Operations Research Techniques For Optimizing Smart Grid Systems
Year: 2024
Type: article
Abstract: The application of operations research techniques, advanced algorithms related to optimizing smart grids for their smart operations, and distributed energy resources, electric vehicle (EV) charging coordination, and load forecasting are focused upon in this paper of research. Four key algorithms were used to optimize energy distribution: GA, PSO, ML, and RL, which ultimately helped to improve grid stability and thus bring a decline in the operational cost. Demonstrations of results show 12% improvement in grid efficiency, 15% reduction in energy loss, and 10% improvement as compared to conventional methods in terms of load forecasting accuracy. Coordinated EV charging using reinforcement learning produces a 20% increase in system fairness. Validation is completed through a comparative analysis with existing works. This finding also manifests the need for AI-enabled decision-making as something related to smart energy systems for tackling future energy challenges.
Source: Nanotechnology Perceptions
Authors: Manish Patidar, Dr. Ashish Kumar, Dr. Deepak Kartikey, Dr. Nishank Sudhakar Pimple, Akansh Garg, Dr.Anand Mahadev Mahajan
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4403679618