This project investigates the viability of using reconditioned batteries, which have lost part of their original capacity while powering electric vehicles (EVs), to minimize the expenses of fast-charging infrastructures under the three charging scenarios where fast-charging mode is likely to be needed the most. The analysis is conducted for the Spanish scenario and considers the retail electricity tariff that best suits the requirements of a FCS. The economic analysis is performed on an annual basis and is tackled with an optimization algorithm, formulated as a mixed-integer linear programming problem and run on MATLAB. The expected lifetime of the ESS, being made of reused automotive cells, is estimated with a semi-empirical approach, using an iterative process and implemented in MATLAB. A sensitivity analysis is conducted on three input parameters that were identified to have a considerable impact on the system design and performance. Overall, results show that with current figures energy storage integration in FCSs is viable as it effectively reduces the infrastructure expenses in all scenarios. Peak-shaving is identified as the main source of cost savings while demand shifting is not effective at all. The latter is further discussed in the sensitivity analysis and some considerations are elaborated. The most profitable scenario for storage integration is the case of a fast-charger located in a urban environment while, surprisingly, the lowest cost savings are obtained in the highway case. The sensitivity analysis illustrates the impact and effects that electricity prices and specific cost of both the power converter and the second-life batteries produce on the optimal system design. Moreover, charging demand profiles are deeply analyzed and their main implications highlighted.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-226328 |
Date | January 2017 |
Creators | de Maio, Pasquale |
Publisher | KTH, Energi och klimatstudier, ECS |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | TRITA-ITM-EX ; EGI_2017:0100 |
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