基于可用度约束的风力机单部件顺序维修优化
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摘要
为提高风电场运行维护效率,以风力机为对象开展风力机单部件顺序维修优化研究.通过引入有效年龄的概念,考虑改善因子随维修次数的增加而降低的情况,分析最小维修、不完全维修和更换对风力机有效年龄的影响.考虑维护期内突发性维修成本、不完全维修成本、更换成本、停机损失和固定成本,将部件单生命周期划分为若干个维护期,以维护期个数和维护期时间间隔为决策变量,部件更换周期内单位时间维护成本最低为目标,建立可用度约束下的风力机单部件顺序维修优化模型.采用内点法和枚举法求解模型,完成算例分析,并验证模型的有效性.结果表明,与传统的周期维修和顺序维修相比,该模型求解得到的最佳维修计划可以保证风力机各部件的可用度均在98%以上,且维护期时间间隔更加符合工程实际.
To improve the efficiency of operation and maintenance of w ind farms,the single part maintenance optimization problem of w ind turbines w as studied. The effective age w as introduced to describe the reduction of improvement factors w ith the number of the maintenance,and the influences of minimal repair,imperfect repair and replacement on the effective age of the component w ere analyzed. The replacement cycle w as divided into several maintenance periods. Considering the maintenance cost,dow ntime losses,fixed cost and availability,and taking the number of maintenance periods and the length of each maintenance period as variables,a sequential maintenance optimization model for single part w as proposed w ith the goal to minimize the maintenance cost per unit time in a replacement period. The interior point method and the enumeration method w ere used to solve the model. A case study w as given to prove the validity of the model. The results show that compared w ith the traditional periodical maintenance and sequential maintenance,the optimal maintenance plan obtained by the model can ensure that the availability of w ind turbine components is above 98%,and the maintenance period is more in line w ith engineering practice.
To improve the efficiency of operation and maintenance of w ind farms,the single part maintenance optimization problem of w ind turbines w as studied. The effective age w as introduced to describe the reduction of improvement factors w ith the number of the maintenance,and the influences of minimal repair,imperfect repair and replacement on the effective age of the component w ere analyzed. The replacement cycle w as divided into several maintenance periods. Considering the maintenance cost,dow ntime losses,fixed cost and availability,and taking the number of maintenance periods and the length of each maintenance period as variables,a sequential maintenance optimization model for single part w as proposed w ith the goal to minimize the maintenance cost per unit time in a replacement period. The interior point method and the enumeration method w ere used to solve the model. A case study w as given to prove the validity of the model. The results show that compared w ith the traditional periodical maintenance and sequential maintenance,the optimal maintenance plan obtained by the model can ensure that the availability of w ind turbine components is above 98%,and the maintenance period is more in line w ith engineering practice.
引文
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[16]苏春,陈武.基于滚动窗口方法的风力机动态机会维修优化[J].机械工程学报,2014,50(14):62-68.DOI:10.3901/JME.2014.14.062.Su C,Chen W.Dynamic opportunistic maintenance optimization for wind turbine system based on rolling horizon approach[J].Journal of Mechanical Engineering,2014,50(14):62-68.DOI:10.3901/JME.2014.14.062.(in Chinese)
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[18]苏春,周小荃.基于有效年龄的风力机多部件维修优化[J].东南大学学报(自然科学版),2012,42(6):1100-1104.DOI:10.3969/j.issn.1001-0505.2012.06.015.Su C,Zhou X Q.Maintenance optimization for multicomponent of wind turbine based on effective age[J].Journal of Southeast University(Natural Science Edition),2012,42(6):1100-1104.DOI:10.3969/j.issn.1001-0505.2012.06.015.(in Chinese)
[19]Li L,Hanson T E.A Bayesian semiparametric regression model for reliability data using effective age[J].Computational Statistics&Data Analysis,2014,73:177-188.DOI:10.1016/j.csda.2013.11.015.
[20]赵永强,梁工谦.可靠性及动态维修成本下的定期预防维修研究[J].航空制造技术,2012(7):89-91,95.DOI:10.3969/j.issn.1671-833X.2012.07.016.Zhao Y Q,Liang G Q.Periodic preventive maintenance based on reliability and dynamic maintenance cost[J].Aeronautical Manufacturing Technology,2012(7):89-91,95.DOI:10.3969/j.issn.1671-833X.2012.07.016.(in Chinese)
[21]陈宝林.最优化理论与算法[M].2版.北京:清华大学出版社,2005:401-405.
[2]Su C,Hu Z Y.Reliability assessment for Chinese domestic wind turbines based on data mining techniques[J].Wind Energy,2018,21(3):198-209.DOI:10.1002/we.2155.
