Quantifying the real-time energy flexibility of commuter plug-in electric vehicles in an office building considering photovoltaic and load uncertainty

Zhenyu Yu, Fei Lu, Yu Zou and Xudong Yang

Applied Energy, 2022, vol. 321, issue C, No S0306261922007097

Abstract: The widespread use of fluctuating renewable electricity has introduced challenges in balancing power systems. This can be alleviated by using flexible resources on the demand side to provide ancillary services at various timescales (e.g., day-ahead planning or real-time operation). However, practitioners lack a unified framework for measuring energy flexibility in the real-time operation frame. This study considers a control structure for clustered commuter plug-in electric vehicles (PEVs) in an office building with both day-ahead scheduling and real-time dispatch and proposes a generic quantification framework for assessing the capability of PEVs to manage the uncertainties of photovoltaic output and inflexible building load. Our evaluation considered the flexibility shortage in terms of power, energy, and control strategy, and the Monte Carlo method was used for probabilistic analysis. We conducted a sensitivity analysis to identify the key factors determining real-time flexibility. The results suggest that 1.5–2 times the number of PEVs is required to meet the defined level of real-time flexibility rather than planning flexibility. Possible conflicts in flexibility enhancement at different timescales and directions were observed under various day-ahead scheduling strategies; prediction information can be used to mitigate conflicts in scheduling strategies and improve the overall control performance.

Keywords: Flexibility evaluation; Electric vehicle; Demand response; Uncertainty modeling; Day-ahead scheduling; Real-time dispatch (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.apenergy.2022.119365

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