不同类型DG在配电系统中的单、多配置

O. Oladepo
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引用次数: 0

摘要

分布式发电在配电系统中的集成对提高电网电压稳定性和电能质量具有重要意义。然而,能量源的大小和位置不准确会使网络性能恶化。提出了一种混合粒子群优化/鲸鱼优化算法,用于解决电网中不同配电类型的最优配置问题。独立元启发式算法是一种高效且鲁棒的优化工具,但主要面临收敛性和次优解的挑战。鲸鱼优化算法的开发阶段附加了选择较高惯性权值的粒子群优化的探索潜力。该技术在IEEE 33总线配电系统上得到了验证。结果表明,ⅰ型和ⅲ型注入DG分别改善了86.12%和89.84%的电压偏差。此外,与独立方法相比,收敛在不到50次迭代中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single and Multiple Placements of Different DG Types On the Power Distribution System
Integration of distributed generation on power distribution system impacts the network for improved voltage stability and power quality. However, inaccurate sizing and placement of the energy sources can worsen the network performance. This paper proposes a hybrid particle swarm optimization/whale optimization algorithm for the optimal placement of different distribution generation types on a power network. Standalone metaheuristics are efficient and robust optimization tools but are mostly challenged with convergence and sub-optimal solutions. The exploration potential of particle swarm optimization with the selection of higher inertial weight is annexed with the exploitation phase of the whale optimization algorithm. The proposed technique is verified on IEEE 33 – bus distribution system. Results show 86.12% and 89.84% improvement in voltage deviation for Type I and Type III DG injection respectively. Besides, the convergence is achieved in less than 50 iterations compared to standalone methods.
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