ELECTRICA
Original Articles

Result-Adaptive PID Control Based Ant Colony Optimization Tuning for Battery Operation Control in Standalone PV System With Consumption Side Power Management

1.

Energy Engineering and Computer Engineering Laboratory L2GEGI, Ibn Khaldoun University of Tiaret, Tiaret, Algeria

2.

Energy Engineering and Computer Engineering Laboratory L2GEGI, Higher School of Electrical and Energetic, Oran, Algeria

ELECTRICA 2024; 24: 710-721
DOI: 10.5152/electrica.2024.24041
Read: 137 Downloads: 68 Published: 23 October 2024

Abstract
The evolution of the management of smart grids, which mainly aims to integrate various high-capacity energy sources, more specifically photovoltaic units, on the one hand, as well as optimal control of loads connected to the network in order to ensure coordination between production and consumption, leads not only to the management of production units but also to the management of consumption power using different static converters. This makes this operation possible, and feasible but complex because of their effects on the quality of energy and the need for reliable control. There are currently many studies focusing on power management from the consumption side. This article then proposes a new controller for managing the requested power by combining an optimization technique, which is the Ant Colony Optimization (ACO), with an adaptive PI regulator, which is the Result-Adaptive PID (RAPID) Control, as the controller of the operation of the battery. The battery represents an essential part in solar installations, enabling energy-efficient operation of the network by regulating the operation of controllable loads. To adjust the RAPID regulator using the ACO algorithm, we used an objective function to minimize the error between the input and output of the new regulator. Demonstrated on an isolated DC-AC network, the performance of the proposed controller for energy management on the consumption side is established after comparison with standard controllers such as the classic PI based trial & error methods and the RAPID tuned by ACO.

Cite this article as: M. Bey, R. Araria, S. Bouradi, S. Drias and A. Thamer, "Result-adaptive PID control based ant colony optimization tuning for battery operation control in standalone PV system with consumption side power management," Electrica, 24(3), 710-721, 2024.

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