, IEEE Transactions on Reliability.

[37]  M. Hand,et al.  Wind Turbine Design Cost and Scaling Model , 2006 .

[38]  Cristina H. Amon,et al.  A new mathematical programming approach to optimize wind farm layouts , 2014 .

[39]  Xuan Zhang,et al.  Wind turbine positioning optimization of wind farm using greedy algorithm , 2013 .

[40]  Min Xie,et al.  A value-based preventive maintenance policy for multi-component system with continuously degrading components , 2014, Reliab. Eng. Syst. Saf..

[41]  Jie Zhang,et al.  Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions , 2013 .

[42]  Ana Sánchez,et al.  Onshore wind farms maintenance optimization using a stochastic model , 2013, Math. Comput. Model..

[43]  Matija Fajdiga,et al.  Generalized renewal process for repairable systems based on finite Weibull mixture , 2008, Reliab. Eng. Syst. Saf..

[44]  Michael Muskulus,et al.  Maintenance Strategies for Large Offshore Wind Farms , 2012 .

[45]  Rajesh Karki,et al.  Reliability assessment of a wind power delivery system , 2009 .

[46]  J. Christopher Beck,et al.  Solving wind farm layout optimization with mixed integer programs and constraint programs , 2014, EURO J. Comput. Optim..

[47]  Michael Pidd,et al.  Computer Simulation in Management Science (3rd Edition) , 1998 .

[48]  Tongdan Jin,et al.  Condition based maintenance optimization for wind power generation systems under continuous monitoring , 2011 .