Community approaches to socio-economic aspects of urban energy transition

The increasing proliferation of energy-intensive devices in urban smart homes presents a pressing challenge to the stability of electrical systems, manifesting as the potential for peak load issues, unexpected disruptions, and a consequential decline in economic returns. This research is dedicated to the meticulous optimization of energy consumption, achieved through the implementation of intelligent scheduling protocols for household devices, all while factoring in their distinct characteristics and user preferences. The primary objective of this paper is to introduce a holistic engineering framework tailored to analyze the intricate dynamics of household energy consumption behaviors, with a particular emphasis on the community-level context prevalent in smart urban environments. In addressing the inherent intricacy and nonlinearity inherent in multi-objective challenges within this domain, our proposal revolves around the deployment of a specialized whale optimization algorithm. This algorithm offers a powerful tool to efficiently navigate the complexities of optimization problems, yielding solutions that approach near-optimality. Empirical findings stemming from our experimentation robustly affirm the efficacy of our proposed algorithm. They indicate substantial reductions in energy expenditure, heightened levels of customer satisfaction, and a more equitably balanced load distribution throughout the primary grid. These outcomes, in turn, contribute significantly to the overarching enhancement of global power system performance, all the while aligning harmoniously with the socio-economic considerations central to urban energy transition endeavors.