Three-stage optimization of integrated energy system considering source/load uncertainties and orderly charging of NEVs

Xiaofeng Zhang, Yu Zhan, Tingbo Zhao, Jin Mei, Fan Jiao, Rong Zeng, Xiaoqin Sun and Meng Wang

Energy, 2024, vol. 313, issue C

Abstract: New energy vehicles are seeing robust growth as newly registered vehicles reached 7.43 million in 2023, with an increase of 38.76 % compared to that of 2022. Since energy consumption in building and transportation fields rises year by year, there is an urgent need for novel integrated energy system optimization solution. This study presented a three-stage optimization model for renewable energy/natural gas hybrid integrated energy system, which considers orderly charging scheduling of new energy vehicles and uncertainties of solar radiation and new energy vehicles load. Four scenarios based on different combinations of uncertainties and orderly charging strategy are designed and investigated. Three-stage multi-objectives for integrated energy system are solved and optimized by mixed integer linear programming. Results showed that scenario considering both uncertainties and new energy vehicles dispatching can obtain the optimal performances with primary energy saving rate, CO2 emission reduction rate and total expenditure saving rate of 56.6 %, 46.0 % and 35.6 %, system independence is improved with grid interaction level of 44.5 %. Besides, load variances of electric and hydrogen vehicles are reduced by 28.44 % and 3.18 % after new energy vehicles scheduling. In summary, performance of integrated energy system can be improved considering source/load uncertainties and scheduling of new energy vehicles.

Keywords: Integrated energy system; Electric vehicle; Hydrogen vehicle; Three-stage multi-objective optimization; Uncertainty; Orderly charging (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224034959

DOI: 10.1016/j.energy.2024.133717

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