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A Planning Model for a Hybrid AC–DC Microgrid Using a Novel GA/AC OPF Algorithm

机译:使用新型GA / AC OPF算法的AC-DC混合微电网规划模型

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摘要

This paper focuses on developing an appropriate combinatorial optimization technique for solving the optimal sizing problem of hybrid ac-dc microgrids. A novel two-stage iterative approach is proposed. In the first stage, a meta-heuristic technique based on a tailor-made genetic algorithm is used to tackle the optimal sizing problem, while, in the second, a non-linear solver is deployed to solve the operational problem subject to the obtained design/investment decisions. The proposed approach, being able to capture technical characteristics such as voltage and frequency through a detailed power flow algorithm, provides accurate solutions and, therefore, can address operational challenges of microgrids. Its capability to additionally capture contingencies ensures that the proposed sizing solutions are suitable both during normal operation and transient states. Finally, the genetic algorithm provides convergence of the model with relative computational simplicity. The proposed model is applied to a generalizable microgrid comprising of ac and dc generators and loads, as well as various types of storage technologies in order to demonstrate the benefits. The load and natural resources data correspond to real data.
机译:本文着重于开发一种适当的组合优化技术,以解决交流-直流混合微电网的最佳尺寸问题。提出了一种新颖的两阶段迭代方法。在第一阶段,基于量身定制的遗传算法的元启发式技术用于解决最佳规模问题,而在第二阶段,则采用非线性求解器来解决所获得设计的操作问题。 /投资决策。所提出的方法能够通过详细的潮流算法捕获技术特征,例如电压和频率,提供了准确的解决方案,因此可以解决微电网的运营挑战。其额外捕获突发事件的能力确保了所提出的尺寸解决方案在正常操作和瞬态期间均适用。最后,遗传算法以相对的计算简单性提供了模型的收敛性。拟议的模型应用于包含交流和直流发电机和负载以及各种类型的存储技术的可推广微电网,以证明其优势。负荷和自然资源数据对应于真实数据。

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