考虑环境中冲击影响的风电机组双动态阈值维修决策

王金贺; 秦亚鹏; 陈嘉玉; 张晓红

doi:10.19912/j.0254-0096.tynxb.2024-0144

PDF(1516 KB)

太阳能学报 ›› 2025, Vol. 46 ›› Issue (5) : 602-611. DOI: 10.19912/j.0254-0096.tynxb.2024-0144

考虑环境中冲击影响的风电机组双动态阈值维修决策

王金贺^1,2, 秦亚鹏^1,2, 陈嘉玉^1,2, 张晓红^1,2

作者信息 +

RESEARCH ON MAINTENANCE DECISION OF WIND TURBINE WITH DUAL DYNAMIC THRESHOLD CONSIDERING SHOCK FROM ENVIRONMENT

Wang Jinhe^1,2, Qin Yapeng^1,2, Chen Jiayu^1,2, Zhang Xiaohong^1,2

Author information +

文章历史 +

摘要

为深入分析环境、随机冲击对风电机组退化过程的影响,提高系统性能,并降低运维成本,在环境和随机冲击影响下基于系统自身抗扰动能力和抗冲击能力提出风电机组的双动态阈值随机冲击维修策略。该策略根据风电机组当前退化状态设定系统自身抗扰动能力和抗冲击能力双阈值曲线,并依据冲击载荷大小界定随机冲击对系统退化过程的影响,进一步通过极端冲击到达时刻点和软失效阈值确定风电机组维修决策点,建立双动态阈值随机冲击维修决策模型。算例分析结果验证了模型的可行性和有效性,灵敏性分析和策略对比结果进一步表明该策略在降低风电系统维修成本方面具有显著经济优势,且随机冲击与系统性能之间的确存在相互影响关系。

Abstract

In order to thoroughly analyze the impact of environment and random shock on the degradation process of wind turbines, improve system performance and reduce operation and maintenance costs, a dual dynamic threshold random shock maintenance strategy for wind turbine was proposed based on the system’s own anti-disturbance capability and anti-shock capability under the influence of operation and maintenance environmental and random shock factors. According to the current degradation state of the wind turbine, the dual threshold curves of the system's own anti-disturbance capability and anti-shock capability are set, and the impact of random shock on the system degradation process is determined according to the impact load size. The maintenance decision point of the wind turbine is further determined by the arrival time point of the extreme shock and the soft failure threshold, and the dual dynamic threshold random shock maintenance decision model is established. The results of example analysis validate the feasibility and effectiveness of the model, and the results of sensitivity analysis and strategy comparison further show that the strategy has significant economic advantages in reducing wind trubine maintenance costs, and there is indeed an interaction between random impact and system performance.

导出引用

王金贺, 秦亚鹏, 陈嘉玉, 张晓红. 考虑环境中冲击影响的风电机组双动态阈值维修决策[J]. 太阳能学报. 2025, 46(5): 602-611 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0144

Wang Jinhe, Qin Yapeng, Chen Jiayu, Zhang Xiaohong. RESEARCH ON MAINTENANCE DECISION OF WIND TURBINE WITH DUAL DYNAMIC THRESHOLD CONSIDERING SHOCK FROM ENVIRONMENT[J]. Acta Energiae Solaris Sinica. 2025, 46(5): 602-611 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0144

