Title

Power flow control in grid-connected microgrid operation using Particle Swarm Optimization under variable load conditions

Document Type

Journal Article

Publisher

Elsevier

Faculty

Faculty of Health, Engineering and Science

School

School of Engineering/Centre for Communications and Electronics Research

RAS ID

14510

Comments

This article was originally published as: Al-Saedi, W. A., Lachowicz, S. W., Habibi, D. , & Bass, O. (2013). Power flow control in grid-connected microgrid operation using Particle Swarm Optimization under variable load conditions. International Journal of Electrical Power & Energy Systems, 49(1), 76-85. Original article available here

Abstract

This paper presents an optimal power flow controller for a utility connected microgrid based on a real-time self-tuning method. The purpose is to control the flow of the active and reactive power between the main grid and the microgrid composed of Distributed Generation (DG) units. Sharing power at the desired ratio by the DG units is the main performance parameter which is considered during the load change. This paper also shows the response of the controller in situations, where the load is either higher or greatly lower than the rated power of the DG unit. In this work, the controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. The power controller is designed for active-reactive power (PQ) control strategy. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that the required load power is shared equally between the microgrid and the utility based on the PSO algorithm during the load change. The utility supplies the difference power when the load is more than the power generated by the microgrid, while it injects the extra power to the grid when the load is less than the power generated by the microgrid. The results show that the proposed controller offers an excellent response and proves the validity of the proposed strategy.

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