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Storage Optimization (r, Q) Strategy under Condition-Based Maintenance of Key Equipment of Coal-Fired Power Units in Carbon Neutrality Era

Author

Listed:
  • Tao Sun

    (SPIC Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
    These authors contributed equally to this work.)

  • Qiang Zhang

    (Shanghai Power Equipment Research Institute Co., Ltd., Shanghai 200240, China
    These authors contributed equally to this work.)

  • Jing Ye

    (Shanghai Power Equipment Research Institute Co., Ltd., Shanghai 200240, China)

  • Rong Guo

    (Shanghai Power Equipment Research Institute Co., Ltd., Shanghai 200240, China)

  • Rongze Chen

    (Shanghai Power Equipment Research Institute Co., Ltd., Shanghai 200240, China)

  • Jianguo Chen

    (SPIC Jiangxi Electric Power Co., Ltd., Nanchang 330096, China)

  • Rui Xiong

    (SPIC Jiangxi Electric Power Co., Ltd., Nanchang 330096, China)

  • Jitao Zhu

    (SPIC Jiangxi Electric Power Co., Ltd., Nanchang 330096, China)

  • Yue Cao

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China)

Abstract

For the safe, stable, and economic operation of thermal power units in new power systems, the condition-based maintenance mode and storage strategy of key equipment and materials for power generation enterprises were selected. According to the storage linkage demand of condition-based maintenance, a Weibull probability density function was used to calculate spare parts demand, and an intelligent storage optimization model with an availability constraint was established. The application cases of spare parts cost and availability of high-value key equipment and low-value key equipment of coal-fired thermal power units were analyzed, respectively, and the influence of different life spans and the number of covered units on the model were expounded. The results show that the cost of spare parts borne by a single unit is greatly reduced via the optimization of an intelligent inventory (r, Q) strategy on the premise that the availability of units is not less than 99.5%.

Suggested Citation

  • Tao Sun & Qiang Zhang & Jing Ye & Rong Guo & Rongze Chen & Jianguo Chen & Rui Xiong & Jitao Zhu & Yue Cao, 2023. "Storage Optimization (r, Q) Strategy under Condition-Based Maintenance of Key Equipment of Coal-Fired Power Units in Carbon Neutrality Era," Energies, MDPI, vol. 16(14), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5485-:d:1197841
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