郭旭升, 娄素华, 张金平, 李湃. 电力市场环境下生物质气化耦合燃煤机组与风电场联合自调度优化策略[J]. 中国电机工程学报, 2024, 44(16): 6334-6346. DOI: 10.13334/j.0258-8013.pcsee.232358
引用本文: 郭旭升, 娄素华, 张金平, 李湃. 电力市场环境下生物质气化耦合燃煤机组与风电场联合自调度优化策略[J]. 中国电机工程学报, 2024, 44(16): 6334-6346. DOI: 10.13334/j.0258-8013.pcsee.232358
GUO Xusheng, LOU Suhua, ZHANG Jinping, LI Pai. Joint Self-scheduling Optimization Strategy of Biomass Gasification Coupled Coal-fired Thermal Power Unit and Wind Farm Under Power Market Environment[J]. Proceedings of the CSEE, 2024, 44(16): 6334-6346. DOI: 10.13334/j.0258-8013.pcsee.232358
Citation: GUO Xusheng, LOU Suhua, ZHANG Jinping, LI Pai. Joint Self-scheduling Optimization Strategy of Biomass Gasification Coupled Coal-fired Thermal Power Unit and Wind Farm Under Power Market Environment[J]. Proceedings of the CSEE, 2024, 44(16): 6334-6346. DOI: 10.13334/j.0258-8013.pcsee.232358

电力市场环境下生物质气化耦合燃煤机组与风电场联合自调度优化策略

Joint Self-scheduling Optimization Strategy of Biomass Gasification Coupled Coal-fired Thermal Power Unit and Wind Farm Under Power Market Environment

  • 摘要: 利用生物质气化耦合燃煤发电技术可以提升火电机组的燃料及运行灵活性,从而促进风电的高水平消纳,同时实现生物质能的有效开发利用。该文首先建立反映生物质气化耦合热电联产机组内部能流过程和外部出力特性的运行模型。然后,从能源供应商视角出发,给出耦合机组与风电场联合参与日前、日内和实时平衡市场的多阶段决策框架,提出反映联合体期望收益和条件风险价值的多目标自调度策略。最后,利用基于字典优化框架的增强ε约束法,给出构建帕累托前沿的多目标优化求解流程。以一台350 MW燃煤热电联产机组和一座600 MW风电场构成的联合体为例进行分析。结果可知,增设生物质气化子系统和联合运行能够使其经济效益提升6%左右,同时有利于降低能源供应商的运营风险。

     

    Abstract: Biomass gasification coupled coal-fired power generation technology can enhance the fuel and operation flexibility of thermal power units, thereby promoting the high-level accommodation of wind power as well as the effective exploitation of biomass energy. In this paper, an operation model reflecting the internal energy flow processes and the external output characteristics of the biomass gasification coupled CHP unit is firstly established. Then, from the perspective of an energy supplier, a multi-objective self-scheduling strategy reflecting the expected benefits and conditional value-at-risk (CVaR) of the coalition is proposed, considering the multi-stage decision framework for the joint participation of the coupled unit and the wind farm in the day-ahead, intra-day and real-time balancing markets. Finally, the multi-objective optimization solution procedure for constructing the Pareto front is illustrated using the augmented ε-constraint method based on lexicographic optimization. The numerical analysis is performed to demonstrate that the addition of biomass gasification subsystem and the joint operation of the 350 MW CHP unit and the 600 MW wind farm can increase their economic benefits by about 6%, as well as reduce the operation risk of the energy supplier.

     

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