You are here
DESIGN AND OPERATION OF STATIONARY DISTRIBUTED BATTERY MICRO-STORAGE SYSTEMS
| Title: | DESIGN AND OPERATION OF STATIONARY DISTRIBUTED BATTERY MICRO-STORAGE SYSTEMS. |
 59 views 11 downloads |
|---|---|---|
| Name(s): |
Al-Haj Hussein, Ala, Author Batarseh, Issa, Committee Chair University of Central Florida, Degree Grantor |
|
| Type of Resource: | text | |
| Date Issued: | 2011 | |
| Publisher: | University of Central Florida | |
| Language(s): | English | |
| Abstract/Description: | Due to some technical and environmental constraints, expanding the current electric power generation and transmission system is being challenged by even increasing the deployment of distributed renewable generation and storage systems. Energy storage can be used to store energy from utility during low-demand (off-peak) hours and deliver this energy back to the utility during high-demand (on-peak) hours. Furthermore, energy storage can be used with renewable sources to overcome some of their limitations such as their strong dependence on the weather conditions, which cannot be perfectly predicted, and their unmatched or out-of-synchronization generation peaks with the demand peaks. Generally, energy storage enhances the performance of distributed renewable sources and increases the efficiency of the entire power system. Moreover, energy storage allows for leveling the load, shaving peak demands, and furthermore, transacting power with the utility grid. This research proposes an energy management system (EMS) to manage the operation of distributed grid-tied battery micro-storage systems for stationary applications when operated with and without renewable sources. The term "micro" refers to the capacity of the energy storage compared to the grid capacity. The proposed management system employs four dynamic models; economic model, battery model, and load and weather forecasting models. These models, which are the main contribution of this research, are used in order to optimally control the operation of the micro-storage system (MSS) to maximize the economic return for the end-user when operated in an electricity spot market system. | |
| Identifier: | CFE0003964 (IID), ucf:48712 (fedora) | |
| Note(s): |
2011-08-01 Ph.D. Engineering and Computer Science, School of Electrical Engineering and Computer Science Doctorate This record was generated from author submitted information. |
|
| Subject(s): |
Artificial neural network battery model energy management system extended Kalman filter micro-storage state-of-charge state-of-health |
|
| Persistent Link to This Record: | http://purl.flvc.org/ucf/fd/CFE0003964 | |
| Restrictions on Access: | campus 2012-07-01 | |
| Host Institution: | UCF |
