Robust Optimization Model of AC/DC Hybrid Distribution Network Considering Renewable Energy Uncertainty

Yue Ma, Xiaoming Dong, Xue Yang, Z. Liu, XueYong Jia, Hongwen Sun
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Abstract

The rapid growth of renewable energy integration and power load exacerbates the uncertainty of power flow, thereby threatening the security of distribution network, and causing difficult regulation. The increase in DC application makes rapid development of AC/DC power distribution network, which operates with preferable flexibility. Accordingly, this study proposes a robust optimization model based on the relaxation evolution algorithm. Firstly, the formulations of AC/DC distribution network model, which is in terms of second-order cone programming, are derived. Accordingly, a robust reactive power optimization model is established with the objective function for minimizing the power loss and voltage offset of AC/DC distribution network. Furthermore, a co-evolution algorithm based on the relaxation method is proposed to solve this model. Case studies based on the improved IEEE33 bus system were conducted in simulation. The robust optimization model is demonstrated to effectively locating and treating the worst case of renewable energy operation.
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考虑可再生能源不确定性的交直流混合配电网鲁棒优化模型
可再生能源并网和电力负荷的快速增长加剧了潮流的不确定性,从而威胁到配电网的安全,并造成调控困难。随着直流应用的增加,交直流配电网发展迅速,具有良好的运行灵活性。因此,本研究提出了一种基于松弛进化算法的鲁棒优化模型。首先,推导了交/直流配电网的二阶锥规划模型。在此基础上,以交直流配电网的功率损耗和电压偏置最小为目标函数,建立了鲁棒无功优化模型。在此基础上,提出了一种基于松弛法的协同进化算法来求解该模型。基于改进的IEEE33总线系统进行了实例仿真。结果表明,该鲁棒优化模型能够有效地定位和处理可再生能源运行的最坏情况。
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