Smart City Gnosys

Smart city article details

Title When Shared Autonomous Electric Vehicles Meet Microgrids: Citywide Energy-Mobility Orchestration
ID_Doc 61760
Authors Qi W.; Sha M.; Li S.
Year 2022
Published Manufacturing and Service Operations Management, 24, 5
DOI http://dx.doi.org/10.1287/msom.2021.1050
Abstract Problem definition: We develop a crossdisciplinary analytics framework to understand citywide mobility-energy synergy. In particular, we investigate the potential of shared autonomous electric vehicles (SAEVs) for improving the self-sufficiency and resilience of solar-powered urban microgrids. Academic/practical relevance: Our work is motivated by the ever-increasing interconnection of energy and mobility service systems at the urban scale. We propose models and analytics to characterize the dynamics of the SAEV-microgrid service systems, which were largely overlooked by the literature on service operations and vehicle-grid integration (VGI) analysis. Methodology: We develop a space-time-energy network representation of SAEVs. Then, we formulate linear program models to incorporate an array of major operational decisions interconnecting the mobility and energy systems. To preventatively ensure microgrid resilience, we also propose an “N − 1” resilience-constrained fleet dispatch problem to cope with microgrid outages. Results: Combining eight data sources of New York City, our results show that 80,000 SAEVs in place of the current ride-sharing mobility assets can improve the microgrid self-sufficiency by 1.45% (benchmarked against the case without grid support) mainly via the spatial transfer of electricity, which complements conventional VGI. Scaling up the SAEV fleet size to 500,000 increases the microgrid self-sufficiency by 8.85% mainly through temporal energy transfer, which substitutes conventional VGI. We also quantify the potential and trade-offs of SAEVs for peak electricity import reduction and ramping mitigation. In addition, microgrid resilience can be enhanced by SAEVs, but the actual resilience level varies by microgrids and by the hour when grid contingency occurs. The SAEV fleet operator can further maintain the resilience of pivotal microgrid areas at their maximum achievable level with no more than a 1% increase in the fleet repositioning trip length. Managerial implications: Our models and findings demonstrate the potential in deepening the integration of urban mobility and energy service systems toward a smart-city future. Copyright: © 2021 INFORMS.
Author Keywords shared autonomous electric vehicles; smart city operations; solar-powered microgrids


Similar Articles


Id Similarity Authors Title Published
22500 View0.887Ahmed I.; Basit A.; Ahmad M.; AlMuhaini M.; Khalid M.Electric Mobility Challenges And Approaches For Sustainable Green Power Synergy In Smart CitiesArabian Journal for Science and Engineering, 50, 8 (2025)
40803 View0.873Fernandez V.; Pérez V.; Roig R.Optimizing Energy Supply For Full Electric Vehicles In Smart Cities: A Comprehensive Mobility Network ModelWorld Electric Vehicle Journal, 16, 1 (2025)
40890 View0.873Algburi S.; Al-Dulaimi O.; Fakhruldeen H.F.; Isametdinova S.; Sapaev I.B.; Islam S.; Naveed Q.N.; Lasisi A.; alhani I.; Hassan Q.; Khalaf D.H.; Ssebunya M.; Jabbar F.I.Optimizing Smart Grid Flexibility With A Hybrid Minlp Framework For Renewable Integration In Urban Energy SystemsEnergy Reports, 14 (2025)
53110 View0.872Gill A.; Ramachandran T.; Upadhyay R.; Agarwal Gautam A.Strategic Grid Integration Of Renewable Using Electric Vehicles For Smart Cities StabilityE3S Web of Conferences, 540 (2024)
51618 View0.87Jiang J.; Li Y.; Li Y.; Li C.; Yu L.; Li L.Smart Transportation Systems Using Learning Method For Urban Mobility And Management In Modern CitiesSustainable Cities and Society, 108 (2024)
16309 View0.869Simsek M.; Omara A.; Kantarci B.Cost-Aware Data Aggregation And Energy Decentralization With Electrical Vehicles In Microgrids Through Lte Links2020 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2020 (2020)
47360 View0.868Qi W.; Zhang Y.; Zhang N.Scaling Up Electric-Vehicle Battery Swapping Services In Cities: A Joint Location And Repairable-Inventory ModelManagement Science, 69, 11 (2023)
39820 View0.867Kremzow-Tennie S.; Mecit H.On The Convergence Of Electric Mobility And Energy Systems- Potentials And Challenges2024 22nd International Conference on Research and Education in Mechatronics, REM 2024 (2024)
43000 View0.867Reza Salehizadeh M.; Kubra Erenoglu A.; Sengor I.; Tascikaraoglu A.; Erdinc O.; Liu J.; Catalao J.P.S.Preventive Energy Management Strategy Before Extreme Weather Events By Modeling Evs' Opt-In PreferencesIEEE Transactions on Intelligent Transportation Systems, 25, 11 (2024)
21693 View0.865Watanabe T.; Wasa Y.; Susuki Y.; Miwa Y.; Hirata K.; Tanaka K.Economic Optimization For Dynamic Cross-Sector Resilience Design Of Energy And Mobility Via Evs: An Emergency AnalysisIFAC-PapersOnLine, 56, 2 (2023)