Queueing Theory-Based Optimal Decision-Making Model of Battery Energy Storage-Assisted Fast Charging Station Participating in Emergency Demand Response

Author(s):  
Jun Wang ◽  
Dan Wu ◽  
Wanru Zhao ◽  
Shanshan Shi ◽  
Bishal Upadhaya ◽  
...  
2010 ◽  
Vol 14 (1) ◽  
pp. 74-88 ◽  
Author(s):  
Domenico Conforti ◽  
Francesca Guerriero ◽  
Rosita Guido ◽  
Marco Matucci Cerinic ◽  
Maria Letizia Conforti

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 558 ◽  
Author(s):  
Yian Yan ◽  
Huang Wang ◽  
Jiuchun Jiang ◽  
Weige Zhang ◽  
Yan Bao ◽  
...  

With the pervasiveness of electric vehicles and an increased demand for fast charging, stationary high-power fast-charging is becoming more widespread, especially for the purpose of serving pure electric buses (PEBs) with large-capacity onboard batteries. This has resulted in a huge distribution capacity demand. However, the distribution capacity is limited, and in some urban areas the cost of expanding the electric network capacity is very high. In this paper, three battery energy storage system (BESS) integration methods—the AC bus, each charging pile, or DC bus—are considered for the suppression of the distribution capacity demand according to the proposed charging topologies of a PEB fast-charging station. On the basis of linear programming theory, an evaluation model was established that consider the influencing factors of the configuration: basic electricity fee, electricity cost, cost of the energy storage system, costs of transformer and converter equipment, and electric energy loss. Then, a case simulation is presented using realistic operation data, and an economic comparison of the three configurations is provided. An analysis of the impacts of each influence factor in the case study is discussed to verify the case results. The numerical results indicate that the appropriate BESS configuration can significantly reduce the distribution demand and stationary cost synchronously.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Wei Li ◽  
Hang Wu ◽  
Liurui Deng

We investigate how the diversity of consumers’ perceived value in different remanufacturing modes affects remanufacturing decision-making. We establish a two-stage optimal decision-making model of original equipment manufacturer (OEM) remanufacturing and a noncooperative game model of third party remanufacturer (TPR) remanufacturing and then analyze the optimal decisions of OEM and TPR. Comparing the effects of consumers’ perceived value on remanufacturing decision-making in different modes, we find that when OEM remanufactures products, consumers’ perceived value has a negative effect on new products’ price and quantity and has a positive effect on remanufactured products’ quantity and when TPR remanufactures products, consumers’ perceived value has a positive effect on new products price and quantity and has a negative effect on remanufactured products’ quantity. Compared with OEM remanufacturing, TPR remanufacturing can raise the profits of OEM and whole closed-loop supply chain, but it will lower the quantity of remanufacturing products.


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