Life cycle cost analysis (LCCA) of PV-powered cooling systems with thermal energy and battery storage for off-grid applications. (1st September 2020) - Luerssen, Christoph; Gandhi, Oktoviano; Reindl, Thomas; Sekhar, Chandra; Cheong, David
Highlights: Comparison of battery and thermal energy storage and their combinations. Optimisation to determine the most cost-effective solutions for off-grid cases. Battery storage offers the lowest LCC in most cases. Combinations of thermal energy storage and battery can reduce the LCC. Combinations of thermal energy storage and battery reduce fuel consumption. Abstract: In this paper, we determine the optimised life cycle cost (LCC) of PV-powered cooling systems for three off-grid applications, namely a remote eco-resort, a hotel, and a refrigerated warehouse. We focus our work on the comparison of seven different system configurations with battery and thermal energy storages (chilled water and ice), as well as a combination of both to a purely diesel-powered baseline case. Therefore, we set up energy simulation and LCC models in TRNSYS and carried out multi-parameter optimisations for each system configuration and scenario. The results show that adding PV to the diesel generator reduces the LCC by 9–10%, while additional batteries reduce the LCC further for all scenarios – 14–17% compared to the diesel-powered baseline. Although thermal energy storages on their own cannot compete with battery storage, a combination of both can yield competitive LCC. Moreover, the optimised cases with a combination of battery and thermal energy storage oer the highest fuel cost savings of 51–77% compared to the baseline case, while the optimised cases with just battery only yield 39–48%. However, the investment is 27–50% higher for the system with a combination of thermal energy storage and battery compared to the configurations with only battery storage. To validate the results and the chosen parameters thorough sensitivity analyses were conducted. The analyses show that the LCC are especially influenced by financial parameters, namely fuel price, fuel price escalation and the discount rate.