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    刘中华, 牛玉刚, 贾廷纲. 基于风-光-储联合优化的最优潮流[J]. 华东理工大学学报(自然科学版), 2022, 48(2): 221-230. DOI: 10.14135/j.cnki.1006-3080.20201214001
    引用本文: 刘中华, 牛玉刚, 贾廷纲. 基于风-光-储联合优化的最优潮流[J]. 华东理工大学学报(自然科学版), 2022, 48(2): 221-230. DOI: 10.14135/j.cnki.1006-3080.20201214001
    LIU Zhonghua, NIU Yugang, JIA Tinggang. Optimal Power Flow Based on Optimization of Wind-Photovoltaic-Storage Hybrid System[J]. Journal of East China University of Science and Technology, 2022, 48(2): 221-230. DOI: 10.14135/j.cnki.1006-3080.20201214001
    Citation: LIU Zhonghua, NIU Yugang, JIA Tinggang. Optimal Power Flow Based on Optimization of Wind-Photovoltaic-Storage Hybrid System[J]. Journal of East China University of Science and Technology, 2022, 48(2): 221-230. DOI: 10.14135/j.cnki.1006-3080.20201214001

    基于风-光-储联合优化的最优潮流

    Optimal Power Flow Based on Optimization of Wind-Photovoltaic-Storage Hybrid System

    • 摘要: 针对分布式能源发电的间歇性和不确定性,提出了风、光互补发电和储能实时在线优化结合的方法。以风、光日前预测发电与实时发电误差最小、储能出力最少为目标,建立风-光-储联合优化模型;使用改进PSO算法对风、光出力进行实时优化,优化后的分布式发电可以有效降低分布式电源带来的日前调度偏差。储能优化后的风、光出力在进行潮流计算时可直接处理为负荷模型,因此可以有效降低分布式能源建模的复杂度。最后,以IEEE30节点系统为例,以发电机发电费用最低为目标函数,将风-光-储联合出力等效为单个节点,利用遗传算法对最优潮流模型进行求解,验证了本文方法的正确性和有效性。

       

      Abstract: With the vigorous development and application of distributed energy, the planning and operation of traditional power grids are facing more and more challenges. The intermittent influence of distributed energy needs to be solved urgently, e.g., the wind power and photovoltaic power generation on energy dispatch and the impact of uncertainty on the power grid. In view of the intermittency and uncertainty of distributed power generation, this paper established the wind-solar energy-storage joint optimization model to achieve the minimization of wind-solar forecast power generation error and energy storage output. Besides, this paper proposes a real-time online optimization method of wind-solar complementary power generation and energy storage. The improved PSO (particle swarm optimization) algorithm is used to optimize the model in real time. Based on the established wind-solar-storage complementary model, the co-generation of wind-solar storage is regarded as an equivalent node to construct an optimal power flow model with the objective of optimizing the diesel generators outputs. Moreover, GA (genetic algorithm) is used to solve the optimal power flow model. Finally, the experiments via IEEE30-node system are made to verify the effectiveness of the proposed joint optimization strategy.

       

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