In this paper, we present mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.
Rehman, Waqas ur, et al. "Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation." Applied Energy, vol. 313, Mar. 2022. https://doi.org/10.1016/j.apenergy.2022.118745
Rehman, Waqas ur, Bo, Rui, Mehdipourpicha, Hossein, & Kimball, Jonathan W. (2022). Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation. Applied Energy, 313. https://doi.org/10.1016/j.apenergy.2022.118745
Rehman, Waqas ur, Bo, Rui, Mehdipourpicha, Hossein, et al., "Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation," Applied Energy 313 (2022), https://doi.org/10.1016/j.apenergy.2022.118745
@article{osti_1853992,
author = {Rehman, Waqas ur and Bo, Rui and Mehdipourpicha, Hossein and Kimball, Jonathan W.},
title = {Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation},
annote = {In this paper, we present mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.},
doi = {10.1016/j.apenergy.2022.118745},
url = {https://www.osti.gov/biblio/1853992},
journal = {Applied Energy},
issn = {ISSN 0306-2619},
volume = {313},
place = {United States},
publisher = {Elsevier},
year = {2022},
month = {03}}
ur Rehman, Waqas; Sajjad, Intisar A.; Malik, Tahir N.
2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)https://doi.org/10.1109/EEEIC.2017.7977733
Bayram, I. Safak; Michailidis, George; Devetsikiotis, Michael
2011 IEEE Second International Conference on Smart Grid Communications (SmartGridComm), 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm)https://doi.org/10.1109/SmartGridComm.2011.6102396