Model-Based Techno-Economic Analysis of Battery Function for Energy Storage of Solar Energy

By its nature solar power is intermittent. Because the amount of solar power generation cannot be controlled the economic value energy from a solar array is devalued. Adding energy storage can remove the intermittent nature of solar power (see figure 1), but will increase the overall cost of electricity supplied from the system. The model developed for this study analyzes the operational characteristics and economics of adding a battery system to solar arrays in different regions around the country. The technologic and economic benefits of battery systems are assessed on an individual site basis. A system level model includes a battery component based on electrochemical and transport principles, a solar array that accounts for site-based irradiance patterns, and a dispatch and control structure that controls the flow of power between generation and demand [1]. The battery component is the focus of the system level model and is studied to understand how the battery will function under dynamic application cycling. The irradiance data for US sites was obtained from the NREL MIDC database which contains minute resolution irradiance data for all the sites studied [2]. The battery model includes a study of how variation in irradiance will affect capacity fade by including fade side reactions into the model. Metrics studied include battery sizing, battery utilization, battery degradation, system autonomy, solar energy utilization. Additionally, the economic value of systems were studied based on time-of-use pricing scenarios to determine break-even points for adding battery to solar arrays for non-utility customers. The economic analysis is informed by the battery utilization and system autonomy studied in the model. Comparisons of individual sites and solar+battery systems were studied. These model-based studies are important for determining the utility of batteries in conjunction with renewable applications. Acknowledgements The authors acknowledge financial support from the U.S. Department of Energy’s Advanced Research Projects Agency- Energy (ARPA-E), and the Solar Energy Research Institute in India and the United States (SERIIUS), as well as, Washington University in St. Louis’ McDonnell Academy Global Energy and Environmental Partnership (MAGEEP). References 1. S. Santhanagopalan, Q. Z. Guo, P. Ramadass, and R. E. White, Journal of Power Sources, 156 , 620(2006) 2. National Renewable Energy Laboratory. (2014, 2014). Measurement and Instrumentation Data Cen