[3]夏云峰.2017年中国风电行业关键数据汇总[J].风能,2018(3):34-36.Xia Y F.Key data collection of China wind power industry in 2017[J].Wind Energy,2018(3):34-36.(in Chinese)
[4]Qian P,Ma X D,Cross P.Integrated data-driven modelbased approach to condition monitoring of the wind turbine gearbox[J].IET Renewable Power Generation,2017,11(9):1177-1185.DOI:10.1049/iet-rpg.2016.0216.
[5]Chan D,Mo J.Life cycle reliability and maintenance analyses of wind turbines[J].Energy Procedia,2017,110:328-333.DOI:10.1016/j.egypro.2017.03.148.
[6]Slimacek V,Lindqvist B H.Reliability of wind turbines modeled by a Poisson process with covariates,unobserved heterogeneity and seasonality[J].Wind Energy,2016,19(11):1991-2002.DOI:10.1002/we.1964.
[7]Lin Y G,Tu L,Liu H W,et al.Fault analysis of wind turbines in China[J].Renewable and Sustainable Energy Reviews,2016,55:482-490.DOI:10.1016/j.rser.2015.10.149.
[8]Zhang C,Gao W,Guo S,et al.Opportunistic maintenance for wind turbines considering imperfect,reliabilitybased maintenance[J].Renewable Energy,2017,103:606-612.DOI:10.1016/j.renene.2016.10.072.
[9]Li Y F,Valla S,Zio E.Reliability assessment of generic geared wind turbines by GTST-MLD model and Monte Carlo simulation[J].Renewable Energy,2015,83:222-233.DOI:10.1016/j.renene.2015.04.035.
[10]Su C,Jin Q,Fu Y Q.Correlation analysis for wind speed and failure rate of wind turbines using time series approach[J].Journal of Renewable and Sustainable Energy,2012,4(3):032301.DOI:10.1063/1.4730597.
[11]Su C,Fu Y.Assessment for wind turbines considering the influence of wind speed using Bayesian network[J].Eksploatacja i Niezawodnosc-Maintenance and Reliability,2014,16(1):1-8.
[12]Guo H T,Watson S,Tavner P,et al.Reliability analysis for wind turbines with incomplete failure data collected from after the date of initial installation[J].Reliability Engineering&System Safety,2009,94(6):1057-1063.DOI:10.1016/j.ress.2008.12.004.
[13]Santos F P,Teixeira A P,Guedes Soares C.Maintenance planning of an offshore wind turbine using stochastic petri nets with predicates[J].Journal of Offshore Mechanics and Arctic Engineering,2018,140(2):021904.DOI:10.1115/1.4038934.
[14]Sarker B R,Faiz T I.Minimizing maintenance cost for offshore wind turbines following multi-level opportunistic preventive strategy[J].Renewable Energy,2016,85:104-113.DOI:10.1016/j.renene.2015.06.030.
[15]Sinha Y,Steel J A.A progressive study into offshore wind farm maintenance optimisation using risk based failure analysis[J].Renewable and Sustainable Energy Reviews,2015,42:735-742.DOI:10.1016/j.rser.2014.10.087.
[16]苏春,陈武.基于滚动窗口方法的风力机动态机会维修优化[J].机械工程学报,2014,50(14):62-68.DOI:10.3901/JME.2014.14.062.Su C,Chen W.Dynamic opportunistic maintenance optimization for wind turbine system based on rolling horizon approach[J].Journal of Mechanical Engineering,2014,50(14):62-68.DOI:10.3901/JME.2014.14.062.(in Chinese)
[17]Ding F F,Tian Z G.Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds[J].Renewable Energy,2012,45:175-182.DOI:10.1016/j.renene.2012.02.030.
[18]苏春,周小荃.基于有效年龄的风力机多部件维修优化[J].东南大学学报(自然科学版),2012,42(6):1100-1104.DOI:10.3969/j.issn.1001-0505.2012.06.015.Su C,Zhou X Q.Maintenance optimization for multicomponent of wind turbine based on effective age[J].Journal of Southeast University(Natural Science Edition),2012,42(6):1100-1104.DOI:10.3969/j.issn.1001-0505.2012.06.015.(in Chinese)
[19]Li L,Hanson T E.A Bayesian semiparametric regression model for reliability data using effective age[J].Computational Statistics&Data Analysis,2014,73:177-188.DOI:10.1016/j.csda.2013.11.015.
[20]赵永强,梁工谦.可靠性及动态维修成本下的定期预防维修研究[J].航空制造技术,2012(7):89-91,95.DOI:10.3969/j.issn.1671-833X.2012.07.016.Zhao Y Q,Liang G Q.Periodic preventive maintenance based on reliability and dynamic maintenance cost[J].Aeronautical Manufacturing Technology,2012(7):89-91,95.DOI:10.3969/j.issn.1671-833X.2012.07.016.(in Chinese)
[21]陈宝林.最优化理论与算法[M].2版.北京:清华大学出版社,2005:401-405.