Author : Xin Qiu
Publisher :
ISBN 13 :
Total Pages : 95 pages
Book Rating : 4.:/5 (92 download)
Book Synopsis Modeling and Optimization of Energy Storage System for Microgrid by : Xin Qiu
Download or read book Modeling and Optimization of Energy Storage System for Microgrid written by Xin Qiu and published by . This book was released on 2014 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The vanadium redox flow battery (VRB) is well suited for the applications of microgrid and renewable energy. This thesis will have a practical analysis of the battery itself and its application in microgrid systems. The first paper analyzes the VRB use in a microgrid system. The first part of the paper develops a reduced order circuit model of the VRB and analyzes its experimental performance efficiency during deployment. The statistical methods and neural network approximation are used to estimate the system parameters. The second part of the paper addresses the implementation issues of the VRB application in a photovoltaic-based microgrid system. A new dc-dc converter was proposed to provide improved charging performance. The paper was published on IEEE Transactions on Smart Grid, Vol. 5, No. 4, July 2014. The second paper studies VRB use within a microgrid system from a practical perspective. A reduced order circuit model of the VRB is introduced that includes the losses from the balance of plant including system and environmental controls. The proposed model includes the circulation pumps and the HVAC system that regulates the environment of the VRB enclosure. In this paper, the VRB model is extended to include the ESS environmental controls to provide a model that provides a more realistic efficiency profile. The paper was submitted to IEEE Transactions on Sustainable Energy. Third paper discussed the optimal control strategy when VRB works with other type of battery in a microgrid system. The work in first paper is extended. A high level control strategy is developed to coordinate a lead acid battery and a VRB with reinforcement learning. The paper is to be submitted to IEEE Transactions on Smart Grid"--Abstract, page iv.