Distributed Reinforcement Learning Framework for Autonomous Optimization of Grid-Scale Energy Storage Systems in Renewable Energy Integration-Reference-Cited by-同舟云学术

Distributed Reinforcement Learning Framework for Autonomous Optimization of Grid-Scale Energy Storage Systems in Renewable Energy Integration

Author:

Nuvvula Ramakrishna S S¹,Kumar Polamarasetty P²,Ahammed Syed Riyaz³,R Hushein⁴,Reddy R.Siva Subramanyam⁵,Harish Babu Bachina⁶,Ali Ahmed⁷

Affiliation:

1. NITTE Deemed to be University,NMAM Institute of Technology,Deparmtent of Electrical and Electronics Engineering,Karnataka,India

2. GMR Institute of Technology,Department of Electrical and Electronics Engineering,Rajam,India

3. NITTE Deemed to be University,NMAM Institute of Technology,Department of Electronics & Communication Engineering,Karnataka,India

4. Vel Tech RanagarajanDr.Sagunthala R&D Institute of Science and Technology,Department of Electronics and Communication,Chennai,India

5. Sri Kalahasteeswara Institute of Technology (SKIT),Department of EEE,Srikalahasti,Andhra Pradesh A.P

6. VNR Vignana Jyothi Institute Of Engineering & Technology,Department of Automobile Engineering,Telangana

7. University of Johannesburg,Department of Electrical and Electronic Engineering Technology,South Africa

Publisher

IEEE

Link

Reference14 articles.

1. Optimization of Grid-Scale Energy Storage Using Distributed Reinforcement Learning;Li;IEEE Transactions on Sustainable Energy,2023

2. Challenges in Integrating Renewable Energy Sources into Smart Grids;Jha;Renewable Energy,2023

3. A Review on Distributed Control Systems for Grid-Scale Energy Storage;Sharma;Journal of Power Sources,2024

4. Decentralized Decision Making in Energy Storage for Effective Renewable Integration;Gupta

5. Advanced Machine Learning Techniques for Energy Systems: A Focus on Reinforcement Learning;Kumar;Energy AI,2023