Optimizing dispatch factor in smart energy networks using cloud-based computational resources

The coordination of eco-friendly power sources and brilliant matrix advances has changed the power lattice framework. Optimized dispatch of distributed resources assisted by cloud-based technologies, is inevitable in this evolving era of could computing. This paper provides a comprehensive framework of cloud-based load management technologies, with a focus on the dispatch factor as a crucial parameter in making energy dispatch decisions. Cloud computing provides grid administrators with the adaptability and computational power expected to advance energy dispatch continuously. The contributions of this research work about the optimized dispatch of power sources include i) formulation of constrained optimization objective function for power distribution network ii) proposed a novel algorithm for evaluation of the parametric values involved in proposed objective function. iii) proposed a framework for resourcing the computational burden to cloud computational platform. These contributions inculcates a methodology for efficient energy dispatch, highlighting the use of machine learning, optimization algorithms, and real-time data analytics to adjust the dispatch factor dynamically. The paper concludes with the discussion of results obtained after implementation of proposed methodology on google cloud platform which shows the effectiveness of the proposed methodology.