基于非洲秃鹫优化算法的分布式发电优化规划

Mintong Zhao, Jia-jia Huan, Xin Huang, Tao Yu, Qiaoyi Ding
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引用次数: 1

摘要

随着环境污染的不断影响,以化石燃料为代表的传统发电机正逐渐被可再生能源发电机所取代。不同于传统的优化规划只包括光伏(PV)和风力发电机组。本文将燃料电池(FC)和微型汽轮机与光伏系统和风力发电机组结合使用,可以弥补其输出功率波动的缺陷。此外,建立了考虑功率损耗、电压分布和投资成本的多目标模型,并采用非洲秃鹫优化算法(AVOA)进行求解。最后,基于IEEE 33和69节点分配网络(DN)系统进行了仿真。结果表明,AVOA具有较快的收敛速度和较强的优化特性,能够改善分布式发电接入后的电压分布。仿真结果表明,与DG连接后,IEEE 33节点的功率损耗和电压分布分别降低了57%和58%,IEEE 69节点的功率损耗和电压分布分别降低了64%和61%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Planning of Distributed Generation Based on African Vultures Optimization Algorithm
With the continuous impact of environmental pollution, the traditional generator represented by fossil fuels is gradually being replaced by renewable energy generators. Different from the conventional optimal planning, which only includes photovoltaic (PV) and wind turbines. This paper adds the use of fuel cells (FC) and miniature steam turbines with PV systems and wind turbines, which can make up for the defect of fluctuation of its output power. In addition, a multi-objective model considering power loss, voltage profile, and investment cost is established and solved by the African vultures optimization algorithm (AVOA). Finally, the simulation is based on IEEE 33 and 69 node distribution network (DN) systems. The results show that AVOA has a fast convergence speed and strong optimization characteristics, and can improve voltage distribution after distributed generation (DG) access. The simulation results show that the power loss and voltage profile decreased by 57% and 58% at the IEEE 33 and 64% and 61% at the IEEE 69 node after being connected to DG.
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