中图分类号： TB114.3

参考文献

[1] 王金贺, 曾建潮. 排队论在风电场最优成组维修决策中的应用[J]. 太阳能学报, 2020, 41(8): 314-322.
WANG J H, ZENG J C.Application of queuing theory for optimal group maintenance strategy in wind farm[J]. Acta energiae solaris sinica, 2020, 41(8): 314-322.
[2] 张晓红, 张剑飞, 何于港, 等. 基于多状态空间划分的风电机组非完美维修决策[J]. 太阳能学报, 2022, 43(11): 203-214.
ZHANG X H, ZHANG J F, HE Y G, et al.Imperfect maintenance decision of wind turbine based on multi-state space partitioning[J]. Acta energiae solaris sinica, 2022, 43(11): 203-214.
[3] ABDERRAHMANE F, BOUSLIKHANE S, HAJEJ Z, et al.An improved integrated maintenance/spare parts management for wind turbine systems with adopting switching concept[J]. Energy reports, 2022, 8: 936-955.
[4] LI H, HUANG C G, GUEDES SOARES C.A real-time inspection and opportunistic maintenance strategies for floating offshore wind turbines[J]. Ocean engineering, 2022, 256: 111433.
[5] YAN R D, DUNNETT S, JACKSON L.Impact of condition monitoring on the maintenance and economic viability of offshore wind turbines[J]. Reliability engineering & system safety, 2023, 238: 109475.
[6] KONG K, DYER K, PAYNE C, et al.Progress and trends in damage detection methods, maintenance, and data-driven monitoring of wind turbine blades: a review[J]. Renewable energy focus, 2023, 44: 390-412.
[7] ZHAO C Y, LIU H B, QU X Q, et al.Reliability analysis of floating offshore wind turbine generator based on failure prediction and preventive maintenance[J]. Ocean engineering, 2023, 288: 116089.
[8] NGUYEN T A T, CHOU S Y, YU T H. Developing an exhaustive optimal maintenance schedule for offshore wind turbines based on risk-assessment, technical factors and cost-effective evaluation[J]. Energy, 2022, 249: 123613.
[9] SONG K, CUI L R.A common random effect induced bivariate gamma degradation process with application to remaining useful life prediction[J]. Reliability engineering & system safety, 2022, 219: 108200.
[10] WU D Z, JIA M P, CAO Y D, et al.Remaining useful life estimation based on a nonlinear Wiener process model with CSN random effects[J]. Measurement, 2022, 205: 112232.
[11] ZHOU S R, TANG Y C, XU A C.A generalized Wiener process with dependent degradation rate and volatility and time-varying mean-to-variance ratio[J]. Reliability engineering & system safety, 2021, 216: 107895.
[12] JIANG P H, WANG B X, WANG X F, et al.Inverse Gaussian process based reliability analysis for constant-stress accelerated degradation data[J]. Applied mathematical modelling, 2022, 105: 137-148.
[13] GUIDA M, PULCINI G.A continuous-state Markov model for age-and state-dependent degradation processes[J]. Structural safety, 2011, 33(6): 354-366.
[14] SRIVASTAV H, LUNDTEIGEN M A, BARROS A.Introduction of degradation modeling in qualification of the novel subsea technology[J]. Reliability engineering & system safety, 2021, 216: 107956.
[15] GENG Y X, WANG S P, SHI J, et al.Reliability modeling of phased degradation under external shocks[J]. Reliability engineering & system safety, 2023, 239: 109524.
[16] GAO J X, YUAN Y P.Probabilistic model of fatigue damage accumulation of materials based on the principle of failure probability equivalence[J]. Structures, 2020, 28: 659-667.
[17] GOYAL D, HAZRA N K, FINKELSTEIN M.Shock models based on renewal processes with matrix Mittag-Leffler distributed inter-arrival times[J]. Journal of computational and applied mathematics, 2024, 435: 115090.
[18] ERYILMAZ S, UNLU K D.A new generalized δ-shock model and its application to 1-out-of-(m + 1): G cold standby system[J]. Reliability engineering & system safety, 2023, 234: 109203.
[19] 曾建潮, 武鑫宇, 张晓红, 等. 加速冲击损伤退化系统剩余寿命预测及预测维修决策[J]. 控制与决策, 2022, 37(10): 2647-2656.
