何知纯, 谢敏, 黄莹, 李弋升, 张世平. 基于连续隐马尔可夫模型的风水火联合低碳检修优化[J]. 南方能源建设, 2023, 10(4): 43-56. DOI: 10.16516/j.gedi.issn2095-8676.2023.04.005
引用本文: 何知纯, 谢敏, 黄莹, 李弋升, 张世平. 基于连续隐马尔可夫模型的风水火联合低碳检修优化[J]. 南方能源建设, 2023, 10(4): 43-56. DOI: 10.16516/j.gedi.issn2095-8676.2023.04.005
HE Zhichun, XIE Min, HUANG Ying, LI Yisheng, ZHANG Shiping. Wind Power, Hydropower and Thermal Power Combined Low-Carbon Maintenance Optimization Based on Continuous Hidden Markov Model[J]. Southern Energy Construction, 2023, 10(4): 43-56. DOI: 10.16516/j.gedi.issn2095-8676.2023.04.005
Citation: HE Zhichun, XIE Min, HUANG Ying, LI Yisheng, ZHANG Shiping. Wind Power, Hydropower and Thermal Power Combined Low-Carbon Maintenance Optimization Based on Continuous Hidden Markov Model[J]. Southern Energy Construction, 2023, 10(4): 43-56. DOI: 10.16516/j.gedi.issn2095-8676.2023.04.005

基于连续隐马尔可夫模型的风水火联合低碳检修优化

Wind Power, Hydropower and Thermal Power Combined Low-Carbon Maintenance Optimization Based on Continuous Hidden Markov Model

  • 摘要:
      目的  新型电力系统背景下,风机的低碳检修与常规机组的协同检修等问题亟待解决。文章兼顾多属性气象因子影响和低碳性、经济性需求,建立基于连续隐马尔可夫的风水火联合低碳检修优化模型。
      方法  首先,以降雨量、风速、雷电危险度为观测序列,以检修容量为隐状态序列,利用连续隐马尔可夫(Continuous Hidden Markov Model, CHMM)过程实现对风电场检修容量的动态跟踪。然后,以最优检修容量为决策依据、以总成本最小为优化目标,统筹考虑检修约束、系统控制约束等,构建风水火联合低碳检修优化模型。最后,以IEEE30节点系统进行算例展开研究。
      结果  结果表明,所提模型具有更显著的经济效益和低碳特性。
      结论  文章所做研究对风机的运行维护具有较高的理论价值,工程适用性较强。

     

    Abstract:
      Introduction  In the context of the new power system, low-carbon maintenance of wind turbines and coordinated maintenance with conventional wind turbine generator systems (WTGS) need to be solved urgently. In this paper, taking into account the impact of multi-attribute meteorological factors and low carbon and economic needs, an optimization model for wind power, hydropower and thermal power combined low-carbon maintenance based on continuous hidden Markov model is established.
      Method  Firstly, dynamic tracking of wind farm maintenance capacity was realized by taking rainfall, wind speed and lightning hazard degree as the observation sequence, taking maintenance capacity as hidden state sequence, and using continuous hidden Markov model (CHMM) process. Then, an optimization model for wind power, hydropower and thermal power combined low-carbon maintenance was constructed by taking the optimal maintenance capacity as the decision-making basis, taking the minimum total cost as the optimization objective, and taking the maintenance constraints and system control constraints into consideration. Finally, took the IEEE30-node system as an example.
      Result  The results show that the proposed model has more significant economic benefits and low carbon characteristics.
      Conclusion  The research in this paper has high theoretical value for the operation and maintenance of WTGS, and has strong engineering applicability.

     

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