Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency

Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency

Hybrid Energy Storage Systems (HESS) can provide solutions for grid stability and integration of renewable energy sources. A novel model integrating Model Predictive Control (MPC), Particle Swarm Optimization (PSO), Mixed-Integer Linear Programming (MILP), and Artificial Neural Networks (ANN) is dev...

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Bibliographic Details
Main Authors: Rajesh M. Bhagat, Dilendra B. Jasutkar, Amitkumar B. Ranit, Vikrant S. Vairagade, Balram Yelamasetti, Sagar D. Shelare, Shubham Sharma, Abinash Mahapatro, V.K. Bupesh Raja, Quadri Noorulhasan Naveed, Naoufel Kraiem, Saiful Islam, Jasmina Lozanovic
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:International Journal of Electrical Power & Energy Systems
Subjects:
Hybrid energy storage
Model predictive control
Particle swarm optimization
Grid stability
Renewable energy integration
Process
Online Access:http://www.sciencedirect.com/science/article/pii/S0142061525004521
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