Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)


Electrical Engineering and Computer Science

First Advisor

Reinaldo Tonkoski

Second Advisor

Timothy M. Hansen

Third Advisor

Robert Fourney


The contribution of renewable energy resources in the global energy generation has been increasing at a fast pace. Variability and uncertainty are the two main issues related to renewable energy integration. Thus, energy storage systems (ESSs) are used in such systems to smooth the power generated by the renewable energy sources. In order to ensure reliable and economic operation of the system, energy management system (EMS) is implemented to control the dispatch of the available resources. ESS such as a battery requires significant capital investment and frequent replacement. A battery has a maximum lifetime called float life, regardless of energy throughput. Furthermore, the useful lifetime of these batteries varies considerably based on the operating conditions. Generally, the batteries are used excessively without considering the impact on the useful lifetime when used in systems that are isolated from the utility. On the contrary, the batteries are rarely used in the systems that are connected to the utility such that the available output is wasted at the end of the float life of the batteries. Thus, the consideration of the battery lifetime characteristics in EMS can maximize the battery utilization during its useful life. In this work, implementation of EMS including the battery lifetime for the operation of hybrid power systems– a remote microgrid, and a data center are investigated. Implementation of EMS for the annual operation of a remote microgrid considering the battery lifetime is performed. A heuristic search technique– genetic implementor (genitor) algorithm has been implemented as the inclusion of fuel consumption of diesel generator and battery degradation models in objective function yields in high nonlinearity. The fuel consumption and battery output minimization are achieved. Similar to a remote microgrid, EMS can also be implemented in large scale systems like data centers. Data centers consume a large amount of energy and have backup resources allocated for emergency conditions. These resources can be utilized to participate in demand response (DR) to reduce the peak load demand. Real-time dispatch module of a data center is developed to consume daily allocated budget for battery usage to ensure utilization of the battery. The real-time operational cost of a data center is reduced for participation in DR as compared to the operational cost without DR.

Library of Congress Subject Headings

Electric power systems -- Management.
Renewable energy sources.
Storage batteries.


Includes bibliographical references (79-85)



Number of Pages



South Dakota State University


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