As energy systems become increasingly complex, there is a growing need for sustainable and efficient energy management strategies that reduce greenhouse gas emissions. In this paper, multi-energy systems (MES) have emerged as a promising solution that integrates various energy sources and enables energy sharing between different sectors. The proposed model is based on using an Attractive Repulsive Shuffled Frog-Leaping (ARSFL) algorithm that optimizes the scheduling of energy resources, taking into account constraints such as capacity limitations and environmental regulations. The model considers different energy sources, including renewable energy and a power-to-gas (P2G) network with power grid, and incorporates a demand–response mechanism that allows consumers to adjust their energy consumption patterns in response to price signals and other incentives. The ARSFL algorithm demonstrates superior performance in managing and minimizing energy purchase uncertainty compared to the particle swarm optimization (PSO) and genetic algorithm (GA). It also exhibits significantly reduced execution time, saving approximately 1.59% compared to PSO and 2.7% compared to GA.

The growing presence of EVs in regional microgrids introduces increased variability and uncertainty in the areas’ load profiles. This paper presents a novel approach for optimizing energy and reserve minimization in a sustainable integrated microgrid with electric vehicles (EVs) by the use of the dynamic and adjustable Manta Ray Foraging (DAMRF) algorithm. The DAMRF algorithm harnesses the inherent flexibility of EVs as controllable loads and develops a comprehensive dispatch model for a large-scale EV response. The model takes into account the management, operational, and environmental costs associated with load fluctuations in the microgrid. Simulation evaluations conducted based on a practical microgrid environment validate the effectiveness of our wind–solar energy storage and management strategy. The results showcase significant improvements in energy and reserve minimization, highlighting the potential advantages of integrating EVs into sustainable microgrid systems. In addition, the DAMRF algorithm achieves lower environmental pollution control costs (USD 8000) compared to the costs associated with the Genetic Algorithm (GA) (USD 8654.639) and PSO (USD 8579.546), emphasizing its ability to effectively control and minimize environmental pollution. In addition, the DAMRF algorithm offers a more cost-effective solution for managing the power grid, and the shorter solution running time of the DAMRF is almost the same as PSO’s quicker decision-making and response times, enhancing the overall responsiveness and adaptability of the power grid management system.

Cleft lips and cleft palates are the most common birth defects in newborns. Pre-surgical correction of unilateral and bilateral cleft lips and palates has been the subject of interest of many previous works. This condition has necessitated the evolution of many surgical and non-surgical techniques to mitigate the problem of this deformity in children. In this study, we proposed a new architecture that can be used instead of the conventional pre-surgical treatment. The proposed architecture has mechanical and electronic parts. This architecture was adopted to apply external stress to the cleft bones and cleft edges using an airbag that is located in the mechanical part. The amount of air in the airbag can be controlled by an available control unit in the electronic part. The effect of external stress on the cleft bones and the cleft edges was analyzed by using the finite element analysis (FEA) method. The FEA study aimed to analyze the displacement, amount of tensile and compressive forces, and Von Mises stress distributions on the cleft bones, cleft edges, nasal septum, and superior alveolar part of the maxillary jaw of unilateral and bilateral cleft models during pre-surgical treatment with the novel architecture. The results show that displacement and stress affected the clefts of both models. Displacement had a significant effect of gradually bringing the clefts closer to each other and returning them to the posterior. The analysis also investigated the effects of stress on the cleft bone and cleft edge. It was found from the results that the stresses helped to bring the incisions closer to the most appropriate position for plastic surgeons. The results prove that the positive and negative X-displacements move in the opposite direction, which means that the cleft edges gradually converge toward each other. Moreover, the negative Z-displacement affected the movement of cleft bones and cleft edges from outside to inside and gradually returned them to a suitable position. The findings show that the proposed architecture can be contributed to the pre-surgical treatment of the unilateral and bilateral clefts as an alternative to the traditional method.