scholarly journals A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System

Energies ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 229 ◽  
Author(s):  
Yan Bao ◽  
Yu Luo ◽  
Weige Zhang ◽  
Mei Huang ◽  
Le Wang ◽  
...  
Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2048 ◽  
Author(s):  
Rodrigo Martins ◽  
Holger Hesse ◽  
Johanna Jungbauer ◽  
Thomas Vorbuchner ◽  
Petr Musilek

Recent attention to industrial peak shaving applications sparked an increased interest in battery energy storage. Batteries provide a fast and high power capability, making them an ideal solution for this task. This work proposes a general framework for sizing of battery energy storage system (BESS) in peak shaving applications. A cost-optimal sizing of the battery and power electronics is derived using linear programming based on local demand and billing scheme. A case study conducted with real-world industrial profiles shows the applicability of the approach as well as the return on investment dependence on the load profile. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, peak-power tariff, and battery aging. This underlines the need for a general mathematical optimization approach to efficiently tackle the challenge of peak shaving using an energy storage system. The case study also compares the applicability of yearly and monthly billing schemes, where the highest load of the year/month is the base for the price per kW. The results demonstrate that batteries in peak shaving applications can shorten the payback period when used for large industrial loads. They also show the impacts of peak shaving variation on the return of investment and battery aging of the system.


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.


2018 ◽  
Vol 8 (8) ◽  
pp. 1212 ◽  
Author(s):  
Yian Yan ◽  
Jiuchun Jiang ◽  
Weige Zhang ◽  
Mei Huang ◽  
Qiang Chen ◽  
...  

In order to reduce the recharging time of electric vehicles, the charging power and voltage are becoming higher, which has led to a huge distribution capacity demand and load fluctuation, especially in pure electric buses (PEBs) with large onboard batteries. Based on one actual direct current (DC) fast-charging station, a two-step strategy for the suppression of the peak charging power was developed in this paper, which combined charging optimization and a battery energy storage system (BESS) configuration. A novel charging strategy was proposed, with the PEBs fast-charging during operating hours and normal charging at night, based on a new charging topology. Then, a charging sequence optimization model was established, according to the operation characteristics analysis of the DC fast-charging station. The particle swarm optimization (PSO) algorithm is applied to optimize the charging sequence, which is disordered at present. Linear programming is used to configure the battery energy storage system in order to further decrease the peak charging power and satisfy the distribution capacity constraint. The two-step strategy was simulated by the dataset from the real station. The results show that the distribution capacity demand, charging load fluctuation, electricity cost, and size of the BESS were significantly decreased.


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