ZENG J C, WU X Y, ZHANG X H, et al.Remaining useful life prediction and predictive maintenance decision of accelerated shock damage deteriorating system[J]. Control and decision, 2022, 37(10): 2647-2656.
[20] ZHANG N, DENG Y J, LIU B, et al.Condition-based maintenance for a multi-component system in a dynamic operating environment[J]. Reliability engineering & system safety, 2023, 231: 108988.
[21] WU B, DING D.A gamma process based model for systems subject to multiple dependent competing failure processes under Markovian environments[J]. Reliability engineering & system safety, 2022, 217: 108112.
[22] WANG J, BAI G H, LI Z G, et al.A general discrete degradation model with fatal shocks and age- and state-dependent nonfatal shocks[J]. Reliability engineering & system safety, 2020, 193: 106648.
[23] LI X Y, HUANG H Z, LI Y F, et al.A Markov regenerative process model for phased mission systems under internal degradation and external shocks[J]. Reliability engineering & system safety, 2021, 215: 107796.
[24] CHA J H, FINKELSTEIN M, LEVITIN G.On preventive maintenance of systems with lifetimes dependent on a random shock process[J]. Reliability engineering & system safety, 2017, 168: 90-97.
[25] WU B, WEI X H, ZHANG Y M, et al.Modeling dynamic environment effects on dependent failure processes with varying failure thresholds[J]. Reliability engineering & system safety, 2023, 229: 108848.
[26] LIANG Q Z, YANG Y H, PENG C H.A reliability model for systems subject to mutually dependent degradation processes and random shocks under dynamic environments[J]. Reliability engineering & system safety, 2023, 234: 109165.
[27] AN Z W, SUN D M.Reliability modeling for systems subject to multiple dependent competing failure processes with shock loads above a certain level[J]. Reliability engineering & system safety, 2017, 157: 129-138.
[28] SHAFIEE M, FINKELSTEIN M, BÉRENGUER C. An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks[J]. Reliability engineering & system safety, 2015, 142: 463-471.
[29] 王金贺, 麻敬, 甘婕, 等. 考虑运维环境影响的风电系统维修决策建模[J]. 中国电机工程学报, 2024, 44(21): 8507-8518.
WANG J H, MA J, GAN J, et al.Maintenance decision modeling for wind power system considering operation and maintenance environmental impacts[J]. Proceedings of the CSEE, 2024, 44(21): 8507-8518.
[30] ROSS S M.Introduction to probability models[M]. 12th ed. Amsterdam: Elsevier, 2019.
[31] 王嘉, 张云安, 韩旭. 基于互依关系的退化与随机冲击建模研究[J]. 机械工程学报, 2021, 57(2): 230-238.
WANG J, ZHANG Y A, HAN X.Research on the degradation process and random shocks modeling based on their interdependency[J]. Journal of mechanical engineering, 2021, 57(2): 230-238.
[32] 宋鹏, 杨伟新, 刘宏杨, 等. 基于风电场机组大部件运行状态的年度检修策略[J]. 可再生能源, 2019, 37(4): 599-604.
SONG P, YANG W X, LIU H Y, et al.A condition based annual maintenance strategy for big parts of wind turbines in wind farms[J]. Renewable energy resources, 2019, 37(4): 599-604.
[33] 罗涵容. 考虑环境因素的海上风电机组维修决策研究[D]. 南京: 东南大学, 2021.
LUO H R.Research on maintenance decision of offshore wind turbine considering environmental factors[D]. Nanjing: Southeast University, 2021.
[34] 成卉, 刘勤明, 叶春明, 等. 考虑外部冲击的风电机组机会维护策略研究[J]. 工业工程, 2023, 26(3): 159-167.
CHENG H, LIU Q M, YE C M, et al.An opportunistic maintenance strategy for wind turbines under external environment shocks[J]. Industrial engineering journal, 2023, 26(3): 159-167.
[35] 张延静, 马义中, 欧阳林寒, 等. 基于竞争失效的单部件系统可靠性建模与维修[J]. 系统工程与电子技术, 2017, 39(11): 2623-2630.
ZHANG Y J, MA Y Z, OUYANG L H, et al.Reliability modeling and maintenance strategy for a single-unit system based on competing failure processes[J]. Systems engineering and electronics, 2017, 39(11): 2623-2630.