| [1] | IEA (2023). Tracking Clean Energy Progress 2023, IEA, Paris. https://www.iea.org/reports/tracking-clean-energy-progress-2023 |
| [2] | Chen X. (2024). Green and low-carbon energy-use. Innov. Energy. 1:100003. DOI:10.59717/j.xinn-energy.2024.100003 |
| [3] | Chen X., Liu J., Lin B., et al. (2025). Promote the Revolution in Energy Use to Enhance the Impetus for Green Transformation and Development. Energy Use. 1:100001. DOI:10.59717/ipj.energy-use.2025.100001 |
| [4] | Chen X. (2025). Energy-use Net: Path to Green and Low-carbon Energy-use. Proceedings of the CSEE, 1-18. https://link.cnki.net/urlid/11.2107.tm.20250909.1416. 003.(in Chinese). |
| [5] | Wang Y., Ma M., Zhou N., et al. (2025). Paving the way to carbon neutrality: Evaluating the decarbonization of residential building electrification worldwide. Sustain. Cities Soc. 130:106549. DOI:10.1016/j.scs.2025.106549 |
| [6] | Liang Y., Yu C., and Pan W. (2025). Energy efficiency, renewables, and electrification contribute to decarbonising the operation of residential building stock in Hong Kong. Energy Build. 349:116520. DOI:10.1016/j.enbuild.2025.116520 |
| [7] | Yu J., Wang Q., Zhang X., et al. (2026). Optimizing photovoltaic energy sharing: A novel framework based on Stackelberg games in distribution networks. Renew. Energy. 256:123870. DOI:10.1016/j.renene.2025.123870 |
| [8] | Ivona Š., Mirna G., and Tomislav C. (2025). Energy sharing: Encouraging citizen participation in energy communities and collective self-consumption. Energy. 338:138911. DOI:10.1016/j.energy.2025.138911 |
| [9] | Kang J., Wang J., Liu C., et al. (2024). Coordinated optimization of configuration and operation of a photovoltaic integrated building cooling system with electricity and ice storages under source-load uncertainties. Energy Build. 320:114600. DOI:10.1016/j.enbuild.2024.114600 |
| [10] | Li G., Xu X., Cheng X., et al. (2025). Robust configuration planning for net zero-energy buildings considering source-load dual uncertainty and hybrid energy storage system. Build. Environ. 282:113239. DOI:10.1016/j.buildenv.2025.113239 |
| [11] | Wu Y., Liu Z., Li B., et al. (2025). Optimal storage capacity for building photovoltaic-energy storage systems considering energy flexibility management. Energy Build. 338:115757. DOI:10.1016/j.enbuild.2025.115757 |
| [12] | Li S., Chen X., Bu L., et al. (2024). Two-stage optimization for the air conditioning system in public buildings with flexible control of indoor load. Energy Build. 312:114162. DOI:10.1016/j.enbuild.2024.114162 |
| [13] | Wang M., Wang M., Wang R., et al. (2024). Optimization scheduling for low-carbon operation of building integrated energy systems considering source-load uncertainty and user comfort. Energy Build. 318:114423. DOI:10.1016/j.enbuild.2024.114423 |
| [14] | Yao Z., Ran L., Wang Z., et al. (2024). Integrated management of electric vehicle sharing system operations and Internet of Vehicles energy scheduling. Energy. 309:132498. DOI:10.1016/j.energy.2024.132498 |
| [15] | IEA (2025). Global EV Outlook 2025, IEA, Paris. https://www.iea.org/reports/global-ev-outlook-2025 |
| [16] | María V., Jose C., Juan G., et al. (2025). Integrating shared mobility into multimodal habits: A comparative analysis across shared micro- and 'macro'-mobility services. Transp. Policy. 174:103840. DOI:10.1016/j.tranpol.2025.103840 |
| [17] | Gao F., Sylvia Y., Han C., et al. (2024). The impact of shared mobility on metro ridership: The non-linear effects of bike-sharing and ride-hailing services. Travel Behav. Soc. 37:100842. DOI:10.1016/j.tbs.2024.100842 |
| [18] | Morteza T., Samuel S., and Xu M. (2022). Widespread range suitability and cost competitiveness of electric vehicles for ride-hailing drivers. Appl. Energy. 319:119246. DOI:10.1016/j.apenergy.2022.119246 |
| [19] | Tang W., Chen X. (Michael), and Lee D-H. (2025). Toward mobility incentive: Integrating green service and carbon inclusion scheme into the ride-hailing market. Transp. Res. B Methodol. 201:103320. DOI:10.1016/j.trb.2025.103320 |
| [20] | Zhang Z., Yu Q., Gao K., et al. (2025). Carbon emission reduction benefits of ride-hailing vehicle electrification considering energy structure. Appl. Energy. 377:124548. DOI:10.1016/j.apenergy.2024.124548 |
| [21] | Li J., Xu X., Hamid R., et al. (2025). Optimization of electric vehicle charging strategies in residential integrated energy systems: A SARIMA model approach for dynamic electricity prices. Energy. 330:136600. DOI:10.1016/j.energy.2025.136600 |
| [22] | Wu H., Lan X., He Y., et al. (2025). Orderly charging of electric vehicles: A two-stage spatial-temporal scheduling method based on user-personalized navigation. Appl. Energy. 378:124800. DOI:10.1016/j.apenergy.2024.124800 |
