面向低碳交通的含新能源汽车共享站电-氢微能源网区间-随机混合规划方法

doi:10.19595/j.cnki.1000-6753.tces.L10038

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Abstract

Under the rapid development of electric vehicles (EV) and hydrogen fuel vehicles (HFV), the construction of electric-hydrogen coupling micro-energy networks based on terminal parking lots and renewable energy hydrogen production technology is an important means to effectively promote the low-carbon transformation of the transportation field. The current research on micro-energy grid planning based on parking lot rarely considers the load flexibility brought by the traffic substitutability between EV and HFV, and guides users' long-term vehicle choice preferences by optimizing the price to promotes the consumption of renewable energy source(RES). Considering that the new energy vehicles (NEV) sharing station under the leasing mode is one of the typical scenarios to realize the vehicle demand substitution and energy conversion demand transformation between EV and HFV, this paper takes the new energy vehicle sharing station-based electro-hydrogen micro-energy system (VSEHS) as the research object. In this paper, a two-stage VSEHS planning framework with capacity allocation and vehicle rental price co-optimization is proposed based on the concept of comprehensive resource planning and hybrid interval/stochastic optimization method.
Firstly, the VSEHS architecture and the low-carbon operation mode considering multi-energy and multi-vehicle coordination is described. Secondly, according to the difficulty of obtaining the probabilistic distribution, a hybrid modeling method combining interval and probability is used to deal with the uncertainty of supply side and load side. Secondly, the long-term preference and evolutionary modeling of users' car-rental based on evolutionary game are carried out to describe the potential flexibility of user demand on rental pricing under car-sharing services. And then, on the basis of using rental price to guide user demand, considering the influence of various uncertain factors, the capacity allocation and pricing decision optimization model of VSEHS based on interval-stochastic hybrid programming is constructed. Finally, an interval-stochastic hybrid optimization method is proposed to normalize different types of uncertain variables, and achieve efficient solutions based on heuristic algorithms under the same framework.
The simulation results of VSEHS planning for an urban community show that, under the optimum planning scheme, the rental prices of EV and HFV are 0.483 ¥/min and 0.717 ¥/min respectively. At this price level, 30% of users refuse to participate in the rental service, 49% and 21% of users choose to rent EV and HFV, respectively. Through the coordinated optimization of vehicle scheduling and electric-hydrogen energy conversion scheduling, the hydrogen self-sufficiency rate of the system reaches 91.3%, which can ensure that HFV is basic comes from the RES. The planning schemes under different scenarios show that, compared with the independent operation, the annual net investment and environmental benefits of electric-hydrogen integrated planning can be increased by 11.97% and 24.71%, respectively, and the dynamic optimal pricing mechanism has obvious advantages over the fixed price mechanism. This proves that the electric-hydrogen integrated planning can make greater use of RES and reduce the dependence on external market for electricity and hydrogen energy; for another, it illustrates that under the optimal pricing mechanism, the system can guide the user's choice preferences by energy substitutability in the user's vehicle demand, and then adjust its own planning and operation strategy according to the user's demand. Thus, the improvement of investment efficiency is realized. Finally, the planning schemes of interval/stochastic hybrid optimization and pure stochastic optimization are compared. The results show that, the planning scheme obtained by the pure stochastic optimization is highly dependent on the distribution information of the given data, and the proposed interval/stochastic hybrid planning scheme has better general reliability.
The following conclusions can be drawn from the simulation analysis: (1) the VSEHS planning model considering electron-hydrogen coupling and joint operation of different models can achieve the balance between supply and demand, also realize that NEVs can basically supplied by RES while ensuring the economic benefits. (2) The optimal mechanism of vehicle rental price can not only guide the long-term preferences of users in rental cars to match the planning and operation of VSEHS, but also realize the linkage between price and system cost, which makes full use of the low cost advantage of comprehensive resource planning mode, and increase the interaction profit between supply and demand side. (3) Compared with the traditional pure stochastic optimization method, the VSEHS planning scheme based on interval-random hybrid optimization method can effectively adapt to the situation where the prior information of some parameters is unknown, and has better versatility and reliability.

Key words： New energy vehicle sharing station electro-hydrogen micro-energy network planning evolutionary game pricing for vehicle sharing interval-stochastic hybrid optimization

Received: 13 January 2023

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	Wang Yuqing
	Wang Wenshi
	Xu Xinzhu
	Cai Ruining
	Zhang Weixiang
	Zeng Bo

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Wang Yuqing,Wang Wenshi,Xu Xinzhu等. Hybrid Interval/Stochastic Planning Method for New Energy Vehicle Sharing Station-based Electro-Hydrogen Micro-Energy System for Low-Carbon Transportation[J]. Transactions of China Electrotechnical Society, 2023, 38(23): 6373-6390.

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