Abstract
In this study, a new distributed pattern of demand side energy management in residential smart grids regarding Improved Sparse Bayesian Learning (ISBL) method along different types of domestic electrical appliances have been presented. Considering the overall expense of electricity usage, the restrictions of supply quantity is sustained through distribution set-ups and the obtained power demands for individual appliances, the optimal energy management (OEM), for the demand side users, such as households, became an elaborated optimization issue in relation to the coupled objective performance across spatially and temporally of doubled constraints. Usually, in distributed model, figuring out of this kind of issue is problematic. Hence, in this study, we had changed it into ISBL method, and developed a distributed algorithm in order to obtain an optimal quantity of the unified OEM across the procedure of implementation. The presented scheme does not need any personal information about individual operators, meanwhile each of optimality and convergence are achieved. Additionally, this article demonstrated that the presented scheme has high robustness in unreliable communications. In addition, the suggested scheme is demonstrated and confirmed through simulations.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.