Enhancing micro grid sustainability: Genetic-driven reptile search algorithm based carbon emission and cost reduction strategy

Abstract

Grid architecture is continuously changing in response to modern energy rules that ensure the integration of more renewable sources to lower the carbon footprint. The integration of non-dispatchable renewable energy sources (RESs) using low voltage grids is a possible alternative to a centralized method. Due to a recent trend, microgrids (MGs) are reducing their reliance on the primary grid by incorporating localized sources of electricity including energy storage devices, micro turbines, and fuel cells. Due to the expanding number of spread generating sources with diverse features, power dispatching schedule for distribution micro grids is becoming more challenging. This study offers a dispatch scheduling method from the perspective of an operator. The primary objective of this study is to employ the Genetic-driven Reptile search algorithm (G-RSA) for the dual purpose of minimizing carbon emissions and reducing costs within each microgrid. Additionally, fewer sale and purchase are made from the primary grid. Transmission losses are consequently reduced.