3.8 Article

A load frequency control using a PSO-based ANN for micro-grids in the presence of electric vehicles

期刊

INTERNATIONAL JOURNAL OF AMBIENT ENERGY
卷 42, 期 6, 页码 688-700

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/01430750.2018.1563811

关键词

Artificial neural network; load frequency control; micro-grid; fuzzy logic controller

向作者/读者索取更多资源

This study designed an effective PID controller for LFC in an island Micro-grid and proposed a model for EVs to contribute to LFC system. Using particle swarm optimisation based artificial neural network technique, the system became stable in the shortest time with reduced frequency oscillation magnitude, overshoot, and settling time.
Large frequency oscillations happen when the unbalanced power is not compensated by Load Frequency Controller (LFC) system. In recent years, the using of electric vehicles (EVs) has increased with renewable generation sources such as solar cells, wind turbines, fuel cells, and so on. The large-scale integration of these new types of generation sources and demand in power grids will have a significant impact on operations, planning and stability control. This work sets out to design an effective PID controller for LFC in an island Micro-grid (MG) and also proposes a model for EVs to contribute to LFC system. To this end, particle swarm optimisation (PSO) based artificial neural network (ANN) technique is considered to tune the parameters of PID controller in MG structure. Simulation results demonstrate that with PSO-based ANN, the system is becoming stable in shortest time. In addition, frequency oscillation magnitude, overshoot and settling time are reduced.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据