高渗透率风电-氢能混合系统的VMD-MOPSO动态容量配置

Dynamic Capacity Configuration of High-Penetration Wind-Hydrogen Hybrid System Based on VMD-MOPSO

中文关键词:风氢混合储能  动态容量配置  多目标优化

keywords:wind-hydrogen hybrid energy storage  dynamic capacity configuration  multi-objective optimization

中文摘要:为解决新能源并网的波动性问题，提高其利用率，提出一种基于变分模态分解算法-多目标粒子群优化算法的高渗透率风电-氢能混合系统的动态容量配置方法。首先，结合设备特性构建系统的数学模型，制定能源管理策略。其次，建立以总成本现值和电网需求服务性为目标的容量配置模型。然后，采用变分模态分解算法对风电信号滤波，确定储能系统目标功率。最后，利用多目标粒子群算法求解，研究权重系数、设备投资成本及额定运行功率对容量配置的影响。结果表明，优化后系统的经济性和电网服务能力得到提高；权重系数改变时，配置结果的变化主要体现在发电单元上；系统经济性对燃料电池的投资成本最敏感，投资增长40%时，总成本现值提高2.76%，而对于电解槽和超级电容，增长相同幅度，现值仅变化不到1%；燃料电池的额定运行功率与系统经济性负相关，与电网服务能力正相关，且变化幅度超过20%时，功率对优化结果的影响逐渐减小。

Abstract:To solve the fluctuation problem of grid-connected new energy and improve its utilization rate，this paper proposes a dynamic capacity configuration method for high-penetration wind-hydrogen hybrid systems based on VMD-MOPSO. First，the mathematical model of the system is constructed according to equipment characteristics，and the energy management strategy is formulated. Second，a capacity configuration model is established with the present value of total cost and power grid service performance as dual objectives. Third，the variational mode decomposition algorithm is used to filter wind power signals and determine the target power of the energy storage system. Finally，the multi-objective particle swarm optimization algorithm is adopted for model solution. The influences of weight coefficient，equipment investment cost and rated operating power on capacity configuration are studied. The results show that the optimized system achieves improved economic efficiency and grid service capability. When the weight coefficient changes，the difference of configuration results is mainly reflected in power generation units. System economy is most sensitive to the investment cost of fuel cells. A 40% increase in fuel cell investment cost raises the present value of total cost by 2.76%，while the present value changes less than 1% for electrolyzes and supercapacitors with the same growth range. The rated operating power of fuel cells is negatively correlated with system economy and positively correlated with grid service capability. When the variation range exceeds 20%，its influence on optimization results gradually decreases.