Session: 07-02: CSP Systems Analysis for Heat and Electricity Applications

Paper Number: 142465

142465 - Analysis of a System Employing Parabolic Trough and Heat Pump Technology to Generate Process Heat and Charge Tes 

Abstract: 

Industrial process heat (IPH) accounts for approximately 8% of primary energy consumption in the United States. Most of this thermal energy currently is generated by the combustion of fossil fuels, so IPH is a critical sector for decarbonization efforts.  Over 50% the IPH demand occurs at temperatures colder than 500 C. In sunny climates, both concentrating solar thermal (CST) and PV-driven electrification technologies are attractive options to generate thermal energy in this temperature range without carbon emissions. CST technologies, like parabolic troughs and linear Fresnel, are commercially available with years of operating history. These technologies also have the option to heat a sensible heat fluid that combines well with existing thermal energy storage (TES) technology to make heat available to an off-taker during periods when solar resource is unavailable. Electrification options like heat pumps and resistance heaters rely on low-cost electricity to generate heat at competitive prices, so these technologies also may utilize TES to charge during periods with low-cost electricity and discharge during periods with high-cost electricity. This study investigates the performance, operation, and techno-economics of a hybrid system that employs both a parabolic trough and a heat pump that share a common TES and heat customer.

We leverage and extend existing CST models in NREL’s System Advisor Model (SAM) to develop the hybrid model. We use the existing parabolic trough model and nominally employ the two-tank TES model. We model the heat pump using a simple coefficient of performance (COP) informed by literature and scale this value based on changes to ambient temperature. We assume that the customer requires steam, and we vary its operation schedule to investigate both 24-7 operation and weekday shifts. We use modeled grid data from futures studies to predict hourly electricity prices. With these inputs and for a given weather file, TES size, parabolic trough design, and heat pump capacity, we implement an operations model that chooses optimal operation of the heat generation components and TES to provide the lowest cost heat to the customer. We use a mixed integer linear program for the operations model that is informed by the detailed SAM models in a rolling horizon approach. This framework ensures that the operations model is robust to changes in system design and does not drift over the course of the annual simulation due to non-linearities in the physical model. We optimize design inputs like parabolic trough size, TES size, heat pump capacity to find the optimal design that minimizes annualized cost to meet the customer’s load, both with and without a backup gas-fired boiler. Finally, assess the influence of component cost and electricity purchase assumptions on the optimal solution.

Presenting Author: Ty Neises NREL

Presenting Author Biography: Name: Ty Neises

Institution: NREL

Email Address: Ty.Neises@nrel.gov

Authors:

Ty Neises NREL
Alexander Zolan NREL
William Hamilton NREL