高比例新能源电网多源最优协同调频策略

随着大规模可再生能源对电网渗透率的不断增加,大型风光电站也开始参与到电网的调频当中。首先,建立了功率响应总偏差、调频里程支出最小化的多目标互补控制模型,以解决不同调频资源的动态功率分配问题。为解决该非线性优化问题,采用多目标蝠鲼觅食优化算法(multi-objective manta ray foraging optimization, MMRFO)快速地获取高质量的Pareto前沿,以满足电网的实时在线调频需求,提高区域电网的动态响应能力。然后,基于熵权法,设计了灰靶决策法客观地选择不同功率扰动下兼顾运行经济性和电能质量的折中解。最后,基于扩展的两区域负荷频率控制(load frequency control,LFC)模型验证了所提方法的有效性。

Multi-source Optimal Coordinated Frequency Regulation for Power Grid with High Penetration of Renewable Energy

With the increasing penetration of large-scale renewable energy into the power grid, large-scale wind and solar power stations also begin to participate in the frequency regulation of the power grid. In order to solve the dynamic power allocation problem of different frequency-regulation resources, a multi-objective complementary control model with minimum total power deviation and regulation mileage payment is established. To solve the nonlinear optimization problem, the multi-objective manta ray foraging optimization algorithm (MMRFO) is adopted in this paper to quickly obtain high quality Pareto front to meet the real-time online frequency-regulation requirements of the power grid and improve the dynamic response capability of the regional power grid. Then, applying the entropy weight method, the grey target decision-making theory is designed to objectively select the compromise solution which takes into account both operation economy and power quality under different power perturbations. Finally, the validity of the proposed method is verified by an extended two-area load frequency control model.