沈煜, 杨志淳, 闵怀东, 杨帆, 雷杨, 胡伟. 考虑分布式电源电压支撑的新型配电网精准负荷双层供电恢复策略[J]. 太阳能学报, 2024, 45(7): 398-406. DOI: 10.19912/j.0254-0096.tynxb.2023-1977
引用本文: 沈煜, 杨志淳, 闵怀东, 杨帆, 雷杨, 胡伟. 考虑分布式电源电压支撑的新型配电网精准负荷双层供电恢复策略[J]. 太阳能学报, 2024, 45(7): 398-406. DOI: 10.19912/j.0254-0096.tynxb.2023-1977
Shen Yu, Yang Zhichun, Min Huaidong, Yang Fan, Lei Yang, Hu Wei. NEW DISTRIBUTION NETWORK CONSIDERING DISTRIBUTED POWER SUPPLY VOLTAGE SUPPORT PRECISION LOAD DOUBLE-LAYER POWER SUPPLY RECOVERY STRATEGY[J]. Acta Energiae Solaris Sinica, 2024, 45(7): 398-406. DOI: 10.19912/j.0254-0096.tynxb.2023-1977
Citation: Shen Yu, Yang Zhichun, Min Huaidong, Yang Fan, Lei Yang, Hu Wei. NEW DISTRIBUTION NETWORK CONSIDERING DISTRIBUTED POWER SUPPLY VOLTAGE SUPPORT PRECISION LOAD DOUBLE-LAYER POWER SUPPLY RECOVERY STRATEGY[J]. Acta Energiae Solaris Sinica, 2024, 45(7): 398-406. DOI: 10.19912/j.0254-0096.tynxb.2023-1977

考虑分布式电源电压支撑的新型配电网精准负荷双层供电恢复策略

NEW DISTRIBUTION NETWORK CONSIDERING DISTRIBUTED POWER SUPPLY VOLTAGE SUPPORT PRECISION LOAD DOUBLE-LAYER POWER SUPPLY RECOVERY STRATEGY

  • 摘要: 针对有源配电网故障后借助含分布式电源(DG)微网的恢复控制问题,提出一种考虑微网电压支撑的配电网精准负荷双层供电恢复策略。首先,为充分量化故障时段内重构后孤岛运行风险,从电压稳定和功率平衡的角度定义重构后孤岛运行风险指标,最大程度的利用故障时段内微网DG资源建立重构模型;然后,针对供电恢复重构模型求解难度高的问题,使用灰狼优化算法(GWO)与二阶锥松弛技术分别求解双层重构模型,其中,为解决GWO算法以优质解引导种群进化导致效率受限制的问题,采用粒子群算法(PSO)思想来改善GWO算法的个体位置更新过程,通过融合每个灰狼个体的历史信息以构筑更高效的种群进化方法。最后,采用修正的IEEE 33节点系统,在2种不同类型故障下均能够提供供电恢复方案,验证方法的可行性。

     

    Abstract: Aiming at the problem of recovery control of active distribution network with microgrid containing distributed generation(DG) after fault, this paper proposes a two-layer power supply recovery strategy for precise load of distribution network considering microgrid voltage support. Firstly, in order to fully quantify the risk of island operation after reconfiguration during the fault period, the risk index of island operation after reconfiguration is defined from the perspective of voltage stability and power balance, and the reconfiguration model is established by using the distributed generation resources of microgrid in the fault period to the greatest extent.Then, aiming at the problem of high difficulty in solving the power supply recovery reconstruction model, the grey wolf optimization algorithm(GWO) and the second-order cone relaxation technique are used to solve the two-layer reconstruction model respectively.Among them, in order to solve the problem that the GWO algorithm guides the population evolution with high-quality solutions, which leads to the limitation of efficiency, the PSO algorithm is used to improve the individual position update process of the GWO algorithm, and the historical information of each gray wolf individual is integrated to construct a more efficient population evolution method.Finally, using the modified IEEE 33 node system, the power supply recovery scheme can be provided under two different types of faults, which verifies the feasibility of the proposed method.

     

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