Dynamic Energy Management of a Microgrid Using Approximate Dynamic Programming and Deep Recurrent Neural Network Learning

Zeng, Peng; Li, Hepeng; He, Haibo; Li, Shuhui

doi:10.1109/tsg.2018.2859821

Public

Dynamic Energy Management of a Microgrid Using Approximate Dynamic Programming and Deep Recurrent Neural Network Learning

Published in IEEE Transactions on Smart Grid • Jul 25, 2018

Authors:

Peng Zeng

Hepeng Li

Haibo He

Abstract

This paper focuses on economical operation of a microgrid (MG) in real-time. A novel dynamic energy management system is developed to incorporate efficient management of energy storage system into MG real-time dispatch while considering power flow constraints and uncertainties in load, renewable gen...

Subject

Microgrid

Markov decision process

Dynamic programming

Research Assistant

AI chat, annotations, notes & similar papers

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!