Term of Award

Summer 2017

Degree Name

Master of Science in Applied Engineering (M.S.A.E.)

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Electrical Engineering

Committee Chair

Dr. Rami Haddad

Committee Member 1

Dr. Rocio Alba-Flores

Committee Member 2

Dr. Adel ElShahat


The growing demand for renewable energy source renders solar power as one of the most viable sources for future electrical energy production.However, its intermittent nature is the main limiting factor for its immediate adaptation. To overcome this limitation, electric storage devices, such as battery energy storage systems, are used to fill the void. However, battery energy storage systems are relatively expensive and usually suffer from low utilization especially if provisioned to accommodate the peak load. In this work, a centralized battery storage model for distributed photovoltaic systems is proposed to improve the storage system utilization and reduce the grid dependency. The proposed model consists of detailed analytical models of the photovoltaic and energy storage systems. To validate the proposed model, a comparative analysis was conducted to highlight the grid power dependency of the proposed centralized and current decentralized storage models using various synthetically generated load profiles. In addition, a case study where a centralized battery storage model for 60 residential locations was used to validate the proposed model using actual location-based hourly irradiance, temperature, and load demand. It was concluded that the proposed model improved the storage devices utilization by virtually smoothing out the high variation (peak loads) within the load profiles accommodated by the storage system. The grid dependency of this centralized storage model was evaluated and compared with the conventional decentralized storage model. As a result of using the centralized storage model, the utilization of the grid was reduced by 68.86% compared to the decentralized model for the same PV generation and storage capacity. A cost optimization analysis was also carried out for the centralized storage system to find out the optimal sizing in terms of the energy economy.

Research Data and Supplementary Material