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Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures

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  • Liu, Jingfan
  • Zhang, Shijie

Abstract

Compared to centralized generation technology, distributed energy resource systems are susceptible to energy risks caused by boundary uncertainties and unit failures. This study introduces a stochastic two-stage multi-objective optimization method to address reliability-based unit commitment issues. In the day-ahead stage, operational state and reserve capacity are determined to minimize prescheduled operation costs based on forecasted parameters. In the real-time stage, a decision-dependent stochastic reliability method is proposed to simulate outage scenarios. Reserve resources within available units are allocated to mitigate forecasting errors and unit failures. Additionally, the grid interaction ratio and penalty cost are added to restrict the depth and frequency access to the grid. Four comparative cases analyze the effects of the proposed methodology. This method innovatively achieves the simulation of stochastic multi-unit outages and delete faulty units in the operation scheme. The optimal results show that the risks of electricity and cooling supply are underestimated, while the risks of heating are overestimated, compared to N-1 reliability. Furthermore, Pareto analysis of the multi-objective problem enhances independent operational capacity through utilization of reserve resources. Grid dispatch pressure is reduced since purchased power can be used as day-ahead planning. Thus, the methodology achieves collaborative optimization of reliability with a reduction of operation costs, offering effective guidance for engineering applications.

Suggested Citation

  • Liu, Jingfan & Zhang, Shijie, 2025. "Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:reensy:v:253:y:2025:i:c:s0951832024005921
    DOI: 10.1016/j.ress.2024.110520
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    1. Zhao, Xian & Han, He & Jiao, Chunhui & Qiu, Qingan, 2024. "Reliability modeling of k-out-of-n: F balanced systems with common bus performance sharing," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. Zhang, Dingmao & Li, Gengfeng & Bie, Zhaohong & Fan, Kangjian, 2024. "An analytical method for reliability evaluation of power distribution system with time-varying failure rates," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    3. Gazijahani, Farhad Samadi & Salehi, Javad, 2018. "Reliability constrained two-stage optimization of multiple renewable-based microgrids incorporating critical energy peak pricing demand response program using robust optimization approach," Energy, Elsevier, vol. 161(C), pages 999-1015.
    4. Das, Sayan & Dutta, Risav & De, Souvanik & De, Sudipta, 2024. "Review of multi-criteria decision-making for sustainable decentralized hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
    5. Tan, Jin & Wu, Qiuwei & Zhang, Menglin & Wei, Wei & Liu, Feng & Pan, Bo, 2021. "Chance-constrained energy and multi-type reserves scheduling exploiting flexibility from combined power and heat units and heat pumps," Energy, Elsevier, vol. 233(C).
    6. Jain, Tanmay & Verma, Kusum, 2024. "Reliability based computational model for stochastic unit commitment of a bulk power system integrated with volatile wind power," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    7. Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2011. "Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market," Applied Energy, Elsevier, vol. 88(7), pages 2548-2558, July.
    8. Fan, Wei & Tan, Zhongfu & Li, Fanqi & Zhang, Amin & Ju, Liwei & Wang, Yuwei & De, Gejirifu, 2023. "A two-stage optimal scheduling model of integrated energy system based on CVaR theory implementing integrated demand response," Energy, Elsevier, vol. 263(PC).
    9. Qi, Faqun & Huang, Meiqi, 2024. "Joint optimization of maintenance and spares inventory policy for a series-parallel system considering dependent failure processes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    10. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    11. Rakipour, Davood & Barati, Hassan, 2019. "Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response," Energy, Elsevier, vol. 173(C), pages 384-399.
    12. Wim Ackooij, 2017. "A comparison of four approaches from stochastic programming for large-scale unit-commitment," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 119-147, March.
    13. Wang, Yongli & Wang, Huan & Meng, Xiao & Dong, Huanran & Chen, Xin & Xiang, Hao & Xing, Juntai, 2023. "Considering the dual endogenous-exogenous uncertainty integrated energy multiple load short-term forecast," Energy, Elsevier, vol. 285(C).
    14. Silva-Rodriguez, Lina & Sanjab, Anibal & Fumagalli, Elena & Gibescu, Madeleine, 2024. "Light robust co-optimization of energy and reserves in the day-ahead electricity market," Applied Energy, Elsevier, vol. 353(PA).
    15. Qipeng Zheng & Jianhui Wang & Panos Pardalos & Yongpei Guan, 2013. "A decomposition approach to the two-stage stochastic unit commitment problem," Annals of Operations Research, Springer, vol. 210(1), pages 387-410, November.
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