Model-Based Regional Comparison of Autonomy and Battery Utilization of Energy Storage Integration with Solar Power

For intermittent renewable energy sources to be utilized beyond small penetration levels in the electric grid they must be coupled with some form of energy storage (see Figure 1). Solar power varies on two time scales. Solar trends vary seasonally, but instantaneous solar power can also vary on a minute-to minute basis because of cloud cover. This variability creates a need for a flexible form of energy storage.

We used a model-based approach to study the autonomy (the percentage of time the system meets demand) and battery utilization (amount of capacity used)  of a battery system tied to solar generation during yearly operation.¹ Along with the variation in solar insolation seen throughout the year, we include a demand schedule which allows for different system load demands to be studied. Including demand allows for the study of different types of grid systems ranging from regional utility scale to Microgrid scale. In the study we look at Microgrid systems which include energy storage and distributed energy generation² and include both islanded and grid-tied demand structures. Grid charging options have been incorporated into the study and allow for an economic analysis of battery utilization strategies.

We used an electrochemical and transport based battery model battery model for the energy storage aspect of the system.³ For the solar portion of the model we will assess both ideal insolation curves as well as site based insolation data. For the real-site data, several solar monitoring sites within the US were studied. The real data from solar sites was obtained through an NREL database and will offer a contrasting look at how much the coupled system can be affected on a daily and seasonal basis.⁴

Comparisons for solar charging versus grid charging will be studied from an autonomy, utilization, and economic stand-point. System wide metrics will be used to assess the system’s operation.

Acknowledgements

The authors acknowledge financial support from 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.             C. Protogeropoulos, B. J. Brinkworth, and R. H. Marshall,  International Journal of Energy Research, 21, (1997)

2.             R. H. Lasseter,  Journal of Energy Engineering-Asce, 133, (2007)

3.             S. Santhanagopalan, Q. Z. Guo, P. Ramadass, and R. E. White,  Journal of Power Sources, 156, 620(2006)

4.             National Renewable Energy Laboratory. (2013). Solar Resource Data. Available: http://www.nrel.gov/rredc/solar_data.html