Abstract

Battery storage is essential to enhance the flexibility and reliability of electric power systems by providing auxiliary services and load shifting. Storage owners typically gains incentives from quick responses to auxiliary service prices, but frequent charging and discharging also reduce its lifetime. Therefore, this paper embeds the battery degradation cost into the operation simulation to avoid overestimated profits caused by an aggressive bidding strategy. Based on an operation simulation model, this paper conducts the economic viability analysis of whole life cycle using the internal rate of return(IRR). A clustering method and a typical day method are developed to reduce the huge computational burdens in the life-cycle simulation of battery storage. Our models and algorithms are validated by the case study of two mainstream technology routes currently: lithium nickel cobalt manganese oxide (NCM) batteries and lithium iron phosphate (LFP) batteries. Then a sensitivity analysis is presented to identify the critical factors that boost battery storage in the future. We evaluate the IRR results of different types of battery storage to provide guidance for investment portfolio.

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