Chaotic-Based Big Bang-Big Crunch Algorithm (CBCA) for Energy Management System of Hybrid Isolated Micro-grid: An Inherent Control Scheme

• Published in: Energy sources. Part A, Recovery, utilization, and environmental effects Vol. 47; no. 1; pp. 3827 - 3847
• Main Authors: Kalki, Kavin Mullai, Rajaguru, Harikumar
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 31.12.2025
• Subjects: Energy management; hybrid renewable energy sources; maximum power point tracking; sources converter; system power balance and energy constraints
• DOI: 10.1080/15567036.2020.1859012
• ISSN: 1556-7036

In this manuscript, an energy management and maximum power point tracking (MPPT) to micro-grid based on hybrid renewable energy sources (HRESs) like wind, solar, battery using an inherent control scheme. The proposed control scheme is the chaotic-based big bang-big crunch algorithm (CBCA). Here, chaotic-based techniques have been integrated into BB-BC to get the global optimum solution. In the proposed control scheme, the CBCA streamlines the parameter of the sources converter according to the required load demand and creates the optimal switching pulses. By the proposed control scheme the sources are controlled and operate in the MPPT during low energy generation or off-MPPT modes during the excess of energy to meet the load requirement based on the system power balance and energy constraints. The proposed control scheme is designed to operate the micro-grid as an autonomous system considering the power obtainable from renewable sources, the load power requirement including the condition of the battery. Finally, the voltage on the load side is controlled to assure proficient power transfer from the source of energy to the load. With this proper control, the proposed technique presents a steady control function at every micro-grid subsystems subject to different power generation including load conditions. By then, the performance of the CBCA scheme is implemented in the MATLAB/Simulink work site and also the implementation is likened to the existing approaches like GOA and AGONN. The statistical analysis of CBCA with existing approaches under cases 1, 2, and 3 has been analyzed. The CBCA method under cases 1, 2, and 3 of mean, median, the standard deviation is more efficient than the existing solution strategies. The mean value of the CBCA method under case 1 indicates 1.2641. The median value of the CBCA method under case 2 implicates 1.2204. The standard deviation value of the CBCA method under case 3 denotes 0.0762.