Optimal configuration planning of vehicle sharing station-based electro-hydrogen micro-energy systems for transportation decarbonization. (10th February 2023)

• Record Type: Journal Article
• Authors: Zeng, Bo; Wang, Wenshi; Zhang, Weixiang; Wang, Yuqing; Tang, Chenghong; Wang, Jingtao
• Is Part Of: Journal of cleaner production. Volume 387(2023)
• Publication Date: 2023-02-10
• Subjects: Vehicle sharing station -- User's choice preference -- Evolutionary game -- Electricity -- Hydrogen micro energy network planning -- Interval-stochastic hybrid optimization; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2023.135906
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: With the popularization of electric vehicles and hydrogen fuel vehicles, establishing an eco-friendly and economic-affordable fuel supply system turns out to be critical for the decarbonization of transportation sector. To achieve this, this paper proposes a systematic methodological framework to facilitate optimal configuration planning of an electric-hydrogen micro-energy system with vehicle sharing stations (EHVS). The proposed approach is based on the notion of integrated resource planning, which combines supply side with demand side simultaneously. The problem is formulated as a two-stage hybrid stochastic-interval programming, where the first-stage is aimed at minimizing the investment cost by determining the optimal configuration planning, while the second-stage is aimed at maximizing the expected benefits through optimal operation simulation of the system. The potential flexibility of vehicular demands in response to the rental price-setting has been explicitly considered in this work and represented using an evolutionary game model. Through this, the substitutability between different vehicle demands and its impact on the long-term planning of electric-hydrogen integrated energy system can be properly captured. A hybrid interval-stochastic method is presented to handle different types of uncertainties involved in the discussed problem, wherein the scenario analysis, the interval order relation and the fuzzy preference methods are jointly utilized. The resultant problem is solved with a genetic-algorithm based framework, and implemented in the MATLAB environment. The simulation results show that, compared with conventional independent planning, there could be an improvement in the carbon emission reduction by 24.74% and an additional cost saving of 11.97% achievable using the proposed approach. Highlights: Decarbonization via electric-hydrogen system with vehicle sharing stations is studied. Flexibility of vehicular energy demands based on rental pricing is considered. Long-term evolution of users' behavioral pattern is modeled via evolutionary game. Hybrid interval-stochastic approach is used to handle different uncertainties. A carbon emission reduction of 24.74% and cost saving of 11.97% are achieved.