Abstract

Energy storage is essential for balancing the generation and load in power systems. Building a battery energy storage system (BESS) with retired battery packs from electric vehicles (EVs) or plug-in hybrid electric vehicles (PHEVs) is one possible way to subsidize the price of EV/PHEV batteries, and at the same time mitigating forecast error introduced by load and renewable energy sources in power systems. This paper proposes a detailed framework to evaluate end-of-life (EOL) EV/PHEV batteries in BESS application. The framework consists of three parts. A generalized model for battery degradation is first introduced. It is followed by modeling the battery retirement process in its first life. Two vehicle types—EV and PHEV—as well as two retirement modes—nominal and realistic modes—are considered. Finally, the application of the second-life BESS in power systems is modeled in a detailed economic dispatch (ED) problem. This is how second-life BESS’s performance translates into cost savings on power generation. An optimization problem is formulated to maximize total cost savings in power generation over the battery’s second life. This is done by striking a balance between short-term benefit (daily cost savings) and long-term benefit (cost savings through service years). Numerical results validate the effectiveness of the proposed framework/models. They show that battery usage and retirement criterion in its first life directly affect the performance in its second life application. In our case study, EV battery packs possess larger EOL energy capacities and consequently generate more cost savings in the second life. However, the BESS built from retired PHEV batteries has higher cost savings per MWh. It is because, with the proposed degradation model, battery health is better preserved in PHEV applications. Compared to nominal retirement mode, realistic retirement mode results in extra cost savings due to the reduced first-life service years.

Highlights

  • Energy storage is essential for balancing the generation and load

  • Since it directly links to the forecast errors to be mitigated during the day as well as the depth of discharge (DoD), ∆EBESS represents the trade-off between daily cost savings and service life of the battery energy storage system (BESS)

  • When the penetration level increases from 10% to 30%, i.e., wind power accounts for more error, the total cost savings becomes sensitive to and increases with the penetration level

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Summary

VARIABLES

C20nd,i Relative capacity of battery pack i at the beginning of its second life. Rated energy capacity of battery pack i. Life expectancy of battery pack i in EV/PHEV. Actual life span of battery pack i in EV/PHEV. Pjt and Pjt′ Power output of generator j at hour t without and with BESS. Rated capacity of WTGs. Power output of WTGs at hour t. Energy contributed from battery pack i in BESS at hour t. Average energy contribution of battery pack i in BESS during day td. Efficiency of battery pack i at the beginning of its second life

FUNCTIONS
PARAMETERS
INTRODUCTION
Part 3. Second-life application in power systems
MODELING BATTERY PERFORMANCE DEGRADATION
CASE STUDY
FIRST LIFE
SECOND LIFE
CONCLUSION
Findings
VEHICLE OWNERSHIP LENGTH
Full Text
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