| [23] | Liu G., Wang B., Li T., et al. (2025). Multi-objective electric-carbon synergy optimisation for electric vehicle charging: Integrating uncertainty and bounded rational behaviour models. Appl. Energy. 389:125790. DOI:10.1016/j.apenergy.2025.125790 |
| [24] | Chen X. (2025). Urban Energy Use and Its Friendly Interaction with Power Grid. Energy Use. 1:100011. DOI:10.59717/ipj.energy-use.2025.100011 |
| [25] | Abdalla M. A. A., Min W., Bing W., et al. (2023). Double-layer home energy management strategy for increasing PV self-consumption and cost reduction through appliances scheduling, EV, and storage. Energy Rep. 10:3494-3518. DOI:10.1016/j.egyr.2023.10.019 |
| [26] | Michele D., Tohid H., Anna R., et al. (2025). Enhancing voltage optimization in distribution networks through flexible operation of EV parking lots. Sustain. Energy Grids Netw. 41:101601. DOI:10.1016/j.segan.2024.101601 |
| [27] | Yan Q., Wang J., Lin T., et al. (2025). Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through ggregators. Int. J. Electr. Power Energy Syst. 169:110812. DOI:10.1016/j.ijepes.2025.110812 |
| [28] | Xiang Y., Yang J., Li X., et al. (2022). Routing optimization of electric vehicles for charging with event-driven pricing strategy. IEEE Trans. Autom. Sci. Eng. 19:7−20. DOI:10.1109/tase.2021.3102997 |
| [29] | Su S., Li Y., Yamashita K., et al. (2024). Electric vehicle charging guidance strategy considering “traffic network-charging station-driver” modeling: a multiagent deep reinforcement learning-based approach. IEEE Trans. Transp. Electrific. 10:4653−4666. DOI:10.1109/tte.2023.3322685 |
| [30] | Tao Y., Qiu J., Lai S., et al. (2024). Distributed electric vehicle assignment and charging navigation in cyber-physical systems. IEEE Trans. Smart Grid. 15:1861−1875. DOI:10.1109/tsg.2023.3293251 |
| [31] | Sun X., and Qiu J. (2021). Hierarchical voltage control strategy in distribution networks considering customized charging navigation of electric vehicles. IEEE Trans. Smart Grid. 12:4752−4764. DOI:10.1109/tsg.2021.3094891 |
| [32] | Habbal A., and Alrifaie M. F. (2024). A user-preference-based charging station recommendation for electric vehicles. IEEE Trans. Intell. Transp. Syst. 25:11617−11634. DOI:10.1109/tits.2024.3379469 |
| [33] | Yi Z., and Smart J. (2021). A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet. Transp. Res., Part D: Transp. Environ. 95:102822. DOI:10.1016/j.trd.2021.102822 |
| [34] | Wang J., Cai H., Sun L., et al. (2025). MERCI: multi-agent reinforcement learning for enhancing on-demand electric taxi operation in terms of rebalancing, charging, and informing orders. Comput. Ind. Eng. 200:110711. DOI:10.1016/j.cie.2024.110711 |
| [35] | Li D., Hu C., Yang Q., et al. (2025). Charge or pick up. Optimizing E-taxi management: a dual-stage heuristic coordinated reinforcement learning approach. IEEE Trans. Autom. Sci. Eng. 22:8533−8553. DOI:10.1109/tase.2024.3486342 |
| [36] | Li X., Normandin-Taillon H., Wang C., et al. (2024). BM-RCWTSG: an integrated matching framework for electric vehicle ride-hailing services under stochastic guidance. Sustain. Cities Soc. 108:105485. DOI:10.1016/j.scs.2024.105485 |
| [37] | Zhong J., Liu J., and Zhang X. (2023). Charging navigation strategy for electric vehicles considering empty-loading ratio and dynamic electricity price. Sustain. Energy Grids Netw. 34:100987. DOI:10.1016/j.segan.2022.100987 |
| [38] | Ni W., Cheng P., Chen L., et al. (2024). Task assignment framework for online car-hailing systems with electric vehicles. IEEE Trans. Knowl. Data Eng. 36:9361−9373. DOI:10.1109/tkde.2024.3434567 |
| [39] | Patankar P. P., Hussain Rather Z., Liebman A., et al. (2025). Machine Learning-Based EV Charging Management System for Vehicle-to-Home and Vehicle-to-Building. IEEE Trans. Transp. Electrific. 11:11100−11111. DOI:10.1109/tte.2025.3571793 |
| [40] | Dai Y., Liu X., Li H., et al. (2025). Building-related electric vehicle charging behaviors and energy consumption patterns: An urban-scale analysis. Transp. Res., Part D: Transp. Environ. 141:104663. DOI:10.1016/j.trd.2025.104663 |
| Gan L., Jia Z., Bu L., et al. (2025). Charging Guidance Strategy for Electric Ride-Hailing Vehicles Oriented Towards Building Energy Sharing. Energy Use 1:100027. https://doi.org/10.59717/ipj.energy-use.2025.100027 |
To request copyright permission to republish or share portions of our works, please visit Copyright Clearance Center's (CCC) Marketplace website at marketplace.copyright.com.
Module operation sequence of mobility-energy sharing service
Three-layer dynamic queue model of CS
CS service rates and their deviations across two Scenarios
Comparison of reservation rates between central-area CS 8 and remote-area CS 13 in operation time period under two Scenarios
Mobility duration and queue waiting time of electric ride-hailing vehicles across two Scenarios. (A-B) Mobility duration distribution. (C-D) Queue waiting time distribution.