Optimisation of Smart Grid Renewable Energy Integration Based on Hidden Markov Models
This paper proposes an optimization method based on hidden Markov models.It addresses the uncertainties in integrating renewable energy into smart grids.The method combines demand response strategies,real-time pricing,and optimal scheduling of storage systems.Simulations were conducted on a modified IEEE 30-bus system.The Markov decision process was found to significantly improve prediction accuracy.After applying demand response strategies,generation costs and emissions were substantially reduced.Peak demand was also effectively decreased.The proposed integrated energy management system was proven to lower operational costs and emissions.Grid reliability was improved as well.This study provides a viable solution for efficient integration of renewable energy in smart grids.
demand responsedynamic programmingenergy managementrenewable energy generationenergy storage systems
万方数据
维普
