Abstract
This thesis analyzes the impacts battery storage and electric vehicle charging have on a building’s energy consumption and utility spend. The building used as a case study was the Academic Information Resource Center (AIRC) which is a multi-use building at the campus at California State University, Sacramento (CSUS). To model and simulate the AIRC building, Homer Grid was utilized which is a software that focuses on simulation and cost optimization for energy systems. The software offers two different controllers, the peak shaving controller and the MATLAB link controller, to simulate and optimize the system. The energy consumption for 2018 was uploaded into the software and was validated though matching the tariff code the university is billed on and the trends of case studies for battery storage and electric vehicle inclusion. The average percent difference of the actual utility spend attributed to the AIRC building and the Homer Grid monthly utility spend is 11.45%. To further investigate the validity of the working model, a case study with the inclusion of battery storage is considered. An increase of electrical consumption and decrease in utility spend were observed which is consistent with the understanding that battery storage will increase the systems utilization while decreasing cost for the system. The increase in grid purchases align with battery losses that are experienced with battery inclusion in the base case scenario. Another case study includes electric vehicle charging which displayed results consistent with the understanding that an increase in electrical consumption and the utility bill of the system are warranted.
After validation of the model, the peak shaving controller and MATLAB link controller are used to simulate the system to assess the various impacts different scenarios can have. Case study A, which included battery storage and electric vehicle charging and was simulated through the peak shaving controller, saw an increase of 10.77% in electricity consumption and an increase of 11.48% in utility spend when compared to the base case. Case study B, which included battery storage, electric vehicle charging, and photovoltaic production and was simulated through the peak shaving controller, also saw an increase of 10.77% in electricity consumption which was anticipated since no factors were changed in this case study that would’ve affected electricity consumption. Case study B also saw a decrease of 3% in utility spend on grid purchases when compared to the base case. Case study C, which included battery storage and was simulated through a dispatch strategy in MATLAB, saw an increase of 345.1% in annual battery throughput when compared to case study A and an increase of 355.5% when compared to case study B.