HCHaoqian Cui

Haoqian Cui

*This is an algorithmically generated author record based on publicly available information.

Haoqian Cui has a total of 15 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Optimal Scheduling of Park-Level IES by Considering Combined Weights

    by Zihao Yang, Xiran Zhou, Ruijie Si, Xiangyu Cai, Haoqian Cui, Yannan Dong, Haixin Wang, Junyou Yang, Zhe Chen, Shiyan Hu

    To address the carbon emission issue of combined heat and power (CHP) units in park-level integrated energy system (IES), this paper proposes an optimization scheduling model of park-level IES by considering combined weights. Firstly, a park-level IES is established within a designated park area, incorporating gas storage (GS), power to gas (P2G), carbon capture and storage (CCS), CHP units, wind power and photovoltaic power stations. Based on the analysis of the operational characteristics of GS, P2G, CCS, and CHP, an optimal scheduling model of the GS–P2G–CCS–CHP integrated system is proposed to optimize CHP with low carbon. Secondly, to achieve economic viability and the accommodation of renewable energy, a combined weights approach is proposed for the objective function, considering subjective and objective weights. Finally, to verify the feasibility of the proposed method, four operational strategies are compared, and based on the operational characteristics of GS, P2G, CCS, and CHP, the optimal capacities of P2G and GS are determined.


  • Open Access

    A Modified Reynolds-Averaged Navier–Stokes-Based Wind Turbine Wake Model Considering Correction Modules

    by Yuan Li, Zengjin Xu, Zuoxia Xing, Bowen Zhou, Haoqian Cui, Bowen Liu, Bo Hu

    Increasing wind power generation has been introduced into power systems to meet the renewable energy targets in power generation. The output efficiency and output power stability are of great importance for wind turbines to be integrated into power systems. The wake effect influences the power generation efficiency and stability of wind turbines. However, few studies consider comprehensive corrections in an aerodynamic model and a turbulence model, which challenges the calculation accuracy of the velocity field and turbulence field in the wind turbine wake model, thus affecting wind power integration into power systems. To tackle this challenge, this paper proposes a modified Reynolds-averaged Navier–Stokes (MRANS)-based wind turbine wake model to simulate the wake effects. Our main aim is to add correction modules in a 3D aerodynamic model and a shear-stress transport (SST) k-ω turbulence model, which are converted into a volume source term and a Reynolds stress term for the MRANS-based wake model, respectively. A correction module including blade tip loss, hub loss, and attack angle deviation is considered in the 3D aerodynamic model, which is established by blade element momentum aerodynamic theory and an improved Cauchy fuzzy distribution. Meanwhile, another correction module, including a hold source term, regulating parameters and reducing the dissipation term, is added into the SST k-ω turbulence model. Furthermore, a structured hexahedron mesh with variable size is developed to significantly improve computational efficiency and make results smoother. Simulation results of the velocity field and turbulent field with the proposed approach are consistent with the data of real wind turbines, which verifies the effectiveness of the proposed approach. The variation law of the expansion effect and the double-hump effect are also given.