A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption

Abstract

Hydrogen plays a crucial role in the quest for sustainable and clean energy solutions, and its effect on smart home energy management is of particular interest. With the rapid advancements in smart home technologies, energy optimization has become essential, aiming to achieve efficient energy consumption, cost reduction, and enhanced user comfort. Green hydrogen, produced through the electrolysis of water using renewable energy sources, emerges as a promising solution for sustainable energy. It offers numerous benefits, including zero greenhouse gas emissions, high energy density, and versatile applications. In the context of this study, the enhanced northern goshawk optimization (ENGO) algorithm and the original northern goshawk optimization (NGO) algorithm are investigated for optimizing smart home energy management. By employing a two-stage approach based on high and low-velocity ratios, ENGO overcomes the limitations of NGO, such as low exploitation capability and being trapped in local optima. The study demonstrates that ENGO outperforms NGO in achieving multiple objectives simultaneously, including reducing the peak-to-average ratio (PAR), lowering electricity costs, and ensuring user comfort. Furthermore, ENGO proves to be more robust, capable of handling complex smart home energy management problems with multiple constraints. Thus, the integration of hydrogen solutions, such as green hydrogen, with advanced optimization techniques like ENGO, can significantly contribute to the effective management of energy resources in smart homes, promoting sustainability and user satisfaction.