Session: 08-02: Technoeconomic Analysis of CSP and Thermal Energy Storage Systems

Paper Number: 169893

169893 - “Optimization and Techno-Economic Analysis of a Hybrid Pv-Csp System With Thermal Energy Storage and Sco2 Brayton Cycle 

Abstract: 

This project investigated and optimized the performance and cost of a solar thermal energy storage system through the development of an energy-based techno-economic analysis model in Python. The primary objective was to identify optimal system and subcomponent sizes, as well as target deployment locations. The model balanced energy across system generation and storage components on an hourly basis, utilizing data from the National Solar Radiation Database's Typical Meteorological Year (TMY) to simulate photovoltaic (PV) and concentrated solar collector energy output over an entire year (8760 hours).

The system aimed to meet a constant electrical load each hour by either supplying generated energy directly to the load or storing excess energy for later use. Key components included PV panels for ice production and daytime load management, a solar collector for harnessing and storing solar energy as heat, and a supercritical CO2 (sCO2) power block for converting thermal energy back to electricity. The model also tracked the amount of ice required to enable power output from the power block and tracked system cost and performance in grid-tied and isolated scenarios.

Comprehensive assessments across various U.S. cities and geographical regions revealed optimal deployment locations and sizes along with grid-connected or isolated configurations. Initial validation was conducted through a case study in Page, Arizona, followed by evaluations in California, Colorado, Texas, West Virginia, and Florida.

The Levelized Cost of Electricity (LCOE) trends revealed several key insights into the economic performance of solar thermal energy storage systems across various locations. Generally, grid-tied systems exhibited lower LCOE values compared to isolated systems, indicating their cost-effectiveness. The lowest LCOE for grid-tied systems is observed in Otero County, NM, and Sierra Vista, AZ, both at $0.080/kWh. In contrast, the lowest LCOE for isolated systems was found in El Paso, TX, at $0.109/kWh. This result highlights the economic advantage of grid-tied configurations, particularly in regions with favorable solar conditions.

Conversely, the highest non-load-met-percentage constrained LCOE values for both grid-tied and isolated systems were observed in New Martinsville, WV, at $0.099/kWh and $0.143/kWh, respectively. This suggests that locations with lower solar irradiance or other unfavorable conditions may face higher costs for solar thermal energy storage. For instance, Denver, CO, shows slightly higher LCOE values with $0.089/kWh for grid-tied and $0.125/kWh for isolated systems, reflecting the impact of geographical and climatic variations on energy storage costs.

Other locations like Clearwater, FL, and Oxnard, CA, exhibited moderate LCOE values, with grid-tied systems at $0.082/kWh and $0.117/kWh for isolated systems in Clearwater, and $0.082/kWh and $0.117/kWh in Oxnard. These values indicate that while these locations are viable for solar thermal energy storage, they may not be as cost-effective as the top-performing regions.

The results also show that meeting a higher percentage of load correlates with higher LCOE. In high Direct Normal Irradiance (DNI) locations such as El Paso, TX, the LCOE for grid-tied systems at 85% Load Met Percentage (LMP) was $0.141/kWh compared to the El Paso, TX minimum of $0.08/kWh. This trend is repeated across all locations and underscores that meeting a high percentage of the load comes at a cost. Generally, high DNI locations in AZ, NM, and TX show the lowest LCOE values for grid-tied systems at 85% LMP, further emphasizing the benefits of high DNI locations.

Overall, the study highlights economic advantages of grid-tied systems over isolated systems and the significant influence of location and load met percentage on the LCOE. These insights are crucial for strategic planning and optimization of solar thermal energy storage deployments, ensuring that investments are directed towards regions and configurations that offer the best economic returns.

Presenting Author: Taylor Johnson Sandia National Laboratories National Solar Thermal Test Facility

Presenting Author Biography: Taylor Johnson is a senior Mechanical Engineering student at the University of Florida with a strong focus on renewable energy conversion and storage. Taylor is a former intern at the National Renewable Energy Laboratory and currently works at Sandia National Laboratories National Solar Thermal Test Facility as a Thermal Sciences R&D intern.