Date of Award

December 2018

Degree Type


Degree Name

Master of Science


Computer Science

First Advisor

Jun Zhang

Committee Members

Adel Nasiri, Chao Zhu


bellman equation, dynamic programming, hybrid renewable energy systems, matlab, optimization


Hybrid renewable energy systems offer great promise for the future. However, some lingering concerns regarding stability and cost efficiency still exist. If a private party installs the system and maintains full control, the party may itself alleviate some of these problems by wisely optimizing the benefits offered by the system. One of the ways to do so is to develop a schedule for their load such that the cost incurred is minimized; this is done by maximally utilizing the renewable sources of energy before using the backup options of more conventional energy sources. Creating such a schedule involves considering several factors, such as solar energy available and the quantity of load that may be flexibly scheduled as opposed to fixed demands. This work presents a unique and innovate method – dynamic programming – to solve this problem. This is modeled in a mathematical context, one of optimal control, and then implemented using MATLAB. Care is taken to generate a realistic model that serves as a starting point for further research while idealizing some components for simplicity.