A cost-benefit secured DAG based analysis of distributed energy generation in urban settings

Abstract

This study presents a groundbreaking approach to energy management in urban areas, focusing on smart building frameworks. The proposed method integrates a Directed Acyclic Graph (DAG) architecture to enhance data security, transparency, and integrity within the smart building ecosystem. To optimize the energy management system, advanced algorithms, namely Harmony Search (HS) and Artificial Bee Colony (ABC), are employed. Notably, the HS and ABC algorithms undergo modifications to improve their efficiency and convergence properties. The innovative use of these algorithms aims to achieve global solutions in the complex optimization landscape of energy management. The study explores the synergistic effects of DAG, HS, and ABC, providing a robust and secure solution for urban energy challenges. The proposed framework is designed to address the dynamic nature of smart buildings, allowing for adaptive and efficient energy consumption. The findings contribute to the advancement of sustainable urban development, emphasizing the importance of secure data transactions and optimized energy utilization in the context of smart cities. The modified HS and ABC algorithms play a key role in fine-tuning the energy management process, offering a novel and effective approach to address the evolving energy needs of urban areas.