A load frequency control using a PSO-based ANN for micro-grids in the presence of electric vehicles. Issue 6 (26th April 2021)

• Record Type: Journal Article
• Authors: Safari, Amin; Babaei, Farshad; Farrokhifar, Meisam
• Is Part Of: International journal of ambient energy. Volume 42:Issue 6(2021)
• Page Start: 688
• Page End: 700
• Publication Date: 2021-04-26
• Subjects: Artificial neural network -- load frequency control -- micro-grid -- fuzzy logic controller; Power resources -- Periodicals; Renewable energy sources -- Periodicals; 621.04205
• DOI: 10.1080/01430750.2018.1563811
• Languages: English
• ISSNs: 0143-0750

Abstract

ABSTRACT: 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.