scholarly journals Impact of Electric Vehicles as Distributed Energy Storage in Isolated Systems: The Case of Tenerife

2015 ◽  
Vol 7 (11) ◽  
pp. 15152-15178 ◽  
Author(s):  
Alfredo Díaz ◽  
Francisco Ramos-Real ◽  
Gustavo Marrero ◽  
Yannick Perez
2021 ◽  
Vol 2121 (1) ◽  
pp. 012030
Author(s):  
Xiaomei Li ◽  
Rong Cao ◽  
Wenbo Hao ◽  
Mingyu Xu ◽  
Heng Hu ◽  
...  

Abstract Aiming at the problem that large-scale disorderly grid connection of electric vehicles negatively affects grid operation and causes a large amount of abandoned wind and abandoned light, an orderly grid connection cooperative scheduling control strategy based on distributed energy storage of electric vehicles is proposed. The strategy takes the charging and discharging price as the lever to guide the users to charge and discharge in an orderly manner, takes the optimal economics on the user side and the optimal cost of power generation on the grid side as the objective function, and uses linear weighting normalization to convert the multi-objective function into a single objective function for simulation solution. The simulation results show that the effect of peak shaving and valley filling can be achieved on the basis of satisfying users’ demand, and renewable energy can be effectively consumed.


Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1436 ◽  
Author(s):  
Moses Amoasi Acquah ◽  
Sekyung Han

Robust operation of load management control for a building is important to account for the uncertainty in demand as well as any distributed sources connected to the building. This paper discussed an online load management control solution using distributed energy storage (DES) while considering uncertainties in demand as well as DES to reduce peak demand for economic benefit. In recent years’ demand-side management (DSM) solutions using DES such as stationary energy management system (BESS) and plugged-in electric vehicles (PEV) have been popularised. Most of these solutions resort to deterministic load forecast for the day ahead energy scheduling and do not consider the uncertainties in demand and DES making these solutions vulnerable to uncertainties. This study presents an online density demand forecast, k-means clustering of PEV groups and stochastic optimisation for robust operation of BESS and PEV for a building. The proposed method accounts for uncertainties in demand and uncertainties due to mobile energy storage as presented by PEVs. For a case study, we used data obtained from an industrial site in South Korea. The verified results as compared to other methods with a deterministic approach prove the solution is efficient and robust.


Author(s):  
Ricardo Morales ◽  
Jesus Fraile-Ardanuy ◽  
Alvaro Gutierrez ◽  
David Jimenez ◽  
Benito Artaloytia ◽  
...  

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