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

机译:一种使用新型GA / AC OPF算法的混合AC-DC微电网的规划模型

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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:本文侧重于开发合适的组合优化技术,用于解决混合AC-DC微电网的最佳施胶问题。提出了一种新型的两级迭代方法。在第一阶段,基于量制的遗传算法的元启发式技术用于解决最佳尺寸问题,而在第二中,部署了非线性求解器以解决所获得的设计受到的操作问题/投资决定。所提出的方法,能够通过详细的电流算法捕获电压和频率等技术特性,提供准确的解决方案,因此可以解决微普林的操作挑战。其另外捕获突发事件的能力确保所提出的施胶解决方案在正常运行和瞬态状态期间适合。最后,遗传算法提供了具有相对计算简单的模型的收敛性。所提出的模型应用于可推广的微电网,包括AC和DC发生器以及负载以及各种类型的存储技术,以证明这些益处。负载和自然资源数据对应于实际数据。

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